+@c PSPP - a program for statistical analysis.
+@c Copyright (C) 2017 Free Software Foundation, Inc.
+@c Permission is granted to copy, distribute and/or modify this document
+@c under the terms of the GNU Free Documentation License, Version 1.3
+@c or any later version published by the Free Software Foundation;
+@c with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
+@c A copy of the license is included in the section entitled "GNU
+@c Free Documentation License".
+@c
@node Statistics
@chapter Statistics
@cindex data reduction
@display
-FACTOR VARIABLES=@var{var_list}
+FACTOR @{
+ VARIABLES=@var{var_list},
+ MATRIX IN (@{CORR,COV@}=@{*,@var{file_spec}@})
+ @}
[ /METHOD = @{CORRELATION, COVARIANCE@} ]
[ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, PROMAX[(@var{k})], NOROTATE@}]
- [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [KMO] [SIG] [ALL] [DEFAULT] ]
+ [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [KMO] [AIC] [SIG] [ALL] [DEFAULT] ]
[ /PLOT=[EIGEN] ]
The @cmd{FACTOR} command performs Factor Analysis or Principal Axis Factoring on a dataset. It may be used to find
common factors in the data or for data reduction purposes.
-The @subcmd{VARIABLES} subcommand is required. It lists the variables
-which are to partake in the analysis. (The @subcmd{ANALYSIS}
+The @subcmd{VARIABLES} subcommand is required (unless the @subcmd{MATRIX IN}
+subcommand is used).
+It lists the variables which are to partake in the analysis. (The @subcmd{ANALYSIS}
subcommand may optionally further limit the variables that
-participate; it is not useful and implemented only for compatibility.)
+participate; it is useful primarily in conjunction with @subcmd{MATRIX IN}.)
+
+If @subcmd{MATRIX IN} instead of @subcmd{VARIABLES} is specified, then the analysis
+is performed on a pre-prepared correlation or covariance matrix file instead of on
+individual data cases. Typically the matrix file will have been generated by
+@cmd{MATRIX DATA} (@pxref{MATRIX DATA}) or provided by a third party.
+If specified, @subcmd{MATRIX IN} must be followed by @samp{COV} or @samp{CORR},
+then by @samp{=} and @var{file_spec} all in parentheses.
+@var{file_spec} may either be an asterisk, which indicates the currently loaded
+dataset, or it may be a filename to be loaded. @xref{MATRIX DATA}, for the expected
+format of the file.
The @subcmd{/EXTRACTION} subcommand is used to specify the way in which factors (components) are extracted from the data.
If @subcmd{PC} is specified, then Principal Components Analysis is used.
The covariance matrix is printed.
@item @subcmd{DET}
The determinant of the correlation or covariance matrix is printed.
+@item @subcmd{AIC}
+ The anti-image covariance and anti-image correlation matrices are printed.
@item @subcmd{KMO}
The Kaiser-Meyer-Olkin measure of sampling adequacy and the Bartlett test of sphericity is printed.
@item @subcmd{SIG}
The @subcmd{MISSING} subcommand determines the handling of missing
variables.
-If @subcmd{INCLUDE} is set, then user-missing values are included in the
-calculations, but system-missing values are not.
-If @subcmd{EXCLUDE} is set, which is the default, user-missing
-values are excluded as well as system-missing values.
-This is the default.
-
+If @subcmd{INCLUDE} is set then, for the purposes of GLM analysis,
+only system-missing values are considered
+to be missing; user-missing values are not regarded as missing.
+If @subcmd{EXCLUDE} is set, which is the default, then user-missing
+values are considered to be missing as well as system-missing values.
+A case for which any dependent variable or any factor
+variable has a missing value is excluded from the analysis.
@node LOGISTIC REGRESSION
@section LOGISTIC REGRESSION