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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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208 <strong>Syntax</strong> <strong>Reference</strong><br />
Options<br />
Basic Specification<br />
<strong>Syntax</strong> Rules<br />
Transformation type. You can specify the transformation type (spline ordinal, spline nominal,<br />
ordinal, nominal, or numerical) at which you want to analyze each variable.<br />
Discretization. You can use the DISCRETIZATION subcommand to discretize fractional-value<br />
variables or to recode categorical variables.<br />
Initial configuration. You can specify the kind of initial configuration through the INITIAL<br />
subcommand.<br />
Tuning the algorithm. You can control the values of algorithm-tuning parameters with the<br />
MAXITER and CRITITER subcommands.<br />
Missing data. You can specify the treatment of missing data with the MISSING subcommand.<br />
Optional output. You can request optional output through the PRINT subcommand.<br />
Transformation plot per variable. You can request a plot per variable of its quantification against<br />
the category numbers.<br />
Residual plot per variable. You can request an overlay plot per variable of the residuals and the<br />
weighted quantification, against the category numbers.<br />
Writing external data. You can write the transformed data (category numbers replaced with<br />
optimal quantifications) to an outfile for use in further analyses. You can also write the<br />
discretized data to an outfile.<br />
Saving variables. You can save the transformed variables, the predicted values, and/or the<br />
residuals in the working data file.<br />
The basic specification is the command CATREG with the VARIABLES and ANALYSIS<br />
subcommands.<br />
• The VARIABLES and ANALYSIS subcommands must always appear, and the VARIABLES<br />
subcommand must be the first subcommand specified. The other subcommands, if<br />
specified, can be in any order.<br />
• Variables specified in the ANALYSIS subcommand must be found in the VARIABLES<br />
subcommand.<br />
• In the ANALYSIS subcommand, exactly one variable must be specified as a dependent<br />
variable and at least one variable must be specified as an independent variable after the<br />
keyword WITH.<br />
• The word WITH is reserved as a keyword in the CATREG procedure. Thus, it may not be<br />
a variable name in CATREG. Also, the word TO is a reserved word in SPSS.
208 <strong>Syntax</strong> <strong>Reference</strong> Options Basic Specification <strong>Syntax</strong> Rules Transformation type. You can specify the transformation type (spline ordinal, spline nominal, ordinal, nominal, or numerical) at which you want to analyze each variable. Discretization. You can use the DISCRETIZATION subcommand to discretize fractional-value variables or to recode categorical variables. Initial configuration. You can specify the kind of initial configuration through the INITIAL subcommand. Tuning the algorithm. You can control the values of algorithm-tuning parameters with the MAXITER and CRITITER subcommands. Missing data. You can specify the treatment of missing data with the MISSING subcommand. Optional output. You can request optional output through the PRINT subcommand. Transformation plot per variable. You can request a plot per variable of its quantification against the category numbers. Residual plot per variable. You can request an overlay plot per variable of the residuals and the weighted quantification, against the category numbers. Writing external data. You can write the transformed data (category numbers replaced with optimal quantifications) to an outfile for use in further analyses. You can also write the discretized data to an outfile. Saving variables. You can save the transformed variables, the predicted values, and/or the residuals in the working data file. The basic specification is the command CATREG with the VARIABLES and ANALYSIS subcommands. • The VARIABLES and ANALYSIS subcommands must always appear, and the VARIABLES subcommand must be the first subcommand specified. The other subcommands, if specified, can be in any order. • Variables specified in the ANALYSIS subcommand must be found in the VARIABLES subcommand. • In the ANALYSIS subcommand, exactly one variable must be specified as a dependent variable and at least one variable must be specified as an independent variable after the keyword WITH. • The word WITH is reserved as a keyword in the CATREG procedure. Thus, it may not be a variable name in CATREG. Also, the word TO is a reserved word in SPSS.
Operations Limitations CATREG 209 • If a subcommand is specified more than once, the last one is executed but with a syntax warning. Note this is true also for the VARIABLES and ANALYSIS subcommands. • If more than one dependent variable is specified in the ANALYSIS subcommand, CATREG is not executed. • CATREG operates on category indicator variables. The category indicators should be positive integers. You can use the DISCRETIZATION subcommand to convert fractional-value variables and string variables into positive integers. If DISCRETIZATION is not specified, fractional-value variables are automatically converted into positive integers by grouping them into seven categories with a close to normal distribution and string variables are automatically converted into positive integers by ranking. • In addition to system missing values and user defined missing values, CATREG treats category indicator values less than 1 as missing. If one of the values of a categorical variable has been coded 0 or some negative value and you want to treat it as a valid category, use the COMPUTE command to add a constant to the values of that variable such that the lowest value will be 1. (See the SPSS <strong>Syntax</strong> <strong>Reference</strong> Guide or the SPSS Base User’s Guide for more information on COMPUTE). You can also use the RANKING option of the DISCRETIZATION subcommand for this purpose, except for variables you want to treat as numerical, since the characteristic of equal intervals in the data will not be maintained. • There must be at least three valid cases. • The number of valid cases must be greater than the number of independent variables plus 1. • The maximum number of independent variables is 200. • Split-File has no implications for CATREG. Example CATREG VARIABLES = TEST1 TEST3 TEST2 TEST4 TEST5 TEST6 TEST7 TO TEST9 STATUS01 STATUS02 /ANALYSIS TEST4 (LEVEL=NUME) WITH TEST1 TO TEST2 (LEVEL=SPORD DEGREE=1 INKNOT=3) TEST5 TEST7 (LEVEL=SPNOM) TEST8 (LEVEL=ORDI) STATUS01 STATUS02 (LEVEL=NOMI) /DISCRETIZATION = TEST1(GROUPING NCAT=5 DISTR=UNIFORM) TEST5(GROUPING) TEST7(MULTIPLYING) /INITIAL = RANDOM /MAXITER = 100 /CRITITER = .000001 /MISSING = MODEIMPU /PRINT = R COEFF DESCRIP ANOVA QUANT(TEST1 TO TEST2 STATUS01 STATUS02) /PLOT = TRANS (TEST2 TO TEST7 TEST4) /SAVE /OUTFILE = ’c:\data\qdata.sav’.
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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
- Page 157 and 158: D Order of differencing. Q Moving-a
- Page 159 and 160: Termination Criteria Subcommands CI
- Page 161 and 162: References ARIMA 161 Akaike, H. 197
- Page 163 and 164: Subcommand Order • VARIABLES must
- Page 165 and 166: Example AUTORECODE 165 DATA LIST /
- Page 167 and 168: BEGIN DATA—END DATA BEGIN DATA da
- Page 169 and 170: BREAK BREAK Overview BREAK controls
- Page 171 and 172: CASEPLOT Overview CASEPLOT [VARIABL
- Page 173 and 174: Subcommand Order • Subcommands ca
- Page 175 and 176: LN and NOLOG Subcommands CASEPLOT 1
- Page 177 and 178: CASEPLOT 177 erence line. Figure 3
- Page 179 and 180: CASEPLOT 179 • If FORMAT=REFERENC
- Page 181 and 182: Options CASESTOVARS 181 Automatic c
- Page 183 and 184: The commands: CASESTOVARS 183 SPLIT
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- Page 189 and 190: CATPCA CATPCA is available in the C
- Page 191 and 192: Optional output. You can request op
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- Page 195 and 196: SPORD and SPNOM Keywords The follow
- Page 197 and 198: ACTIVE Keyword The ACTIVE keyword h
- Page 199 and 200: MAXITER Subcommand CATPCA 199 MAXIT
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- Page 205 and 206: CATPCA 205 procedures with the succ
- Page 207: CATREG Overview CATREG is available
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- Page 215 and 216: PRINT Subcommand CATREG 215 The PRI
- Page 217 and 218: SAVE Subcommand OUTFILE Subcommand
- Page 219 and 220: CCF Overview Options CCF [VARIABLES
- Page 221 and 222: CCF 221 • LN transforms the data
- Page 223 and 224: CCF 223 • If a natural log transf
- Page 225 and 226: CLEAR TRANSFORMATIONS Overview CLEA
- Page 227 and 228: Example Overview Options CLUSTER V1
- Page 229 and 230: CLUSTER 229 • The variable list i
- Page 231 and 232: Measures for Binary Data CLUSTER 23
- Page 233 and 234: DICE[(p[,np])] Dice (or Czekanowski
- Page 235 and 236: Y( x, y) ad - bc = ----------------
- Page 237 and 238: CLUSTER 237 MEDIAN Median clusterin
- Page 239 and 240: CLUSTER 239 • This example displa
- Page 241 and 242: Matrix Input CLUSTER 241 • The ma
- Page 243 and 244: Example Example Example DATA LIST F
- Page 245 and 246: COMMENT {COMMENT} text { * } Overvi
- Page 247 and 248: Cumulative distribution functions (
- Page 249 and 250: Cumulative distribution functions (
- Page 251 and 252: Logical functions: RANGE(varname,ra
- Page 253 and 254: String Transformations COMPUTE 253
- Page 255 and 256: Examples COMPUTE 255 • The string
- Page 257 and 258: 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
- Page 893 and 894:
Operations 893 MAPS • Each MAPS c
- Page 895 and 896:
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
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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
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948 MATRIX—END MATRIX NAMES Speci
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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
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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
- 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
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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
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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
- 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
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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
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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
- Page 1026 and 1027:
1026 MULT RESPONSE ROW Row percenta
- Page 1028 and 1029:
1028 MULT RESPONSE The following ke
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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
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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
- 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
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1066 NOMREG mates convergence crite
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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:
1092 NPAR TESTS Operations Example
- Page 1094 and 1095:
1094 NPAR TESTS MEDIAN Subcommand S
- Page 1096 and 1097:
1096 NPAR TESTS MOSES Subcommand Sy
- Page 1098 and 1099:
1098 NPAR TESTS Operations Example
- 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
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1130 OMS tics in the columns. To in
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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:
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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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
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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:
1246 Syntax Reference SAVE Subcomma
- 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
- Page 1266 and 1267:
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
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1298 Syntax Reference Example DATA
- Page 1300 and 1301:
1300 Syntax Reference Example DATA
- 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
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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
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1348 RECORD TYPE • SPREAD can be
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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:
1530 Syntax Reference SAVE Subcomma
- 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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