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SPSS® 12.0 Command Syntax Reference
SPSS® 12.0 Command Syntax Reference
SPSS® 12.0 Command Syntax Reference
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PACF<br />
Overview<br />
Options<br />
PACF [VARIABLES=] series names<br />
[/DIFF={1}]<br />
{n}<br />
[/SDIFF={1}]<br />
{n}<br />
[/PERIOD=n]<br />
[/{NOLOG**}]<br />
{LN }<br />
[/SEASONAL]<br />
[/MXAUTO={16**}]<br />
{n }<br />
[/APPLY [=’model name’]]<br />
**Default if the subcommand is omitted and there is no corresponding specification on the TSET command.<br />
Example<br />
PACF TICKETS<br />
/LN<br />
/DIFF=1<br />
/SDIFF=1<br />
/PERIOD=12<br />
/MXAUTO=25.<br />
PACF displays and plots the sample partial autocorrelation function of one or more time<br />
series. You can also display and plot the partial autocorrelations of transformed series by<br />
requesting natural log and differencing transformations from within the procedure.<br />
Modifying the Series. You can request a natural log transformation of the series using the LN<br />
subcommand and seasonal and nonseasonal differencing to any degree using the SDIFF<br />
and DIFF subcommands. With seasonal differencing, you can specify the periodicity on the<br />
PERIOD subcommand.<br />
Statistical Output. With the MXAUTO subcommand, you can specify the number of lags for<br />
which you want values displayed and plotted, overriding the maximum specified on TSET.<br />
You can also display and plot values only at periodic lags using the SEASONAL subcommand.<br />
1185
PACF Overview Options PACF [VARIABLES=] series names [/DIFF={1}] {n} [/SDIFF={1}] {n} [/PERIOD=n] [/{NOLOG**}] {LN } [/SEASONAL] [/MXAUTO={16**}] {n } [/APPLY [=’model name’]] **Default if the subcommand is omitted and there is no corresponding specification on the TSET command. Example PACF TICKETS /LN /DIFF=1 /SDIFF=1 /PERIOD=12 /MXAUTO=25. PACF displays and plots the sample partial autocorrelation function of one or more time series. You can also display and plot the partial autocorrelations of transformed series by requesting natural log and differencing transformations from within the procedure. Modifying the Series. You can request a natural log transformation of the series using the LN subcommand and seasonal and nonseasonal differencing to any degree using the SDIFF and DIFF subcommands. With seasonal differencing, you can specify the periodicity on the PERIOD subcommand. Statistical Output. With the MXAUTO subcommand, you can specify the number of lags for which you want values displayed and plotted, overriding the maximum specified on TSET. You can also display and plot values only at periodic lags using the SEASONAL subcommand. 1185
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SPSS® 12.0 Command Syntax Referenc
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Universals This part of the SPSS Sy
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Commands 5 before processing. All u
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Commands 7 • Subcommands begin wi
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Commands 9 • Transformation comma
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Files SPSS reads, creates, and writ
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SPSS-Format Data File Files 13 An S
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SPSS Matrix Data Files Files 15 An
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Files 17 4. VARNAME_ variable (or F
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Figure 6 Dictionary of a matrix sys
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Variables To prepare data for proce
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Keyword TO Variables 23 You can est
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Variable Formats Variables 25 SPSS
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Format type Description Ew.d Scient
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Table 4 Numeric formats with punctu
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Variables 31 PIBHEXw (hexadecimal o
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Variables 33 RBw (real binary): The
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Variables 35 is read as two separat
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Transformation Expressions Transfor
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SQRT(arg) Square root. SQRT(SIBS) i
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The following are suffixes for cont
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Transformation Expressions 43 0≤p
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Domain Errors Transformation Expres
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Transformation Expressions 47 origi
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Transformation Expressions 49 • L
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NOT Logical Operator Transformation
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and COMPUTE lagvar=LAG(var1). EXECU
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Date and Time SPSS reads and writes
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Input Data Specification Date and T
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The LIST output from these commands
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Date and Time 61 • A time interva
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Aggregation Functions Date and Time
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Conversion Functions Date and Time
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Date and Time 67 XDATE.HOUR(arg) Re
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Precautions with Date and Time Vari
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72 ACF and DIFF subcommands. With s
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74 ACF SDIFF Subcommand If the seri
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76 ACF SERROR Subcommand SERROR spe
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ADD DOCUMENT ADD DOCUMENT ’text
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ADD FILES ADD FILES FILE={file} {*
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82 ADD FILES • The resulting file
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84 ADD FILES • Input data files a
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86 ADD FILES FIRST and LAST Subcomm
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88 ADD VALUE LABELS • The added v
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AGGREGATE AGGREGATE OUTFILE={file}
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92 AGGREGATE Example Example • If
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94 AGGREGATE Example AGGREGATE OUTF
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96 AGGREGATE FIN(varlist,value1,val
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98 AGGREGATE • User-missing value
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ALSCAL ALSCAL VARIABLES=varlist [/F
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102 ALSCAL Operations • ALSCAL ca
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104 ALSCAL ASYMMETRIC Asymmetric da
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106 ALSCAL • INITIAL is the defau
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108 ALSCAL differences model propos
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110 ALSCAL • Algorithmic options
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112 ALSCAL Table 2 Types of configu
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Matrix mode Object by object 114 AL
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Matrix mode Object by object Object
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118 Syntax Reference Basic Specific
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120 Syntax Reference Example DATA L
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122 Syntax Reference PLOT Subcomman
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124 Syntax Reference VARNAME_ Strin
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ANOVA ANOVA [VARIABLES=] varlist BY
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Example Example ANOVA 129 ANOVA VAR
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ANOVA 131 Some restrictions apply t
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Table 2 Combinations of COVARIATES
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Multiple Classification Analysis AN
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APPLY DICTIONARY 137 • The applie
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APPLY DICTIONARY 139 target file as
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APPLY DICTIONARY 141 MRSETS = MERGE
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APPLY DICTIONARY 143
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Options Basic Specification Subcomm
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• Only one method can be specifie
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APPLY Subcommand AREG 149 • Itera
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AREG 151
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Options Basic Specification ARIMA 1
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Limitations Example ARIMA 155 • F
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D Order of differencing. Q Moving-a
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Termination Criteria Subcommands CI
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References ARIMA 161 Akaike, H. 197
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Subcommand Order • VARIABLES must
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Example AUTORECODE 165 DATA LIST /
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BEGIN DATA—END DATA BEGIN DATA da
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BREAK BREAK Overview BREAK controls
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CASEPLOT Overview CASEPLOT [VARIABL
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Subcommand Order • Subcommands ca
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LN and NOLOG Subcommands CASEPLOT 1
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CASEPLOT 177 erence line. Figure 3
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CASEPLOT 179 • If FORMAT=REFERENC
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Options CASESTOVARS 181 Automatic c
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The commands: CASESTOVARS 183 SPLIT
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create a new file with the followin
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SEPARATOR Subcommand CASESTOVARS 18
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CATPCA CATPCA is available in the C
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Optional output. You can request op
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CATPCA 193 • The NORMALIZATION su
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SPORD and SPNOM Keywords The follow
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ACTIVE Keyword The ACTIVE keyword h
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MAXITER Subcommand CATPCA 199 MAXIT
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CATPCA 201 The keyword TO in a vari
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TRIPLOT(varlist(varlist))(n) CATPCA
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CATPCA 205 procedures with the succ
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CATREG Overview CATREG is available
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Operations Limitations CATREG 209
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ANALYSIS Subcommand LEVEL Keyword C
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GROUPING Keyword DISTR Keyword MISS
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PRINT Subcommand CATREG 215 The PRI
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SAVE Subcommand OUTFILE Subcommand
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CCF Overview Options CCF [VARIABLES
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CCF 221 • LN transforms the data
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CCF 223 • If a natural log transf
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CLEAR TRANSFORMATIONS Overview CLEA
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Example Overview Options CLUSTER V1
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CLUSTER 229 • The variable list i
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Measures for Binary Data CLUSTER 23
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DICE[(p[,np])] Dice (or Czekanowski
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Y( x, y) ad - bc = ----------------
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CLUSTER 237 MEDIAN Median clusterin
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CLUSTER 239 • This example displa
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Matrix Input CLUSTER 241 • The ma
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Example Example Example DATA LIST F
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COMMENT {COMMENT} text { * } Overvi
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Cumulative distribution functions (
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Cumulative distribution functions (
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Logical functions: RANGE(varname,ra
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String Transformations COMPUTE 253
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Examples COMPUTE 255 • The string
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COMPUTE 257 • Alternatively, you
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Equivalence COMPUTE 259 STRING DEPT
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CONJOINT Overview CONJOINT is avail
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CONJOINT 263 the experimental profi
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CONJOINT 265 • The ADD FILES comm
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CONJOINT 267 subject is asked to as
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CONJOINT 269 • New value labels a
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PLOT Subcommand CONJOINT 271 The PL
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Basic Specification CORRELATIONS 27
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MISSING Subcommand CORRELATIONS 275
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Example CORRELATIONS 277 • CORREL
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CORRESPONDENCE CORRESPONDENCE is av
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Syntax Rules Operations Limitations
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DIMENSION Subcommand CORRESPONDENCE
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CORRESPONDENCE 285 EUCLID Euclidean
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PLOT Subcommand NONE No output othe
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CORRESPONDENCE 289 DIM1...DIMn Nume
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COUNT COUNT varname=varlist(value l
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COXREG COXREG is available in the A
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Basic Specification COXREG 295 •
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VARIABLES Subcommand COXREG 297 VAR
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COXREG 299 • If the categorical v
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COXREG 301 BSTEP Backward stepwise.
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CRITERIA Subcommand COXREG 303 CRIT
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COXREG 305 TABLE Write the survival
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CREATE CREATE new series={CSUM (ser
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Example CREATE NEWVAR1 = DIFF(OLDVA
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LAG Function CREATE 311 LAG creates
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Example CREATE TICKMA = MA(TICKETS,
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T4253H Function CREATE 315 T4253H p
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Overview Options CROSSTABS 317 CROS
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Example CROSSTABS 319 • The varia
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CROSSTABS 321 • VARIABLES names t
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CROSSTABS 323 CORR Display Pearson
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FORMAT Subcommand CROSSTABS 325 By
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CROSSTABS 327 • The split-file gr
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CROSSTABS 329
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Operations CSDESCRIPTIVES 331 • C
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CSDESCRIPTIVES 333 • Plan file an
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CSDESCRIPTIVES 335 • The set of s
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CSDESCRIPTIVES 337
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CSSELECT 339 inclusion probabilitie
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PLAN Subcommand CSSELECT 341 The PL
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Example CSPLAN /PLAN OUTFILE=’c:\
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CSSELECT 345
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Design Block: Stages 2 and 3 CSPLAN
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Example Overview Options CSPLAN SAM
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CSPLAN 351 • A PLAN subcommand is
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Stratified sample design CSPLAN SAM
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CSPLAN 355 • The variable samplew
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CSPLAN 357 Typically the previous w
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CSPL AN 359 • CLUSTER is required
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SIZE Subcommand CSPLAN 361 The SIZE
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MINSIZE Keyword CSPLAN 363 MINSIZE
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Keyword Default Root Name Descripti
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CSPLAN 367 strata only the last one
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CSPLAN 369
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CSTABULATE 371 • This specificati
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CSTABULATE 373 on the left defines
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CSTABULATE 375 • For example, /SU
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ADJUST= {BONFERRONI} ORIGIN=COLUMN
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Example Think of self as liberal or
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Example CTABLES /TABLE HAPPY. Gener
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Scale Variables CTABLES 383 Scale v
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CTABLES 385 • Each summary functi
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Table 2 Summary functions: scale va
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Table 3 Summary functions: multiple
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Missing Values in Summaries CTABLES
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Example CTABLES 393 CTABLES /TABLE
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CTABLES 395 • The SUBTOTAL keywor
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Totals Example CTABLES /TABLE AGE [
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CTABLES 399 CORNER Corner text. Cor
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Pairwise Comparisons of Proportions
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CTABLES 403 EMPTY Fill characters u
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CURVEFIT CURVEFIT [VARIABLES=] varn
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Operations CURVEFIT 407 • When CU
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CURVEFIT 409 • This command fits
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APPLY Subcommand CURVEFIT 411 APPLY
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Example Overview Options Week and y
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Fixed-Format Data DATA LIST 415 •
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DATA LIST 417 LIST Freefield data w
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DATA LIST 419 • RECORDS can be us
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Example DATA LIST 421 INPUT PROGRAM
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Variable Names DATA LIST 423 • Va
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Example * Mixing column-style and F
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DATA LIST 427 • For freefield dat
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DATA LIST 429 • The width (w) por
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DATE DATE keyword [starting value [
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DATE 433 • The starting value is
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DATE 435 • For DAY_, the starting
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Example 5 DATE Y 1950 Q 2 M. DATE 4
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The following is a partial listing
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Example DEFINE sesvars () age sex e
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Example Example * Macro without arg
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DEFINE—!ENDDEFINE 445 • The mac
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DEFINE—!ENDDEFINE 447 • This ex
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Example * Keyword !CHAREND. DEFINE
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DEFINE—!ENDDEFINE 451 !DEFAULT De
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DEFINE—!ENDDEFINE 453 !HEAD (str)
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Conditional Processing DEFINE—!EN
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DEFINE—!ENDDEFINE 457 • The fir
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DEFINE—!ENDDEFINE 459
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DESCRIPTIVES Overview Options DESCR
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Z Scores DESCRIPTIVES 463 The z-sco
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MAX Maximum observed value. SUM Sum
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DISCRIMINANT DISCRIMINANT GROUPS=va
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Basic Specification DISCRIMINANT 46
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DISCRIMINANT 471 • Variables shou
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Example DISCRIMINANT 473 DISCRIMINA
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DISCRIMINANT 475 • You can set FI
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SAVE Subcommand DISCRIMINANT 477 SA
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STATISTICS Subcommand DISCRIMINANT
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• The default keywords for CLASSI
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Matrix Input DISCRIMINANT 483 recor
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Example Example Example * Use matri
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DISPLAY DISPLAY [SORTED] [{NAMES**
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DISPLAY 489 • If the keyword SORT
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Example Example DOCUMENT 491 • If
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Overview DO IF 493 The DO IF—END
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Flow of Control DO IF 495 • If th
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Example DO IF 497 DO IF (YRHIRED GT
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Nested DO IF Structures DO IF 499 T
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DO REPEAT—END REPEAT DO REPEAT st
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Example DO REPEAT—END REPEAT 503
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Figure 2 Output from the PRINT subc
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ECHO ECHO "text". Example Overview
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Operations Example END CASE 509 •
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END CASE 511 • Data are extracted
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END CASE 513 BEGIN DATA 1 AC 91 2 C
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END CASE 515 • The frequencies ta
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Example Example *Select cases. INPU
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EXAMINE EXAMINE VARIABLES=varlist [
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Example EXAMINE VARIABLES=MIPERGAL
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• The method keywords follow the
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STATISTICS Subcommand EXAMINE 525 S
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EXAMINE 527 PAIRWISE Delete cases w
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EXPORT EXPORT OUTFILE=file [/TYPE={
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EXPORT 531 • Tape density—200,
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DROP and KEEP Subcommands EXPORT 53
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EXSMOOTH EXSMOOTH is available in t
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Subcommand Order Syntax Rules Opera
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Table 1 Models for different types
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Example EXSMOOTH 541 EXSMOOTH VAR2
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INITIAL Subcommand EXSMOOTH 543 •
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References EXSMOOTH 545 • The fir
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Example Overview Options FACTOR VAR
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Operations Example FACTOR 549 • V
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FACTOR 551 • By default, FACTOR u
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FACTOR 553 DET Determinant of the c
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• The factor pattern matrix is ro
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ROTATION Subcommand FACTOR 557 ROTA
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FACTOR 559 • The ROTATION subcomm
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Example Example Example Example FAC
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FACTOR 563 Jöreskog, K. G. 1977. F
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MULTIPUNCH Column binary file. IMAG
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FILE TYPE—END FILE TYPE For mixed
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Syntax Rules FILE TYPE—END FILE T
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Example * A grouped file of student
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FILE TYPE—END FILE TYPE 573 GROUP
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FILE TYPE—END FILE TYPE 575 • T
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FILE TYPE—END FILE TYPE 577 • T
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FILE TYPE—END FILE TYPE 579 WARN
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FILE TYPE—END FILE TYPE 581 BEGIN
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Example FILTER 583 • Both system-
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Example * A command file. FINISH 58
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Syntax Rules FIT 587 • If OBS is
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FLIP FLIP [[VARIABLES=] {ALL }] {va
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FLIP 591 Example Using the untransp
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FORMATS FORMATS varlist(format) [va
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Table 1 Output data formats (Contin
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FREQUENCIES FREQUENCIES [VARIABLES=
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Example FREQUENCIES 599 • FREQUEN
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FREQUENCIES 601 • MISSING and NOM
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Example FREQUENCIES 603 FREQUENCIES
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Example FREQUENCIES VAR=AGE /STATS=
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Options GENLOG 607 mates for unsatu
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GENLOG 609 • To separate the inde
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GENLOG 611 • For each effect, GEN
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GENLOG 613 DESIGN The design matrix
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GENLOG 615 • The saved variables
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GET GET FILE=file [/KEEP={ALL** }]
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GET 619 • Variables can be specif
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GET CAPTURE GET CAPTURE {ODBC }* [/
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GET CAPTURE 623 • You can display
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Overview GET DATA 625 GET DATA read
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READNAMES Subcommand GET DATA 627 O
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QUALIFIER Subcommand GET DATA 629 T
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GET SAS Overview Options GET SAS DA
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GET SAS 633 • Value labels read f
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GET TRANSLATE GET TRANSLATE FILE=fi
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GET TRANSLATE 637 • The first row
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GET TRANSLATE 639 • For string va
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GET TRANSLATE 641 • RANGE cannot
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GLM: Overview GLM is available in t
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GLM: Overview 645 • Display expec
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Model 2: Fixed-effects ANOVA and MA
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GLM: Overview 649 For univariate an
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GLM: Univariate GLM is available in
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Basic Specification GLM: Univariate
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GLM: Univariate 655 • If you spec
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INTERCEPT Subcommand GLM: Univariat
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GLM: Univariate 659 LOF Perform a l
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GLM: Univariate 661 • A coefficie
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Example GLM: Univariate 663 GLM DEP
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Example GLM: Univariate 665 GLM DEP
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GLM: Univariate 667 • Multiple PO
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COMPARE(factor) ADJ(method) GLM: Un
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DESIGN Subcommand GLM: Univariate 6
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Overview Options GLM: Multivariate
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GLM: Multivariate 675 Residual cova
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GLM: Repeated Measures GLM is avail
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Subcommand Order • The list of de
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GLM: Repeated Measures 681 • Leve
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GLM: Repeated Measures 683 • WSFA
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GLM: Repeated Measures 685 • Thes
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GRAPH 687 The following table shows
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GRAPH 689 NGT(x) Number of cases fo
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• The default span (2) and sigma
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GRAPH 693 Figure 3 /BAR=MEAN(SALBEG
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GRAPH 695 Figure 9 /BAR(STACKED)=CO
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LINE Subcommand GRAPH 697 LINE crea
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Figure 19 /LINE=MEAN(THEFT AUTO BUR
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Figure 25 /LINE(AREA)=COUNT BY TIME
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Figure 31 LINE(DIFFERENCE)=VALUE(SA
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GRAPH 705 the variable must be dich
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ERRORBAR Subcommand GRAPH 707 ERROR
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GRAPH 709 MATRIX Scatterplot matrix
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Figure 49 /SCATTERPLOT(XYZ)=JOBCAT
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Figure 52 PARETO(CUM SIMPLE)=SUM(DE
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Elements and Attributes Dependent o
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HILOGLINEAR Overview HILOGLINEAR is
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Operations HILOGLINEAR 719 • HILO
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Example HILOGLINEAR 721 HILOGLINEAR
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Example * An Incomplete Rectangular
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HILOGLINEAR 725 NONE No plots. Spec
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HOMALS Overview Options HOMALS is a
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Example HOMALS 729 Values outside o
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HOMALS 731 The total number of vali
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Example HOMALS 733 HOMALS VARIABLES
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HOMALS 735 LEVEL String variable LE
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Basic Specification IF 737 The basi
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Example Example Example IF (AGE > 2
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Example Example IF 741 tions on eve
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{VERTICAL } {THREE } [/EFFECT={NONE
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Overview Options IGRAPH 745 The int
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CATORDER Subcommand IGRAPH 747 The
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Example IGRAPH /VIEWNAME=’Scatter
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CHARTLOOK Subcommand IGRAPH 751 CHA
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FORMAT Subcommand IGRAPH 753 For ch
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IGRAPH 755 The INTERPOLATE keyword
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IGRAPH 757 START num Indicates the
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Example IGRAPH /X1=VAR(region) TYPE
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ERRORBAR Subcommand IGRAPH 761 Erro
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IGRAPH 763 REGRESSION Fits a straig
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IGRAPH 765 Number of Cases Less Tha
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IMPORT IMPORT FILE=file [/TYPE={COM
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IMPORT 769 • DROP excludes a vari
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INCLUDE INCLUDE FILE=file Example O
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INFO This command is not available
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Types of Information The following
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INPUT PROGRAM—END INPUT PROGRAM I
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Example Example * Select cases with
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KEYED DATA LIST KEYED DATA LIST KEY
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Syntax Rules KEYED DATA LIST 783
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Example * Reading a keyed file: rea
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KM Overview KM is available in the
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KM 789 • Only one status variable
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STRATA Subcommand KM 791 STRATA ide
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TEST Subcommand KM 793 TEST specifi
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SAVE Subcommand KM 795 SAVE saves t
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Example LEAVE 797 • Numeric varia
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Operations Example Example LIST 799
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LIST 801 • If SPLIT FILE is in ef
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Temporary variables created by LOGI
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Limitations Example LOGISTIC REGRES
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LOGISTIC REGRESSION 807 DEVIATION(r
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LOGISTIC REGRESSION 809 Wald statis
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ID Subcommand LOGISTIC REGRESSION 8
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LOGISTIC REGRESSION 813 • POUT re
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LOGISTIC REGRESSION 815 • Assigne
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LOGLINEAR 817 multiway contingency
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Example Example Example Example LOG
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LOGLINEAR 821 • To enter cell cov
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CONTRAST Subcommand LOGLINEAR 823 C
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Example * Contrasts for a logistic
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Example LOGLINEAR RESPONSE(1,2) BY
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Example * Equiprobability model LOG
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Options LOOP—END LOOP 831 Missing
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LOOP—END LOOP 833 • The program
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LOOP—END LOOP 835 time, resulting
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LOOP—END LOOP 837 • The loop is
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MANOVA: Overview MANOVA is availabl
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Overview Example 2 * Analysis of Co
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MANOVA: Univariate MANOVA is availa
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MANOVA: Univariate 845 in the model
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MANOVA: Univariate 847 WITHIN Terms
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MANOVA: Univariate 849 The specifie
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MANOVA: Univariate 851 it generally
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PARAMETERS Keyword MANOVA: Univaria
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ERROR Keyword MANOVA: Univariate 85
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RESIDUALS Subcommand MANOVA: Univar
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MANOVA: Univariate 859 CELLPLOTS Ce
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Split Files and Variable Order MANO
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DESIGN Subcommand MANOVA: Univariat
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MANOVA: Univariate 865 • The numb
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MANOVA: Univariate 867 with similar
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MANOVA: Multivariate MANOVA is avai
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Limitations MANOVA: Multivariate 87
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MANOVA: Multivariate 873 DEVIATION
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MANOVA: Multivariate 875 • You mu
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MANOVA: Multivariate 877 SINGLEDF S
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MANOVA: Multivariate 879 ROTATE Rot
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CONDITIONAL and UNCONDITIONAL Keywo
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MANOVA: Repeated Measures 883 descr
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MANOVA: Repeated Measures 885 • I
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Example MANOVA: Repeated Measures 8
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MANOVA: Repeated Measures 889 • A
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1 MAPS MAPS {/GVAR = VAR(varname)[V
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Operations 893 MAPS • Each MAPS c
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895 MAPS • The total (sum) of sal
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Example 897 MAPS standard deviation
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Example 899 MAPS MAPS /GVAR = VAR(f
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Example 901 MAPS MAPS /GVAR = VAR(c
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Number of Cases Less Than (N of Cas
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906 MATCH FILES Variable Names. You
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908 MATCH FILES • If the files ha
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910 MATCH FILES RENAME Subcommand R
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912 MATCH FILES • FIRST creates a
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914 MATRIX—END MATRIX INV Inverse
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916 MATRIX—END MATRIX • A symme
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918 MATRIX—END MATRIX Example {11
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920 MATRIX—END MATRIX • All of
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922 MATRIX—END MATRIX ** &* &/ &*
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924 MATRIX—END MATRIX • The res
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926 MATRIX—END MATRIX COMPUTE Sta
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928 MATRIX—END MATRIX A = 111 111
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930 MATRIX—END MATRIX DET(M) Dete
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932 MATRIX—END MATRIX MOD(M,S) Re
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934 MATRIX—END MATRIX and the num
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936 MATRIX—END MATRIX • Constan
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938 MATRIX—END MATRIX • The fir
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940 MATRIX—END MATRIX • A logic
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942 MATRIX—END MATRIX • The mat
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944 MATRIX—END MATRIX FORMAT Spec
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946 MATRIX—END MATRIX HOLD Specif
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948 MATRIX—END MATRIX NAMES Speci
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950 MATRIX—END MATRIX • If more
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952 MATRIX—END MATRIX Valid keywo
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954 MATRIX—END MATRIX • The mat
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956 MATRIX—END MATRIX FNAMES Spec
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MATRIX DATA MATRIX DATA VARIABLES=v
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960 MATRIX DATA Table 1 summarizes
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962 MATRIX DATA Example • No othe
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964 MATRIX DATA Example * Matrix da
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966 MATRIX DATA • ROWTYPE_ is spe
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968 MATRIX DATA FULL do not enter t
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970 MATRIX DATA • The split varia
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972 MATRIX DATA Example MATRIX DATA
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974 MATRIX DATA Within-Cells Record
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976 MATRIX DATA • Because ROWTYPE
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978 MCONVERT • If there are multi
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MEANS Overview Options MEANS [TABLE
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982 MEANS • The first table list
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984 MEANS LINEARITY Test of lineari
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986 MISSING VALUES • For date for
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MIXED MIXED is available in the Adv
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990 MIXED Models The following are
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992 MIXED Basic Specification • T
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994 MIXED ARMA1 Autoregressive movi
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996 MIXED Example matrix: σ2 1 σ2
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998 MIXED Variable List The variabl
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1000 MIXED WITH (option) Covariate
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1002 MIXED • The following option
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1004 MIXED Otherwise, it will be ig
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1006 MIXED REGWGT Subcommand The RE
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1008 MIXED Example MIXED SCORE BY S
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1010 MIXED Interpretation of Random
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1012 MIXED
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1014 Syntax Reference Examples MODE
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1016 MRSETS These variables are cod
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1018 MRSETS DISPLAY Subcommand /DIS
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1020 MULT RESPONSE Options did not
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1022 MULT RESPONSE • The group na
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1024 MULT RESPONSE TABLES Subcomman
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1026 MULT RESPONSE ROW Row percenta
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1028 MULT RESPONSE The following ke
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1030 MVA Overview Options [/REGRESS
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1032 MVA Symbols The symbols displa
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1034 MVA Examples MVA VARIABLES=pop
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1036 MVA PERCENT=n Omit rows for va
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1038 MVA TPATTERN Subcommand The TP
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1040 MVA CONVERGENCE=value Converge
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1042 MVA ADDTYPE Type of distributi
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NLR NLR and CNLR are available in t
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1046 NLR Basic Specification The ba
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1048 NLR • The two COMPUTE statem
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1050 NLR Example MODEL PROGRAM A=1,
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1052 NLR • Some new parameters ma
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1054 NLR Example MODEL PROGRAM A=.5
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1056 NLR sponding to a more accurat
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1058 NLR Nonlinear Constraints Nonl
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1060 NLR • CNLR generates the boo
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1062 N OF CASES Example GET FILE=CI
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1064 NOMREG Overview Options NOMREG
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1066 NOMREG mates convergence crite
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1068 NOMREG B are factors. The expr
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1070 NOMREG • The initial model c
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1072 NOMREG • Only one OUTFILE su
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1074 NOMREG SCALE Subcommand The SC
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NONPAR CORR Overview Options NONPAR
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1078 NONPAR CORR Example NONPAR COR
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1080 NONPAR CORR Format of the Matr
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NPAR TESTS NPAR TESTS [CHISQUARE=va
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1084 NPAR TESTS Options Statistical
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1086 NPAR TESTS • If more than 0.
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1088 NPAR TESTS Operations Example
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1090 NPAR TESTS Example • A test
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1092 NPAR TESTS Operations Example
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1094 NPAR TESTS MEDIAN Subcommand S
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1096 NPAR TESTS MOSES Subcommand Sy
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1098 NPAR TESTS Operations Example
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1100 NPAR TESTS Example • Under t
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NUMERIC NUMERIC varlist[(format)] [
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OLAP CUBES OLAP CUBES {varlist} BY
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1106 OLAP CUBES • A Layered Repor
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1108 OLAP CUBES The percentage diff
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OMS Note: Square brackets used in t
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1112 OMS bles from the FREQUENCIES
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1114 OMS Example OMS /SELECT TABLES
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1116 OMS be followed by an equals s
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1118 OMS SVWSOXML XML used by Smart
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1120 OMS • The first OMS command
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1122 OMS keyword must be followed b
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1124 OMS Figure 4 Single two-dimens
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1126 OMS Figure 6 Multiple Tables w
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1128 OMS Figure 8 Tables with diffe
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1130 OMS tics in the columns. To in
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1132 OMS Figure 11 Variable names i
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- Page 1138 and 1139: 1138 OMS Table 2 Command Command Id
- Page 1140 and 1141: 1140 OMS Table 2 Command Command Id
- Page 1142 and 1143: 1142 OMS Table 2 Command Command Id
- Page 1144 and 1145: 1144 OMS Table 2 Command Command Id
- Page 1146 and 1147: 1146 OMS Table 2 Command Command Id
- Page 1148 and 1149: 1148 OMS Table 2 Command Command Id
- Page 1150 and 1151: 1150 OMS Table 2 Command Command Id
- Page 1152 and 1153: 1152 OMS Table 2 Command Command Id
- Page 1154 and 1155: OMSINFO OMSINFO. Example OMSINFO. O
- Page 1156 and 1157: 13 1156 OMSEND OMSEND Note: Square
- Page 1158 and 1159: OMSLOG OMSLOG FILE = ’filespec’
- Page 1160 and 1161: ONEWAY Overview Options ONEWAY varl
- Page 1162 and 1163: 1162 ONEWAY Analysis List The analy
- Page 1164 and 1165: 1164 ONEWAY groups. In addition, ho
- Page 1166 and 1167: 1166 ONEWAY • Up to 10 RANGE subc
- Page 1168 and 1169: 1168 ONEWAY • The dependent varia
- Page 1170 and 1171: ORTHOPLAN Overview Options ORTHOPLA
- Page 1172 and 1173: 1172 ORTHOPLAN Example • The FACT
- Page 1174 and 1175: 1174 ORTHOPLAN • MINIMUM is follo
- Page 1176 and 1177: 1176 Syntax Reference Basic Specifi
- Page 1178 and 1179: 1178 Syntax Reference SETS Subcomma
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- Page 1182 and 1183: 1182 Syntax Reference SAVE Subcomma
- Page 1186 and 1187: 1186 PACF Basic Specification The b
- Page 1188 and 1189: 1188 PACF PERIOD Subcommand PERIOD
- Page 1190 and 1191: 1190 PACF Example PACF TICKETS /LN
- Page 1192 and 1193: 1192 PARTIAL CORR Matrix Input and
- Page 1194 and 1195: 1194 PARTIAL CORR • The second PA
- Page 1196 and 1197: 1196 PARTIAL CORR MATRIX Subcommand
- Page 1198 and 1199: 1198 PARTIAL CORR Example Example E
- Page 1200 and 1201: 1200 PARTIAL CORR
- Page 1202 and 1203: 1202 PERMISSIONS
- Page 1204 and 1205: 1204 PLANCARDS Subcommand Order Ope
- Page 1206 and 1207: 1206 PLANCARDS FORMAT Subcommand FO
- Page 1208 and 1209: 1208 PLANCARDS • If the special c
- Page 1211 and 1212: PLUM Overview Options PLUM is avail
- Page 1213 and 1214: Example PLUM 1213 PLUM chist BY num
- Page 1215 and 1216: PLUM 1215 pair of parentheses must
- Page 1217 and 1218: PLUM 1217 ACPROB Estimated probabil
- Page 1219 and 1220: PLUM 1219 • Effect names and the
- Page 1221 and 1222: Example POINT 1221 an infinite loop
- Page 1223 and 1224: Example POINT 1223 FILE HANDLE DRIV
- Page 1225 and 1226: Overview Options PPLOT 1225 PPLOT (
- Page 1227 and 1228: PPLOT 1227 WEIBULL(a,b) Weibull dis
- Page 1229 and 1230: PPLOT 1229 Q-Q Quantile-quantile pl
- Page 1231 and 1232: Example PPLOT 1231 PPLOT TICKETS /D
- Page 1233 and 1234: Example PPLOT 1233 PPLOT X1 Y1 Z1 /
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PREDICT 1235 • Values on keyword
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Example Example • If variable DAY
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PRINCALS Overview Options PRINCALS
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Example PRINCALS 1241 can use COMPU
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PRINCALS 1243 NUME Numerical. This
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DEFAULT QUANT and OBJECT. ALL All a
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MATRIX Subcommand PRINCALS 1247 PRI
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PRINT PRINT [OUTFILE=file] [RECORDS
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Formats PRINT 1251 • PRINT displa
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RECORDS Subcommand PRINT 1253 RECOR
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PRINT EJECT PRINT EJECT [OUTFILE=fi
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Example PRINT EJECT 1257 DO IF MOD(
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Operations Example PRINT FORMATS 12
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PRINT SPACE PRINT SPACE [OUTFILE=fi
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PRINT SPACE 1263 • The DATA LIST
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PROBIT 1265 Natural Response Rates.
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Example * Aggregating case-by-case
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PROBIT 1269 You can request one or
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PROBIT 1271 • This example reads
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PROCEDURE OUTPUT PROCEDURE OUTPUT O
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PROXIMITIES PROXIMITIES varlist [/V
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Limitations Example PROXIMITIES 127
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PROXIMITIES 1279 RESCALE Rescale th
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PROXIMITIES 1281 PH2 Phi-square bet
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Table 1 Binary matching coefficient
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PROXIMITIES 1285 measures the propo
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PROXIMITIES 1287 BLWMN[(p[,np])] Bi
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Matrix Input PROXIMITIES 1289 • T
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Example Example Example Example PRO
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References PROXIMITIES 1293 Anderbe
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PROXSCAL PROXSCAL is available in t
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PROXSCAL 1297 Output. You can produ
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PROXSCAL 1299 sourceid Source ident
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PROXSCAL 1301 • PROXSCAL reads tw
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CONDITION Subcommand PROXSCAL 1303
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MODEL Subcommand PROXSCAL 1305 MODE
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Example PROXSCAL 1307 PROXSCAL aunt
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PROXSCAL 1309 STRESS Stress measure
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PROXSCAL 1311 CORRELATIONS Correlat
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QUICK CLUSTER Overview Options QUIC
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Example QUICK CLUSTER 1315 • The
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QUICK CLUSTER 1317 • This example
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QUICK CLUSTER 1319 • Six clusters
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Basic Specification RANK 1321 The b
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RANK 1323 NTILES(k) Percentile grou
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Example RANK 1325 RANK VARIABLES=MO
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Case Frequency RATIO STATISTICS 132
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RATIO STATISTICS 1329 PRD Price-rel
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READ MODEL Overview Options Basic S
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TYPE Subcommand TSET Subcommand REA
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Basic Specification RECODE 1335 The
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Example RECODE 1337 • Variable QV
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RECODE 1339 • If RECODE encounter
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RECORD TYPE 1341 command. REPEATING
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Example * A nested file of accident
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Example RECORD TYPE 1345 FILE TYPE
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RECORD TYPE 1347 • MISSING is not
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REFORMAT REFORMAT {ALPHA } = varlis
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REGRESSION REGRESSION [MATRIX=[IN({
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Subcommand Order The standard subco
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REGRESSION 1355 • The order of va
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REGRESSION 1357 variable can be use
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REGRESSION 1359 Excluded Variables
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REGRESSION 1361 • ORIGIN and NOOR
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REGRESSION 1363 SIG Display one-tai
- Page 1365 and 1366:
Format of the Matrix Data File Spli
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REGRESSION: Residuals REGRESSION VA
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Example DRESID Deleted residuals. A
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REGRESSION: Residuals 1371 of $CASE
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REGRESSION: Residuals 1373 • If P
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Example REGRESSION: Residuals 1375
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Options Model Type. You can specify
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GUTTMAN Guttman’s lower bounds fo
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ALL All applicable summary statisti
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RELIABILITY 1383 • A split variab
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Example RELIABILITY 1385 GET FILE=P
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Example Example Example RENAME VARI
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Options REPEATING DATA 1389 Length
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Reading Past End of Record Example
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Example * Create a data set of chil
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Example * Repeating groups in varyi
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REPEATING DATA 1397 • FILE must s
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REPEATING DATA 1399 • DATA LIST d
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REPEATING DATA 1401 • The ID subc
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Aggregate functions: Composite func
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Options Table 1 Keyword default set
- Page 1407 and 1408:
REPORT 1407 • TITLE and FOOTNOTE
- Page 1409 and 1410:
REPORT 1409 MANUAL Default settings
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REPORT 1411 CHWRAP Automatically wr
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Figure 2 Page layout for REPORT whe
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REPORT 1415 • VALUE and LABEL hav
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REPORT 1417 • More than one strin
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Column Heading The following option
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REPORT 1421 • This example create
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MEAN Mean. STDDEV Standard deviatio
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ADD(arg 1 ... arg n ) Add the argum
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REPORT 1427 • For aggregate funct
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REPORT 1429 • The specification o
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REREAD REREAD [FILE=file] [COLUMN=e
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Example REREAD 1433 • Data are ex
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REREAD 1435 • When the updated ba
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RESTORE RESTORE Overview RESTORE re
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RMV 1439 • Equations are separate
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RMV 1441 • Each median is based o
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ROC 1443 • The test result variab
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ROC 1445 DISTRIBUTION(NEGEXPO) The
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SAMPLE 1447 • If SAMPLE precedes
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SAVE 1449 Variable Map. To confirm
- Page 1451 and 1452:
VERSION Subcommand SAVE 1451 VERSIO
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SAVE 1453 • The name changes are
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SAVE 1455
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Syntax Rules Operations Limitations
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SAVE TRANSLATE This command is not
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Overview Options SAVE TRANSLATE 146
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Variable formats are translated to
- Page 1465 and 1466:
CONNECT Subcommand CONNECT identifi
- Page 1467 and 1468:
SAVE TRANSLATE 1467 • Date variab
- Page 1469 and 1470:
SAVE TRANSLATE 1469 RETAIN Retain t
- Page 1471 and 1472:
SCRIPT Overview SCRIPT ‘filename
- Page 1473 and 1474:
SEASON Overview Options Basic Speci
- Page 1475 and 1476:
VARIABLES Subcommand MODEL Subcomma
- Page 1477 and 1478:
References • The second command a
- Page 1479 and 1480:
Syntax Rules SELECT IF 1479 • Log
- Page 1481 and 1482:
Example Example Example Example Exa
- Page 1483 and 1484:
SET SET [WORKSPACE={4096**}] [MXCEL
- Page 1485 and 1486:
SET 1485 Journal Files. You can det
- Page 1487 and 1488:
SET 1487 • You can use the PRINT
- Page 1489 and 1490:
Example SET EPOCH=1900. SET 1489
- Page 1491 and 1492:
SET 1491 • MPRINT is effective on
- Page 1493 and 1494:
NO Do not compress scratch files. B
- Page 1495 and 1496:
Example SET CCA=’-,$,,’. SET 14
- Page 1497 and 1498:
SET 1497 Any variable with defined
- Page 1499 and 1500:
SHOW 1499 • MXWARNS displays the
- Page 1501 and 1502:
MXMEMORY No longer supported. SHOW
- Page 1503 and 1504:
SORT CASES SORT CASES [BY] varlist[
- Page 1505 and 1506:
SPCHART This command is available o
- Page 1507 and 1508:
Syntax Rules SPCHART 1507 • Only
- Page 1509 and 1510:
Figure 1 X-bar chart SPCHART 1509 A
- Page 1511 and 1512:
Variable Specification SPCHART 1511
- Page 1513 and 1514:
SPCHART 1513 moving range chart. Th
- Page 1515 and 1516:
Table 4 Each case is a subgroup for
- Page 1517 and 1518:
SPCHART 1517 axis. Table 6 is an ex
- Page 1519 and 1520:
The Process Performance Indices PP
- Page 1521 and 1522:
SPAN Subcommand SPCHART 1521 SPAN s
- Page 1523 and 1524:
SPCHART 1523
- Page 1525 and 1526:
Basic Specification Subcommand Orde
- Page 1527 and 1528:
Example CENTER Subcommand SPECTRA V
- Page 1529 and 1530:
BY Keyword CROSS Subcommand SPECTRA
- Page 1531 and 1532:
APPLY Subcommand P Periodogram valu
- Page 1533 and 1534:
SPLIT FILE SPLIT FILE {OFF } [{LAYE
- Page 1535 and 1536:
Example SPLIT FILE 1535 • Because
- Page 1537 and 1538:
Example STRING 1537 • Variables d
- Page 1539 and 1540:
Example SUBTITLE 1539 TITLE ’Runn
- Page 1541 and 1542:
SUMMARIZE 1541 each group. You can
- Page 1543 and 1544:
CELLS Subcommand SUMMARIZE 1543 By
- Page 1545 and 1546:
STATISTICS Subcommand SUMMARIZE 154
- Page 1547 and 1548:
Options SURVIVAL 1547 Life Tables.
- Page 1549 and 1550:
SURVIVAL 1549 groups ( A = 1 B = 1
- Page 1551 and 1552:
Example SURVIVAL 1551 SURVIVAL ONSS
- Page 1553 and 1554:
SURVIVAL 1553 can be listed on COMP
- Page 1555 and 1556:
SURVIVAL 1555 one for censored case
- Page 1557 and 1558:
Table 2 Record type 20, produced by
- Page 1559 and 1560:
SYSFILE INFO SYSFILE INFO [FILE=]
- Page 1561 and 1562:
TDISPLAY Overview Options Basic Spe
- Page 1563 and 1564:
TEMPORARY TEMPORARY Example SORT CA
- Page 1565 and 1566:
Example TEMPORARY 1565 GET FILE=HUB
- Page 1567 and 1568:
Example • TITLE is independent of
- Page 1569 and 1570:
Operations TSET 1569 • TSET takes
- Page 1571 and 1572:
TSHOW TSHOW Example TSHOW. Overview
- Page 1573 and 1574:
Options TSPLOT 1573 Modifying the V
- Page 1575 and 1576:
VARIABLES Subcommand TSPLOT 1575 VA
- Page 1577 and 1578:
FORMAT Subcommand TSPLOT 1577 FORMA
- Page 1579 and 1580:
Figure 5 FORMAT=HILO MARK Subcomman
- Page 1581 and 1582:
T-TEST Overview Options One-sample
- Page 1583 and 1584:
Example T-TEST 1583 • This indepe
- Page 1585 and 1586:
T-TEST 1585 ANALYSIS Delete cases w
- Page 1587 and 1588:
Basic Specification 2SLS 1587 The b
- Page 1589 and 1590:
CONSTANT and NOCONSTANT Subcommands
- Page 1591 and 1592:
2SLS 1591
- Page 1593 and 1594:
TWOSTEP CLUSTER 1593 the first stag
- Page 1595 and 1596:
CRITERIA Subcommand TWOSTEP CLUSTER
- Page 1597 and 1598:
NOSTANDARDIZE Subcommand TWOSTEP CL
- Page 1599 and 1600:
Examples TWOSTEP CLUSTER /CONTINUOU
- Page 1601 and 1602:
UNIANOVA UNIANOVA dependent var [BY
- Page 1603 and 1604:
UNIANOVA 1603 the keyword EXCLUDE o
- Page 1605 and 1606:
UNIANOVA 1605 • The keyword INTER
- Page 1607 and 1608:
UNIANOVA 1607 INCLUDE Include the i
- Page 1609 and 1610:
Example UNIANOVA 1609 UNIANOVA DEP
- Page 1611 and 1612:
LMATRIX Subcommand UNIANOVA 1611 Th
- Page 1613 and 1614:
CONTRAST Subcommand UNIANOVA 1613 C
- Page 1615 and 1616:
POSTHOC Subcommand UNIANOVA 1615 PO
- Page 1617 and 1618:
UNIANOVA 1617 • Multiple POSTHOC
- Page 1619 and 1620:
UNIANOVA 1619 COMPARE ADJ(method) P
- Page 1621 and 1622:
UNIANOVA 1621 • To include the in
- Page 1623 and 1624:
UPDATE 1623 Variable Flag. You can
- Page 1625 and 1626:
UPDATE 1625 • BY specifies the ke
- Page 1627 and 1628:
Example UPDATE 1627 UPDATE FILE=MAS
- Page 1629 and 1630:
USE USE [{start date }] [THRU [{end
- Page 1631 and 1632:
USE 1631 • This command selects o
- Page 1633 and 1634:
VALUE LABELS Overview VALUE LABELS
- Page 1635 and 1636:
Example VALUE LABELS 1635 • Label
- Page 1637 and 1638:
VARCOMP 1637 Tuning the Algorithm.
- Page 1639 and 1640:
VARCOMP 1639 INCLUDE Include the in
- Page 1641 and 1642:
VARCOMP 1641 CORB Correlation matri
- Page 1643 and 1644:
VARIABLE ALIGNMENT VARIABLE ALIGNME
- Page 1645 and 1646:
Operations Example Example Example
- Page 1647 and 1648:
VARIABLE WIDTH VARIABLE WIDTH varli
- Page 1649 and 1650:
Basic Specification VARSTOCASES 164
- Page 1651 and 1652:
ID Subcommand VARSTOCASES 1651 The
- Page 1653 and 1654:
VARSTOCASES 1653 • The basic spec
- Page 1655 and 1656:
VECTOR VECTOR {vector name=varlist
- Page 1657 and 1658:
VECTOR 1657 • The first COMPUTE c
- Page 1659 and 1660:
VECTOR 1659 • In this example, th
- Page 1661 and 1662:
VERIFY VERIFY [VARIABLES=series nam
- Page 1663 and 1664:
WEIGHT WEIGHT {BY varname} {OFF } E
- Page 1665 and 1666:
WLS Overview Options WLS is availab
- Page 1667 and 1668:
WLS 1667 • WGT#1 is not created w
- Page 1669 and 1670:
Example WLS 1669 WLS SHARES WITH PR
- Page 1671 and 1672:
WRITE WRITE [OUTFILE=file] [RECORDS
- Page 1673 and 1674:
Example WRITE 1673 WRITE OUTFILE=PR
- Page 1675 and 1676:
WRITE 1675 • WRITE writes the val
- Page 1677 and 1678:
Operations Example WRITE FORMATS 16
- Page 1679 and 1680:
XSAVE XSAVE OUTFILE=’filespec’
- Page 1681 and 1682:
Limitations Example • Maximum 10
- Page 1683 and 1684:
XSAVE 1683 • RENAME does not affe
- Page 1686 and 1687:
1686 XSAVE
- Page 1688 and 1689:
1688 Appendix A A session must go t
- Page 1690 and 1691:
1690 Appendix A Table A.1 Commands
- Page 1692 and 1693:
1692 Appendix A Table A.1 Commands
- Page 1694 and 1695:
1694 Appendix A Table A.2 Taxonomy
- Page 1696 and 1697:
1696 Appendix B Position Graphic Ma
- Page 1698 and 1699:
1698 Appendix B Position Graphic Ma
- Page 1700 and 1701:
1700 Appendix B Position Graphic Ma
- Page 1703 and 1704:
Appendix C Defining Complex Files M
- Page 1705 and 1706:
Figure C.3 File NESTED.DAT Y 1988 R
- Page 1707 and 1708:
Grouped Data Defining Complex Files
- Page 1709 and 1710:
• END FILE TYPE signals the end o
- Page 1711 and 1712:
Defining Complex Files 1711 tion, t
- Page 1713 and 1714:
Figure C.9 LIST output for reading
- Page 1715 and 1716:
Defining Complex Files 1715 • DAT
- Page 1717 and 1718:
Appendix D Using the Macro Facility
- Page 1719 and 1720:
Using the Macro Facility 1719 • T
- Page 1721 and 1722:
Using the Macro Facility 1721 • I
- Page 1723 and 1724:
Using the Macro Facility 1723 • I
- Page 1725 and 1726:
Using the Macro Facility 1725 • C
- Page 1727 and 1728:
Figure D.14 !CORRTST macro with lis
- Page 1729 and 1730:
Figure D.17 Descriptive statistics
- Page 1731:
Using the Macro Facility 1731 Figur
- Page 1734 and 1735:
1734 Appendix A Missing Values Sinc
- Page 1736 and 1737:
1736 Appendix A are specified on an
- Page 1738 and 1739:
1738 Appendix A Models The models s
- Page 1740 and 1741:
1740 Subject Index arctangent funct
- Page 1742 and 1743:
1742 Subject Index sampling, 1446 s
- Page 1744 and 1745:
1744 Subject Index target variable,
- Page 1746 and 1747:
1746 Subject Index in Spectral Plot
- Page 1748 and 1749:
1748 Subject Index dichotomies, 102
- Page 1750 and 1751:
1750 Subject Index drop-line charts
- Page 1752 and 1753:
1752 Subject Index Fisher’s class
- Page 1754 and 1755:
1754 Subject Index GLM Univariate,
- Page 1756 and 1757:
1756 Subject Index in Multidimensio
- Page 1758 and 1759:
1758 Subject Index kurtosis in Desc
- Page 1760 and 1761:
1760 Subject Index expected frequen
- Page 1762 and 1763:
1762 Subject Index in Autoregressio
- Page 1764 and 1765:
1764 Subject Index analysis of vari
- Page 1766 and 1767:
1766 Subject Index one-sample t tes
- Page 1768 and 1769:
1768 Subject Index in loglinear ana
- Page 1770 and 1771:
1770 Subject Index r in Means proce
- Page 1772 and 1773:
1772 Subject Index in Multidimensio
- Page 1774 and 1775:
1774 Subject Index smoothing functi
- Page 1776 and 1777:
1776 Subject Index sum of squares T
- Page 1778 and 1779:
1778 Subject Index 1164, 1616, 1617
- Page 1780 and 1781:
1780 Subject Index including consta
- Page 1782 and 1783:
1782 Syntax Index $COUNT (keyword)
- Page 1784 and 1785:
1784 Syntax Index PRINT subcommand,
- Page 1786 and 1787:
1786 Syntax Index with OVERALS comm
- Page 1788 and 1789:
1788 Syntax Index BTAU (keyword) CR
- Page 1790 and 1791:
1790 Syntax Index CCW (keyword) IGR
- Page 1792 and 1793:
1792 Syntax Index nonlinear constra
- Page 1794 and 1795:
1794 Syntax Index CONVERGENCE (subc
- Page 1796 and 1797:
1796 Syntax Index CPL (keyword) SPC
- Page 1798 and 1799:
1798 Syntax Index MRSETS subcommand
- Page 1800 and 1801:
1800 Syntax Index DEFFSQRT (keyword
- Page 1802 and 1803:
1802 Syntax Index DIFFERENCE (keywo
- Page 1804 and 1805:
1804 Syntax Index DROP (subcommand)
- Page 1806 and 1807:
1806 Syntax Index ERRORS (subcomman
- Page 1808 and 1809:
1808 Syntax Index ORTHOPLAN command
- Page 1810 and 1811:
1810 Syntax Index FORMATS (subcomma
- Page 1812 and 1813:
1812 Syntax Index GET TRANSLATE (co
- Page 1814 and 1815:
1814 Syntax Index GSCH (function) M
- Page 1816 and 1817:
1816 Syntax Index IDENT (function)
- Page 1818 and 1819:
1818 Syntax Index INITTHRESHOLD (ke
- Page 1820 and 1821:
1820 Syntax Index PLOT subcommand,
- Page 1822 and 1823:
1822 Syntax Index CSTABULATE comman
- Page 1824 and 1825:
1824 Syntax Index MACROS (keyword)
- Page 1826 and 1827:
1826 Syntax Index scientific notati
- Page 1828 and 1829:
1828 Syntax Index SHOW command, 150
- Page 1830 and 1831:
1830 Syntax Index MODEIMPU (keyword
- Page 1832 and 1833:
1832 Syntax Index SHOW command, 150
- Page 1834 and 1835:
1834 Syntax Index MFI keyword, 1073
- Page 1836 and 1837:
1836 Syntax Index MH subcommand, 10
- Page 1838 and 1839:
1838 Syntax Index UNIANOVA command,
- Page 1840 and 1841:
1840 Syntax Index T-TEST command, 1
- Page 1842 and 1843:
1842 Syntax Index PLANCARDS (comman
- Page 1844 and 1845:
1844 Syntax Index PPS_MURTHY (keywo
- Page 1846 and 1847:
1846 Syntax Index PROFILES (keyword
- Page 1848 and 1849:
1848 Syntax Index RATE (subcommand)
- Page 1850 and 1851:
1850 Syntax Index MATCH FILES comma
- Page 1852 and 1853:
1852 Syntax Index ROTATE (keyword)
- Page 1854 and 1855:
1854 Syntax Index RELIABILITY comma
- Page 1856 and 1857:
1856 Syntax Index MNEST subcommand,
- Page 1858 and 1859:
1858 Syntax Index PLUM command, 121
- Page 1860 and 1861:
1860 Syntax Index SQ (subcommand) A
- Page 1862 and 1863:
1862 Syntax Index MEANS command, 98
- Page 1864 and 1865:
1864 Syntax Index with SPLIT FILE c
- Page 1866 and 1867:
1866 Syntax Index SPLIT subcommand,
- Page 1868 and 1869:
1868 Syntax Index ZRESID keyword, 1
- Page 1870 and 1871:
1870 Syntax Index LOGISTIC REGRESSI
- Page 1872 and 1873:
1872 Syntax Index WITH (keyword) AN
- Page 1874:
1874 Syntax Index
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