SPSS® 12.0 Command Syntax Reference

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990 MIXED Models The following are examples of models that can be specified using MIXED: Model 1: Fixed-Effects ANOVA Model Suppose that TREAT is the treatment factor and BLOCK is the blocking factor. MIXED Y BY TREAT BLOCK /FIXED = TREAT BLOCK. Model 2: Randomized Complete Blocks Design Suppose that TREAT is the treatment factor and BLOCK is the blocking factor. MIXED Y BY TREAT BLOCK /FIXED = TREAT /RANDOM = BLOCK. Model 3: Split-Plot Design An experiment consists of two factors, A and B. The experiment unit with respect to A is C. The experiment unit with respect to B is the individual subject, a subdivision of the factor C. Thus, C is the whole-plot unit, and the individual subject is the split-plot unit. MIXED Y BY A B C /FIXED = A B A*B /RANDOM = C(A). Model 4: Purely Random-Effects Model Suppose that A, B, and C are random factors. MIXED Y BY A B C /FIXED = | NOINT /RANDOM = INTERCEPT A B C A*B A*C B*C | COVTYPE(CS). The MIXED procedure allows effects specified on the same RANDOM subcommand to be correlated. Thus, in the model above, the parameters of a compound symmetry covariance matrix are computed across all levels of the random effects. In order to specify independent random effects, you need to specify separate RANDOM subcommands. For example: MIXED Y BY A B C /FIXED = | NOINT /RANDOM = INTERCEPT A | COVTYPE(CS) /RANDOM = INTERCEPT B | COVTYPE(CS) /RANDOM = INTERCEPT C | COVTYPE(CS) /RANDOM = INTERCEPT A*B | COVTYPE(CS) /RANDOM = INTERCEPT A*C | COVTYPE(CS) /RANDOM = INTERCEPT B*C | COVTYPE(CS). Here, the parameters of compound symmetry matrices are computed separately for each random effect.
MIXED 991 Model 5: Random Coefficient Model Suppose that the dependent variable Y is regressed on the independent variable X for each level of A. MIXED Y BY A WITH X /FIXED = X /RANDOM = INTERCEPT X | SUBJECT(A) COVTYPE(ID). Model 6: Multilevel Analysis Suppose that SCORE is the score of a particular achievement test given over TIME. STUDENT is nested within CLASS, and CLASS is nested within SCHOOL. MIXED SCORE WITH TIME /FIXED = TIME /RANDOM = INTERCEPT TIME | SUBJECT(SCHOOL) COVTYPE(ID) /RANDOM = INTERCEPT TIME | SUBJECT(SCHOOL*CLASS) COVTYPE(ID) /RANDOM = INTERCEPT TIME | SUBJECT(SCHOOL*CLASS*STUDENT) COVTYPE(ID). Model 7: Unconditional Linear Growth Model Suppose that SUBJ is the individual’s identification and Y is the response of an individual observed over TIME. The covariance structure is unspecified. MIXED Y WITH TIME /FIXED = TIME /RANDOM = INTERCEPT TIME | SUBJECT(SUBJ) COVTYPE(ID). Model 8: Linear Growth Model with a Person-Level Covariate Suppose that PCOVAR is the person-level covariate. MIXED Y WITH TIME PCOVAR /FIXED = TIME PCOVAR TIME*PCOVAR /RANDOM = INTERCEPT TIME | SUBJECT(SUBJ) COVTYPE(ID). Model 9: Repeated Measures Analysis Suppose that SUBJ is the individual’s identification and Y is the response of an individual observed over several STAGEs. The covariance structure is compound symmetry. MIXED Y BY STAGE /RANDOM = INTERCEPT | SUBJECT(SUBJ) COVTYPE(ID) /REPEATED = STAGE | SUBJECT(SUBJ) COVTYPE(CS). Model 10: Repeated Measures Analysis with Time-Dependent Covariate Suppose that SUBJ is the individual’s identification and Y is the response of an individual observed over several STAGEs. X is an individual-level covariate that also measures over several STAGEs. The residual covariance matrix structure is AR(1). MIXED Y BY STAGE WITH X /FIXED = X /RANDOM = INTERCEPT X | SUBJECT(SUBJ) COVTYPE(ID) /REPEATED = STAGE | SUBJECT(SUBJ) COVTYPE(AR1).
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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
Page 779 and 780:
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
Page 785 and 786:
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
Page 807 and 808:
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
Page 821 and 822:
LOGLINEAR 821 • To enter cell cov
Page 823 and 824:
CONTRAST Subcommand LOGLINEAR 823 C
Page 825 and 826:
Example * Contrasts for a logistic
Page 827 and 828:
Example LOGLINEAR RESPONSE(1,2) BY
Page 829 and 830:
Example * Equiprobability model LOG
Page 831 and 832:
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
Page 845 and 846:
MANOVA: Univariate 845 in the model
Page 847 and 848:
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
Page 903:
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
Page 918 and 919:
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
Page 940 and 941: 940 MATRIX—END MATRIX • A logic
Page 942 and 943: 942 MATRIX—END MATRIX • The mat
Page 944 and 945: 944 MATRIX—END MATRIX FORMAT Spec
Page 946 and 947: 946 MATRIX—END MATRIX HOLD Specif
Page 948 and 949: 948 MATRIX—END MATRIX NAMES Speci
Page 950 and 951: 950 MATRIX—END MATRIX • If more
Page 952 and 953: 952 MATRIX—END MATRIX Valid keywo
Page 954 and 955: 954 MATRIX—END MATRIX • The mat
Page 956 and 957: 956 MATRIX—END MATRIX FNAMES Spec
Page 958 and 959: MATRIX DATA MATRIX DATA VARIABLES=v
Page 960 and 961: 960 MATRIX DATA Table 1 summarizes
Page 962 and 963: 962 MATRIX DATA Example • No othe
Page 964 and 965: 964 MATRIX DATA Example * Matrix da
Page 966 and 967: 966 MATRIX DATA • ROWTYPE_ is spe
Page 968 and 969: 968 MATRIX DATA FULL do not enter t
Page 970 and 971: 970 MATRIX DATA • The split varia
Page 972 and 973: 972 MATRIX DATA Example MATRIX DATA
Page 974 and 975: 974 MATRIX DATA Within-Cells Record
Page 976 and 977: 976 MATRIX DATA • Because ROWTYPE
Page 978 and 979: 978 MCONVERT • If there are multi
Page 980 and 981: MEANS Overview Options MEANS [TABLE
Page 982 and 983: 982 MEANS • The first table list
Page 984 and 985: 984 MEANS LINEARITY Test of lineari
Page 986 and 987: 986 MISSING VALUES • For date for
Page 988 and 989: MIXED MIXED is available in the Adv
Page 992 and 993: 992 MIXED Basic Specification • T
Page 994 and 995: 994 MIXED ARMA1 Autoregressive movi
Page 996 and 997: 996 MIXED Example matrix: σ2 1 σ2
Page 998 and 999: 998 MIXED Variable List The variabl
Page 1000 and 1001: 1000 MIXED WITH (option) Covariate
Page 1002 and 1003: 1002 MIXED • The following option
Page 1004 and 1005: 1004 MIXED Otherwise, it will be ig
Page 1006 and 1007: 1006 MIXED REGWGT Subcommand The RE
Page 1008 and 1009: 1008 MIXED Example MIXED SCORE BY S
Page 1010 and 1011: 1010 MIXED Interpretation of Random
Page 1012 and 1013: 1012 MIXED
Page 1014 and 1015: 1014 Syntax Reference Examples MODE
Page 1016 and 1017: 1016 MRSETS These variables are cod
Page 1018 and 1019: 1018 MRSETS DISPLAY Subcommand /DIS
Page 1020 and 1021: 1020 MULT RESPONSE Options did not
Page 1022 and 1023: 1022 MULT RESPONSE • The group na
Page 1024 and 1025: 1024 MULT RESPONSE TABLES Subcomman
Page 1026 and 1027: 1026 MULT RESPONSE ROW Row percenta
Page 1028 and 1029: 1028 MULT RESPONSE The following ke
Page 1030 and 1031: 1030 MVA Overview Options [/REGRESS
Page 1032 and 1033: 1032 MVA Symbols The symbols displa
Page 1034 and 1035: 1034 MVA Examples MVA VARIABLES=pop
Page 1036 and 1037: 1036 MVA PERCENT=n Omit rows for va
Page 1038 and 1039: 1038 MVA TPATTERN Subcommand The TP
Page 1040 and 1041:
1040 MVA CONVERGENCE=value Converge
Page 1042 and 1043:
1042 MVA ADDTYPE Type of distributi
Page 1044 and 1045:
NLR NLR and CNLR are available in t
Page 1046 and 1047:
1046 NLR Basic Specification The ba
Page 1048 and 1049:
1048 NLR • The two COMPUTE statem
Page 1050 and 1051:
1050 NLR Example MODEL PROGRAM A=1,
Page 1052 and 1053:
1052 NLR • Some new parameters ma
Page 1054 and 1055:
1054 NLR Example MODEL PROGRAM A=.5
Page 1056 and 1057:
1056 NLR sponding to a more accurat
Page 1058 and 1059:
1058 NLR Nonlinear Constraints Nonl
Page 1060 and 1061:
1060 NLR • CNLR generates the boo
Page 1062 and 1063:
1062 N OF CASES Example GET FILE=CI
Page 1064 and 1065:
1064 NOMREG Overview Options NOMREG
Page 1066 and 1067:
1066 NOMREG mates convergence crite
Page 1068 and 1069:
1068 NOMREG B are factors. The expr
Page 1070 and 1071:
1070 NOMREG • The initial model c
Page 1072 and 1073:
1072 NOMREG • Only one OUTFILE su
Page 1074 and 1075:
1074 NOMREG SCALE Subcommand The SC
Page 1076 and 1077:
NONPAR CORR Overview Options NONPAR
Page 1078 and 1079:
1078 NONPAR CORR Example NONPAR COR
Page 1080 and 1081:
1080 NONPAR CORR Format of the Matr
Page 1082 and 1083:
NPAR TESTS NPAR TESTS [CHISQUARE=va
Page 1084 and 1085:
1084 NPAR TESTS Options Statistical
Page 1086 and 1087:
1086 NPAR TESTS • If more than 0.
Page 1088 and 1089:
1088 NPAR TESTS Operations Example
Page 1090 and 1091:
1090 NPAR TESTS Example • A test
Page 1092 and 1093:
Page 1094 and 1095:
1094 NPAR TESTS MEDIAN Subcommand S
Page 1096 and 1097:
1096 NPAR TESTS MOSES Subcommand Sy
Page 1098 and 1099:
Page 1100 and 1101:
1100 NPAR TESTS Example • Under t
Page 1102 and 1103:
NUMERIC NUMERIC varlist[(format)] [
Page 1104 and 1105:
OLAP CUBES OLAP CUBES {varlist} BY
Page 1106 and 1107:
1106 OLAP CUBES • A Layered Repor
Page 1108 and 1109:
1108 OLAP CUBES The percentage diff
Page 1110 and 1111:
OMS Note: Square brackets used in t
Page 1112 and 1113:
1112 OMS bles from the FREQUENCIES
Page 1114 and 1115:
1114 OMS Example OMS /SELECT TABLES
Page 1116 and 1117:
1116 OMS be followed by an equals s
Page 1118 and 1119:
1118 OMS SVWSOXML XML used by Smart
Page 1120 and 1121:
1120 OMS • The first OMS command
Page 1122 and 1123:
1122 OMS keyword must be followed b
Page 1124 and 1125:
1124 OMS Figure 4 Single two-dimens
Page 1126 and 1127:
1126 OMS Figure 6 Multiple Tables w
Page 1128 and 1129:
1128 OMS Figure 8 Tables with diffe
Page 1130 and 1131:
1130 OMS tics in the columns. To in
Page 1132 and 1133:
1132 OMS Figure 11 Variable names i
Page 1134 and 1135:
1134 OMS Figure 13 OXML for simple
Page 1136 and 1137:
1136 OMS Command and Subtype Identi
Page 1138 and 1139:
1138 OMS Table 2 Command Command Id
Page 1140 and 1141:
Page 1142 and 1143:
Page 1144 and 1145:
Page 1146 and 1147:
Page 1148 and 1149:
Page 1150 and 1151:
Page 1152 and 1153:
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
Page 1180 and 1181:
1180 Syntax Reference CONVERGENCE S
Page 1182 and 1183:
1182 Syntax Reference SAVE Subcomma
Page 1185 and 1186:
PACF Overview Options PACF [VARIABL
Page 1187 and 1188:
PACF 1187 • DIFF differences the
Page 1189 and 1190:
PACF 1189 • If SEASONAL is specif
Page 1191 and 1192:
PARTIAL CORR Overview Options PARTI
Page 1193 and 1194:
VARIABLES Subcommand PARTIAL CORR 1
Page 1195 and 1196:
FORMAT Subcommand FORMAT determines
Page 1197 and 1198:
Format of the Matrix Data File Spli
Page 1199 and 1200:
PARTIAL CORR 1199 • REGRESSION co
Page 1201 and 1202:
PERMISSIONS PERMISSIONS FILE=’fil
Page 1203 and 1204:
PLANCARDS Overview Options PLANCARD
Page 1205 and 1206:
Example PLANCARDS 1205 DATA LIST FR
Page 1207 and 1208:
Figure 2 Single-profile format Prof
Page 1209:
Profile # 1 Circle the number in th
Page 1212 and 1213:
1212 PLUM Basic Specification The b
Page 1214 and 1215:
1214 PLUM value. The criterion is n
Page 1216 and 1217:
1216 PLUM CELLINFO Cell Information
Page 1218 and 1219:
1218 PLUM • Covariates can be con
Page 1220 and 1221:
POINT POINT KEY=varname [FILE=file]
Page 1222 and 1223:
1222 POINT Example • DATA LIST re
Page 1224 and 1225:
PPLOT PPLOT [VARIABLES=] varlist [/
Page 1226 and 1227:
1226 PPLOT Operations • Subcomman
Page 1228 and 1229:
1228 PPLOT FRACTION Subcommand FRAC
Page 1230 and 1231:
1230 PPLOT • In low resolution, a
Page 1232 and 1233:
1232 PPLOT • If a natural log tra
Page 1234 and 1235:
PREDICT PREDICT [{start date }] [TH
Page 1236 and 1237:
1236 PREDICT • If there is a gap
Page 1238 and 1239:
PRESERVE PRESERVE Overview PRESERVE
Page 1240 and 1241:
1240 Syntax Reference Basic Specifi
Page 1242 and 1243:
1242 Syntax Reference Example DATA
Page 1244 and 1245:
1244 Syntax Reference CONVERGENCE S
Page 1246 and 1247:
Page 1248 and 1249:
1248 Syntax Reference VARNAME_ Stri
Page 1250 and 1251:
1250 PRINT Syntax Rules • A slash
Page 1252 and 1253:
1252 PRINT Strings You can specify
Page 1254 and 1255:
1254 PRINT Example PRINT OUTFILE=PR
Page 1256 and 1257:
1256 PRINT EJECT Basic Specificatio
Page 1258 and 1259:
PRINT FORMATS PRINT FORMATS varlist
Page 1260 and 1261:
1260 PRINT FORMATS Example COMPUTE
Page 1262 and 1263:
1262 PRINT SPACE Example PRINT / NA
Page 1264 and 1265:
PROBIT Overview Options PROBIT is a
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1266 PROBIT • If individual cases
Page 1268 and 1269:
1268 PROBIT • Keywords BY and WIT
Page 1270 and 1271:
1270 PROBIT mately six significant
Page 1272 and 1273:
1272 PROBIT RMP Relative median pot
Page 1274 and 1275:
1274 PROCEDURE OUTPUT Example PROCE
Page 1276 and 1277:
1276 PROXIMITIES Example Overview O
Page 1278 and 1279:
1278 PROXIMITIES RANGE Standardize
Page 1280 and 1281:
1280 PROXIMITIES CORRELATION( xy ,
Page 1282 and 1283:
1282 PROXIMITIES 0, 1, 1, 0, 0 for
Page 1284 and 1285:
1284 PROXIMITIES K1[(p[,np])] Kulcz
Page 1286 and 1287:
1286 PROXIMITIES SS5[(p[,np])] Soka
Page 1288 and 1289:
1288 PROXIMITIES • When used with
Page 1290 and 1291:
1290 PROXIMITIES analysis. If a var
Page 1292 and 1293:
1292 PROXIMITIES Example Example GE
Page 1294 and 1295:
1294 PROXIMITIES
Page 1296 and 1297:
1296 Syntax Reference Overview Opti
Page 1298 and 1299:
Page 1300 and 1301:
Page 1302 and 1303:
1302 Syntax Reference TORGERSON Tor
Page 1304 and 1305:
1304 Syntax Reference SPLINE Monoto
Page 1306 and 1307:
1306 Syntax Reference number of cas
Page 1308 and 1309:
1308 Syntax Reference DIFFSTRESS Co
Page 1310 and 1311:
1310 Syntax Reference PLOT Subcomma
Page 1312 and 1313:
1312 Syntax Reference cases in the
Page 1314 and 1315:
1314 QUICK CLUSTER distances betwee
Page 1316 and 1317:
1316 QUICK CLUSTER is specified, QU
Page 1318 and 1319:
1318 QUICK CLUSTER NONE No addition
Page 1320 and 1321:
RANK RANK [VARIABLES=] varlist [({A
Page 1322 and 1323:
1322 RANK • String variables cann
Page 1324 and 1325:
1324 RANK TIES Subcommand TIES dete
Page 1326 and 1327:
RATIO STATISTICS RATIO STATISTICS n
Page 1328 and 1329:
1328 RATIO STATISTICS • Keywords
Page 1330 and 1331:
1330 RATIO STATISTICS MEAN Mean. Th
Page 1332 and 1333:
1332 Syntax Reference Syntax Rules
Page 1334 and 1335:
RECODE For numeric variables: RECOD
Page 1336 and 1337:
1336 RECODE • SYSMIS specifies th
Page 1338 and 1339:
1338 RECODE • Values for V1 throu
Page 1340 and 1341:
RECORD TYPE For mixed file types: R
Page 1342 and 1343:
1342 RECORD TYPE Example * Reading
Page 1344 and 1345:
1344 RECORD TYPE Example * A mixed
Page 1346 and 1347:
1346 RECORD TYPE Example * Specifyi
Page 1348 and 1349:
1348 RECORD TYPE • SPREAD can be
Page 1350 and 1351:
1350 REFORMAT Example * Convert an
Page 1352 and 1353:
1352 REGRESSION Overview Options RE
Page 1354 and 1355:
1354 REGRESSION • The DEPENDENT s
Page 1356 and 1357:
1356 REGRESSION • When more than
Page 1358 and 1359:
1358 REGRESSION Equation Statistics
Page 1360 and 1361:
1360 REGRESSION PIN[(value)] Probab
Page 1362 and 1363:
1362 REGRESSION • COMPUTE creates
Page 1364 and 1365:
1364 REGRESSION • If SELECT is sp
Page 1366 and 1367:
1366 REGRESSION MISSING Subcommand
Page 1368 and 1369:
1368 REGRESSION: Residuals (RESIDUA
Page 1370 and 1371:
1370 REGRESSION: Residuals • REGR
Page 1372 and 1373:
1372 REGRESSION: Residuals are RESI
Page 1374 and 1375:
1374 REGRESSION: Residuals Example
Page 1376 and 1377:
RELIABILITY Overview RELIABILITY VA
Page 1378 and 1379:
1378 RELIABILITY • This example a
Page 1380 and 1381:
1380 RELIABILITY ICC Subcommand ICC
Page 1382 and 1383:
1382 RELIABILITY Matrix Output Matr
Page 1384 and 1385:
1384 RELIABILITY Example Example Ex
Page 1386 and 1387:
RENAME VARIABLES RENAME VARIABLES {
Page 1388 and 1389:
REPEATING DATA REPEATING DATA [FILE
Page 1390 and 1391:
1390 REPEATING DATA • The DATA LI
Page 1392 and 1393:
1392 REPEATING DATA Example Figure
Page 1394 and 1395:
1394 REPEATING DATA STARTS Subcomma
Page 1396 and 1397:
1396 REPEATING DATA • In the data
Page 1398 and 1399:
1398 REPEATING DATA CONTINUED Subco
Page 1400 and 1401:
1400 REPEATING DATA in positions 1-
Page 1402 and 1403:
REPORT REPORT [/FORMAT=[{MANUAL }]
Page 1404 and 1405:
1404 REPORT Column Widths. Default
Page 1406 and 1407:
1406 REPORT statistics. The maximum
Page 1408 and 1409:
1408 REPORT Example • The maximum
Page 1410 and 1411:
1410 REPORT headings with the first
Page 1412 and 1413:
1412 REPORT Figure 1 Page layout fo
Page 1414 and 1415:
1414 REPORT Example REPORT FORMAT=A
Page 1416 and 1417:
1416 REPORT Column Format The follo
Page 1418 and 1419:
1418 REPORT BREAK Subcommand BREAK
Page 1420 and 1421:
1420 REPORT (OFFSET) Position of th
Page 1422 and 1423:
1422 REPORT • To use the summary
Page 1424 and 1425:
1424 REPORT means of all three vari
Page 1426 and 1427:
1426 REPORT • The summary title m
Page 1428 and 1429:
1428 REPORT Table 3 Default print f
Page 1430 and 1431:
1430 REPORT • The right-justified
Page 1432 and 1433:
1432 REREAD Subcommand Order Subcom
Page 1434 and 1435:
1434 REREAD FILE Subcommand FILE sp
Page 1436 and 1437:
1436 REREAD Example * Reading both
Page 1438 and 1439:
RMV RMV new variables={LINT (varlis
Page 1440 and 1441:
1440 RMV • NEWVAR1 will have the
Page 1442 and 1443:
ROC Overview Options ROC varlist BY
Page 1444 and 1445:
1444 ROC MISSING Subcommand Cases w
Page 1446 and 1447:
SAMPLE SAMPLE {decimal value} {n FR
Page 1448 and 1449:
SAVE SAVE OUTFILE=’filespec’ [/
Page 1450 and 1451:
1450 SAVE Example GET FILE=HUBEMPL.
Page 1452 and 1453:
1452 SAVE Example GET FILE=PRSNL. C
Page 1454 and 1455:
1454 SAVE PERMISSIONS Subcommand Th
Page 1456 and 1457:
1456 Syntax Reference SAVE MODEL Ov
Page 1458 and 1459:
1458 Syntax Reference TYPE Subcomma
Page 1460 and 1461:
1460 SAVE TRANSLATE ** Required for
Page 1462 and 1463:
1462 SAVE TRANSLATE • User-missin
Page 1464 and 1465:
1464 SAVE TRANSLATE The following t
Page 1466 and 1467:
1466 SAVE TRANSLATE WK1 1-2-3 Relea
Page 1468 and 1469:
1468 SAVE TRANSLATE CELLS Subcomman
Page 1470 and 1471:
1470 SAVE TRANSLATE Example SAVE TR
Page 1472 and 1473:
1472 SCRIPT
Page 1474 and 1475:
1474 Syntax Reference Subcommand Or
Page 1476 and 1477:
1476 Syntax Reference PERIOD Subcom
Page 1478 and 1479:
SELECT IF SELECT IF [(]logical expr
Page 1480 and 1481:
1480 SELECT IF Missing Values • I
Page 1482 and 1483:
1482 SELECT IF Example Example Exam
Page 1484 and 1485:
1484 SET [HEADER={NO** }] {YES } {B
Page 1486 and 1487:
1486 SET Operations Example • Set
Page 1488 and 1489:
1488 SET LABELS Displays variable l
Page 1490 and 1491:
1490 SET JOURNAL Subcommand Alias t
Page 1492 and 1493:
1492 SET SPSSB in the server versio
Page 1494 and 1495:
1494 SET • You can specify any le
Page 1496 and 1497:
1496 SET Example SET SMALL = 0. SET
Page 1498 and 1499:
SHOW SHOW [ALL] [BLANKS] [BLKSIZE]
Page 1500 and 1501:
1500 SHOW EPOCH Range of years for
Page 1502 and 1503:
1502 SHOW WEIGHT Variable used to w
Page 1504 and 1505:
1504 SORT CASES addition, special c
Page 1506 and 1507:
1506 SPCHART Overview Options SPCHA
Page 1508 and 1509:
1508 SPCHART • The default span (
Page 1510 and 1511:
1510 SPCHART Figure 3 S chart Data
Page 1512 and 1513:
1512 SPCHART Figure 4 Individuals c
Page 1514 and 1515:
1514 SPCHART Figure 7 NP chart Data
Page 1516 and 1517:
1516 SPCHART based on the Poisson d
Page 1518 and 1519:
1518 SPCHART • A duplicated subco
Page 1520 and 1521:
1520 SPCHART CAPSIGMA Subcommand Th
Page 1522 and 1523:
1522 SPCHART fixed control limits a
Page 1524 and 1525:
1524 Syntax Reference SPECTRA Overv
Page 1526 and 1527:
1526 Syntax Reference Syntax Rules
Page 1528 and 1529:
1528 Syntax Reference TUKEY Tukey-H
Page 1530 and 1531:
Page 1532 and 1533:
1532 Syntax Reference References
Page 1534 and 1535:
1534 SPLIT FILE • AGGREGATE ignor
Page 1536 and 1537:
STRING STRING varlist (An) [/varlis
Page 1538 and 1539:
SUBTITLE SUBTITLE [’]text[’] Ex
Page 1540 and 1541:
SUMMARIZE SUMMARIZE [TABLES=]{varli
Page 1542 and 1543:
1542 SUMMARIZE Example the FORMAT s
Page 1544 and 1545:
1544 SUMMARIZE GEOMETRIC Geometric
Page 1546 and 1547:
SURVIVAL Overview SURVIVAL is avail
Page 1548 and 1549:
1548 SURVIVAL Operations • SURVIV
Page 1550 and 1551:
1550 SURVIVAL • INTERVALS produce
Page 1552 and 1553:
1552 SURVIVAL HAZARD Plot the hazar
Page 1554 and 1555:
1554 SURVIVAL large samples. It is
Page 1556 and 1557:
1556 SURVIVAL WRITE Subcommand Form
Page 1558 and 1559:
1558 SURVIVAL • Record type 31 is
Page 1560 and 1561:
1560 SYSFILE INFO
Page 1562 and 1563:
1562 Syntax Reference Operations Ex
Page 1564 and 1565:
1564 TEMPORARY Example • The XSAV
Page 1566 and 1567:
TITLE TITLE [’]text[’] Example
Page 1568 and 1569:
TSET TSET [PRINT={DEFAULT**}] [/NEW
Page 1570 and 1571:
1570 TSET MXPREDICT Subcommand MXPR
Page 1572 and 1573:
TSPLOT TSPLOT [VARIABLES=] variable
Page 1574 and 1575:
1574 TSPLOT Subcommand Order • Su
Page 1576 and 1577:
1576 TSPLOT Example TSPLOT TICKETS
Page 1578 and 1579:
1578 TSPLOT Figure 3 FORMAT=REFEREN
Page 1580 and 1581:
1580 TSPLOT UNIFORM Scale uniformly
Page 1582 and 1583:
1582 T-TEST degrees of freedom, and
Page 1584 and 1585:
1584 T-TEST PAIRS Subcommand PAIRS
Page 1586 and 1587:
2SLS Overview Options 2SLS is avail
Page 1588 and 1589:
1588 2SLS • In this example, Y1 i
Page 1590 and 1591:
1590 2SLS • In this example, the
Page 1592 and 1593:
TWOSTEP CLUSTER Overview TWOSTEP CL
Page 1594 and 1595:
1594 TWOSTEP CLUSTER Example TWOSTE
Page 1596 and 1597:
1596 TWOSTEP CLUSTER Example TWOSTE
Page 1598 and 1599:
1598 TWOSTEP CLUSTER STATE Save the
Page 1600 and 1601:
1600 TWOSTEP CLUSTER SUMMARY Descri
Page 1602 and 1603:
1602 UNIANOVA Overview Options ** D
Page 1604 and 1605:
1604 UNIANOVA Example UNIANOVA YIEL
Page 1606 and 1607:
1606 UNIANOVA appropriate effect is
Page 1608 and 1609:
1608 UNIANOVA PRINT Subcommand PRIN
Page 1610 and 1611:
1610 UNIANOVA Example UNIANOVA DEP
Page 1612 and 1613:
1612 UNIANOVA • B1 versus B2 at A
Page 1614 and 1615:
1614 UNIANOVA HELMERT Helmert contr
Page 1616 and 1617:
1616 UNIANOVA Post Hoc Tests Statis
Page 1618 and 1619:
1618 UNIANOVA QREGW Ryan-Einot-Gabr
Page 1620 and 1621:
1620 UNIANOVA SRESID Studentized re
Page 1622 and 1623:
UPDATE UPDATE FILE={master file} {*
Page 1624 and 1625:
1624 UPDATE • UPDATE copies all v
Page 1626 and 1627:
1626 UPDATE BY Subcommand BY specif
Page 1628 and 1629:
1628 UPDATE • IN has only one spe
Page 1630 and 1631:
1630 USE • Values on keyword YEAR
Page 1632 and 1633:
1632 USE USE THRU 5. • This comma
Page 1634 and 1635:
1634 VALUE LABELS Operations Exampl
Page 1636 and 1637:
VARCOMP Overview Options VARCOMP is
Page 1638 and 1639:
1638 VARCOMP • You can specify mu
Page 1640 and 1641:
1640 VARCOMP The default is 1.0E-8.
Page 1642 and 1643:
1642 VARCOMP Nesting within an inte
Page 1644 and 1645:
VARIABLE LABELS VARIABLE LABELS var
Page 1646 and 1647:
VARIABLE LEVEL VARIABLE LEVEL varli
Page 1648 and 1649:
VARSTOCASES VARSTOCASES /MAKE new v
Page 1650 and 1651:
1650 VARSTOCASES The command: VARST
Page 1652 and 1653:
1652 VARSTOCASES Example VARSTOCASE
Page 1654 and 1655:
1654 VARSTOCASES COUNT Subcommand W
Page 1656 and 1657:
1656 VECTOR Syntax Rules • Multip
Page 1658 and 1659:
1658 VECTOR Example VECTOR X,Y(A5,6
Page 1660 and 1661:
1660 VECTOR • Aggregating by vari
Page 1662 and 1663:
1662 VERIFY Operations • VERIFY r
Page 1664 and 1665:
1664 WEIGHT Example • Each WEIGHT
Page 1666 and 1667:
1666 WLS without erasing values sav
Page 1668 and 1669:
1668 WLS DELTA Subcommand DELTA, al
Page 1670 and 1671:
1670 WLS Example WLS X1 WITH Y1 /SO
Page 1672 and 1673:
1672 WRITE Basic Specification The
Page 1674 and 1675:
1674 WRITE Strings • MOHIRED, YRH
Page 1676 and 1677:
WRITE FORMATS WRITE FORMATS varlist
Page 1678 and 1679:
1678 WRITE FORMATS Example COMPUTE
Page 1680 and 1681:
1680 XSAVE Basic Specification The
Page 1682 and 1683:
1682 XSAVE • Keyword ALL on KEEP
Page 1684:
1684 XSAVE • The only specificati
Page 1687 and 1688:
Appendix A Commands and Program Sta
Page 1689 and 1690:
Determining Command Order Commands
Page 1691 and 1692:
Table A.1 Commands and program stat
Page 1693 and 1694:
Input Program Commands Commands and
Page 1695 and 1696:
Appendix B IMPORT/EXPORT Character
Page 1697 and 1698:
Position Graphic Macintosh Microsof
Page 1699 and 1700:
Position Graphic Macintosh Microsof
Page 1701:
Position Graphic Macintosh 222 â 1
Page 1704 and 1705:
1704 Appendix C Figure C.1 File REC
Page 1706 and 1707:
1706 Appendix C Figure C.4 NESTED.D
Page 1708 and 1709:
1708 Appendix C • The output from
Page 1710 and 1711:
1710 Appendix C FILE TYPE GROUPED R
Page 1712 and 1713:
1712 Appendix C Figure C.8 LIST out
Page 1714 and 1715:
1714 Appendix C • REPEATING DATA
Page 1716 and 1717:
1716 Appendix C The loop terminates
Page 1718 and 1719:
1718 Appendix D Example 1: Automati
Page 1720 and 1721:
1720 Appendix D • Commands betwee
Page 1722 and 1723:
1722 Appendix D Figure D.7 Listing
Page 1724 and 1725:
1724 Appendix D You can modify the
Page 1726 and 1727:
1726 Appendix D • !TOKENS(1) spec
Page 1728 and 1729:
1728 Appendix D Figure D.15 Output
Page 1730 and 1731:
1730 Appendix D Figure D.19 !DATAGE
Page 1733 and 1734:
Appendix A Trends Options: Special
Page 1735 and 1736:
Trends Options: Special Considerati
Page 1737 and 1738:
Trends Options: Special Considerati
Page 1739 and 1740:
Subject Index active data file cach
Page 1741 and 1742:
inary shape difference in Distances
Page 1743 and 1744:
in Logistic Regression procedure, 8
Page 1745 and 1746:
in Multidimensional Scaling procedu
Page 1747 and 1748:
scratch files, 1492 data dictionary
Page 1749 and 1750:
matrices, 479 matrix input, 482 mat
Page 1751 and 1752:
in Hierarchical Loglinear Analysis
Page 1753 and 1754:
cell weights, 610, 821 contrasts, 8
Page 1755 and 1756:
hierarchical loglinear analysis, 71
Page 1757 and 1758:
in Autoregression procedure, 148- 1
Page 1759 and 1760:
See also Linear Regression procedur
Page 1761 and 1762:
linear transformations, 871 naming
Page 1763 and 1764:
date format variables, 986 defining
Page 1765 and 1766:
function precision, 1056 infinite s
Page 1767 and 1768:
in Cox Regression procedure, 302 in
Page 1769 and 1770:
output, 1489, 1494 output page size
Page 1771 and 1772:
elative risk ratio in Crosstabs pro
Page 1773 and 1774:
scientific notation controlling dis
Page 1775 and 1776:
in ROC Curve procedure, 1445 standa
Page 1777 and 1778:
fixed format, 414, 415, 416, 423 fr
Page 1779 and 1780:
date format variables, 1633 in Homo
Page 1781 and 1782:
Syntax Index !BLANKS (function) DEF
Page 1783 and 1784:
AGGREGATE (command), 90 BREAK subco
Page 1785 and 1786:
AR (subcommand) ARIMA command, 158
Page 1787 and 1788:
REPORT command, 1417 BLANKS (subcom
Page 1789 and 1790:
CASENUM$ (system variable) in PRINT
Page 1791 and 1792:
REGRESSION command, 1360 CIN (subco
Page 1793 and 1794:
SHOW command, 1499 COMPUTE (command
Page 1795 and 1796:
TWOSTEP CLUSTER command, 1600 COUNT
Page 1797 and 1798:
WRITE subcommand, 325 CROSSVALID (k
Page 1799 and 1800:
Symbols D (keyword) CLUSTER command
Page 1801 and 1802:
NPAR TESTS command, 1100 ONEWAY com
Page 1803 and 1804:
DISPER (keyword) CLUSTER command, 2
Page 1805 and 1806:
MIXED command, 999 UNIANOVA command
Page 1807 and 1808:
EXPERIMENTAL (keyword) ANOVA comman
Page 1809 and 1810:
MEANS command, 983 PROXSCAL command
Page 1811 and 1812:
GAC (keyword) OLAP CUBES command, 1
Page 1813 and 1814:
TEST(SSCP) keyword, 674 TUKEY keywo
Page 1815 and 1816:
HISTORY (keyword) CATPCA command, 2
Page 1817 and 1818:
INCLUDE (command), 771 FILE subcomm
Page 1819 and 1820:
JITTER (keyword) IGRAPH command, 75
Page 1821 and 1822:
LEAVE (command), 796 LEFT (keyword)
Page 1823 and 1824:
CWEIGHT subcommand, 821 DESIGN subc
Page 1825 and 1826:
ROVMAP subcommand, 896 SHOWLABEL su
Page 1827 and 1828:
RMV command, 1440 MEAN (keyword) AN
Page 1829 and 1830:
MANOVA command, 858 MEANS command,
Page 1831 and 1832:
CATREG command, 212 MULTIPUNCH (key
Page 1833 and 1834:
NMISS (function) AGGREGATE command,
Page 1835 and 1836:
NOREFERENCE (keyword) TSPLOT comman
Page 1837 and 1838:
CATREG command, 215 ODBC (keyword)
Page 1839 and 1840:
RATIO STATISTICS command, 1328 REGR
Page 1841 and 1842:
PER (keyword) SPECTRA command, 1530
Page 1843 and 1844:
SUMMARY keyword, 1216 TEST subcomma
Page 1845 and 1846:
CATREG command, 215 CLUSTER command
Page 1847 and 1848:
QUANT (keyword) CATPCA command, 200
Page 1849 and 1850:
with FORMATS command, 1349 REG (key
Page 1851 and 1852:
CSTABULATE command, 374 CURVEFIT co
Page 1853 and 1854:
SAMPLEFILE (subcommand) CSSELECT co
Page 1855 and 1856:
SEED (keyword) CSSELECT command, 34
Page 1857 and 1858:
MXLOOPS subcommand, 1500 MXMEMORY s
Page 1859 and 1860:
SP (subcommand) ARIMA command, 156-
Page 1861 and 1862:
DISCRIMINANT command, 479 FREQUENCI
Page 1863 and 1864:
Symbols T (function) MATRIX command
Page 1865 and 1866:
TOLERANCE (subcommand) DISCRIMINANT
Page 1867 and 1868:
UNCLASSIFIED (keyword) DISCRIMINANT
Page 1869 and 1870:
REPORT command, 1414, 1418 value la
Page 1871 and 1872:
VIN (subcommand) DISCRIMINANT comma
Page 1873 and 1874:
X1MULTIPLIER (keyword) IGRAPH comma
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