+@node FACTOR
+@section FACTOR
+
+@vindex FACTOR
+@cindex factor analysis
+@cindex principal components analysis
+@cindex principal axis factoring
+@cindex data reduction
+
+@display
+FACTOR VARIABLES=@var{var_list}
+
+ [ /METHOD = @{CORRELATION, COVARIANCE@} ]
+
+ [ /ANALYSIS=@var{var_list} ]
+
+ [ /EXTRACTION=@{PC, PAF@}]
+
+ [ /ROTATION=@{VARIMAX, EQUAMAX, QUARTIMAX, PROMAX[(@var{k})], NOROTATE@}]
+
+ [ /PRINT=[INITIAL] [EXTRACTION] [ROTATION] [UNIVARIATE] [CORRELATION] [COVARIANCE] [DET] [KMO] [SIG] [ALL] [DEFAULT] ]
+
+ [ /PLOT=[EIGEN] ]
+
+ [ /FORMAT=[SORT] [BLANK(@var{n})] [DEFAULT] ]
+
+ [ /CRITERIA=[FACTORS(@var{n})] [MINEIGEN(@var{l})] [ITERATE(@var{m})] [ECONVERGE (@var{delta})] [DEFAULT] ]
+
+ [ /MISSING=[@{LISTWISE, PAIRWISE@}] [@{INCLUDE, EXCLUDE@}] ]
+@end display
+
+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}
+subcommand may optionally further limit the variables that
+participate; it is not useful and implemented only for compatibility.)
+
+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.
+If @subcmd{PAF} is specified, then Principal Axis Factoring is
+used. By default Principal Components Analysis will be used.
+
+The @subcmd{/ROTATION} subcommand is used to specify the method by which the extracted solution will be rotated.
+Three orthogonal rotation methods are available:
+@subcmd{VARIMAX} (which is the default), @subcmd{EQUAMAX}, and @subcmd{QUARTIMAX}.
+There is one oblique rotation method, @i{viz}: @subcmd{PROMAX}.
+Optionally you may enter the power of the promax rotation @var{k}, which must be enclosed in parentheses.
+The default value of @var{k} is 5.
+If you don't want any rotation to be performed, the word @subcmd{NOROTATE} will prevent the command from performing any
+rotation on the data.
+
+The @subcmd{/METHOD} subcommand should be used to determine whether the covariance matrix or the correlation matrix of the data is
+to be analysed. By default, the correlation matrix is analysed.
+
+The @subcmd{/PRINT} subcommand may be used to select which features of the analysis are reported:
+
+@itemize
+@item @subcmd{UNIVARIATE}
+ A table of mean values, standard deviations and total weights are printed.
+@item @subcmd{INITIAL}
+ Initial communalities and eigenvalues are printed.
+@item @subcmd{EXTRACTION}
+ Extracted communalities and eigenvalues are printed.
+@item @subcmd{ROTATION}
+ Rotated communalities and eigenvalues are printed.
+@item @subcmd{CORRELATION}
+ The correlation matrix is printed.
+@item @subcmd{COVARIANCE}
+ The covariance matrix is printed.
+@item @subcmd{DET}
+ The determinant of the correlation or covariance matrix is printed.
+@item @subcmd{KMO}
+ The Kaiser-Meyer-Olkin measure of sampling adequacy and the Bartlett test of sphericity is printed.
+@item @subcmd{SIG}
+ The significance of the elements of correlation matrix is printed.
+@item @subcmd{ALL}
+ All of the above are printed.
+@item @subcmd{DEFAULT}
+ Identical to @subcmd{INITIAL} and @subcmd{EXTRACTION}.
+@end itemize
+
+If @subcmd{/PLOT=EIGEN} is given, then a ``Scree'' plot of the eigenvalues will be printed. This can be useful for visualizing
+which factors (components) should be retained.
+
+The @subcmd{/FORMAT} subcommand determined how data are to be displayed in loading matrices. If @subcmd{SORT} is specified, then the variables
+are sorted in descending order of significance. If @subcmd{BLANK(@var{n})} is specified, then coefficients whose absolute value is less
+than @var{n} will not be printed. If the keyword @subcmd{DEFAULT} is given, or if no @subcmd{/FORMAT} subcommand is given, then no sorting is
+performed, and all coefficients will be printed.
+
+The @subcmd{/CRITERIA} subcommand is used to specify how the number of extracted factors (components) are chosen.
+If @subcmd{FACTORS(@var{n})} is
+specified, where @var{n} is an integer, then @var{n} factors will be extracted. Otherwise, the @subcmd{MINEIGEN} setting will
+be used.
+@subcmd{MINEIGEN(@var{l})} requests that all factors whose eigenvalues are greater than or equal to @var{l} are extracted.
+The default value of @var{l} is 1.
+The @subcmd{ECONVERGE} setting has effect only when iterative algorithms for factor
+extraction (such as Principal Axis Factoring) are used.
+@subcmd{ECONVERGE(@var{delta})} specifies that
+iteration should cease when
+the maximum absolute value of the communality estimate between one iteration and the previous is less than @var{delta}. The
+default value of @var{delta} is 0.001.
+The @subcmd{ITERATE(@var{m})} may appear any number of times and is used for two different purposes.
+It is used to set the maximum number of iterations (@var{m}) for convergence and also to set the maximum number of iterations
+for rotation.
+Whether it affects convergence or rotation depends upon which subcommand follows the @subcmd{ITERATE} subcommand.
+If @subcmd{EXTRACTION} follows, it affects convergence.
+If @subcmd{ROTATION} follows, it affects rotation.
+If neither @subcmd{ROTATION} nor @subcmd{EXTRACTION} follow a @subcmd{ITERATE} subcommand it will be ignored.
+The default value of @var{m} is 25.
+
+The @cmd{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{LISTWISE} is set, then the entire case is excluded from analysis
+whenever any variable specified in the @cmd{VARIABLES} subcommand
+contains a missing value.
+If @subcmd{PAIRWISE} is set, then a case is considered missing only if either of the
+values for the particular coefficient are missing.
+The default is @subcmd{LISTWISE}.
+
+@node LOGISTIC REGRESSION
+@section LOGISTIC REGRESSION
+
+@vindex LOGISTIC REGRESSION
+@cindex logistic regression
+@cindex bivariate logistic regression
+
+@display
+LOGISTIC REGRESSION [VARIABLES =] @var{dependent_var} WITH @var{predictors}
+
+ [/CATEGORICAL = @var{categorical_predictors}]
+
+ [@{/NOCONST | /ORIGIN | /NOORIGIN @}]
+
+ [/PRINT = [SUMMARY] [DEFAULT] [CI(@var{confidence})] [ALL]]
+
+ [/CRITERIA = [BCON(@var{min_delta})] [ITERATE(@var{max_interations})]
+ [LCON(@var{min_likelihood_delta})] [EPS(@var{min_epsilon})]
+ [CUT(@var{cut_point})]]
+
+ [/MISSING = @{INCLUDE|EXCLUDE@}]
+@end display
+
+Bivariate Logistic Regression is used when you want to explain a dichotomous dependent
+variable in terms of one or more predictor variables.
+
+The minimum command is
+@example
+LOGISTIC REGRESSION @var{y} WITH @var{x1} @var{x2} @dots{} @var{xn}.
+@end example
+Here, @var{y} is the dependent variable, which must be dichotomous and @var{x1} @dots{} @var{xn}
+are the predictor variables whose coefficients the procedure estimates.
+
+By default, a constant term is included in the model.
+Hence, the full model is
+@math{
+{\bf y}
+= b_0 + b_1 {\bf x_1}
++ b_2 {\bf x_2}
++ \dots
++ b_n {\bf x_n}
+}
+
+Predictor variables which are categorical in nature should be listed on the @subcmd{/CATEGORICAL} subcommand.
+Simple variables as well as interactions between variables may be listed here.
+
+If you want a model without the constant term @math{b_0}, use the keyword @subcmd{/ORIGIN}.
+@subcmd{/NOCONST} is a synonym for @subcmd{/ORIGIN}.
+
+An iterative Newton-Raphson procedure is used to fit the model.
+The @subcmd{/CRITERIA} subcommand is used to specify the stopping criteria of the procedure,
+and other parameters.
+The value of @var{cut_point} is used in the classification table. It is the
+threshold above which predicted values are considered to be 1. Values
+of @var{cut_point} must lie in the range [0,1].
+During iterations, if any one of the stopping criteria are satisfied, the procedure is
+considered complete.
+The stopping criteria are:
+@itemize
+@item The number of iterations exceeds @var{max_iterations}.
+ The default value of @var{max_iterations} is 20.
+@item The change in the all coefficient estimates are less than @var{min_delta}.
+The default value of @var{min_delta} is 0.001.
+@item The magnitude of change in the likelihood estimate is less than @var{min_likelihood_delta}.
+The default value of @var{min_delta} is zero.
+This means that this criterion is disabled.
+@item The differential of the estimated probability for all cases is less than @var{min_epsilon}.
+In other words, the probabilities are close to zero or one.
+The default value of @var{min_epsilon} is 0.00000001.
+@end itemize
+
+
+The @subcmd{PRINT} subcommand controls the display of optional statistics.
+Currently there is one such option, @subcmd{CI}, which indicates that the
+confidence interval of the odds ratio should be displayed as well as its value.
+@subcmd{CI} should be followed by an integer in parentheses, to indicate the
+confidence level of the desired confidence interval.
+
+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.
+
+@node MEANS
+@section MEANS
+
+@vindex MEANS
+@cindex means
+
+@display
+MEANS [TABLES =]
+ @{@var{var_list}@}
+ [ BY @{@var{var_list}@} [BY @{@var{var_list}@} [BY @{@var{var_list}@} @dots{} ]]]
+
+ [ /@{@var{var_list}@}
+ [ BY @{@var{var_list}@} [BY @{@var{var_list}@} [BY @{@var{var_list}@} @dots{} ]]] ]
+
+ [/CELLS = [MEAN] [COUNT] [STDDEV] [SEMEAN] [SUM] [MIN] [MAX] [RANGE]
+ [VARIANCE] [KURT] [SEKURT]
+ [SKEW] [SESKEW] [FIRST] [LAST]
+ [HARMONIC] [GEOMETRIC]
+ [DEFAULT]
+ [ALL]
+ [NONE] ]
+
+ [/MISSING = [TABLE] [INCLUDE] [DEPENDENT]]
+@end display
+
+You can use the @cmd{MEANS} command to calculate the arithmetic mean and similar
+statistics, either for the dataset as a whole or for categories of data.
+
+The simplest form of the command is
+@example
+MEANS @var{v}.
+@end example
+@noindent which calculates the mean, count and standard deviation for @var{v}.
+If you specify a grouping variable, for example
+@example
+MEANS @var{v} BY @var{g}.
+@end example
+@noindent then the means, counts and standard deviations for @var{v} after having
+been grouped by @var{g} will be calculated.
+Instead of the mean, count and standard deviation, you could specify the statistics
+in which you are interested:
+@example
+MEANS @var{x} @var{y} BY @var{g}
+ /CELLS = HARMONIC SUM MIN.
+@end example
+This example calculates the harmonic mean, the sum and the minimum values of @var{x} and @var{y}
+grouped by @var{g}.
+
+The @subcmd{CELLS} subcommand specifies which statistics to calculate. The available statistics
+are:
+@itemize
+@item @subcmd{MEAN}
+@cindex arithmetic mean
+ The arithmetic mean.
+@item @subcmd{COUNT}
+ The count of the values.
+@item @subcmd{STDDEV}
+ The standard deviation.
+@item @subcmd{SEMEAN}
+ The standard error of the mean.
+@item @subcmd{SUM}
+ The sum of the values.
+@item @subcmd{MIN}
+ The minimum value.
+@item @subcmd{MAX}
+ The maximum value.
+@item @subcmd{RANGE}
+ The difference between the maximum and minimum values.
+@item @subcmd{VARIANCE}
+ The variance.
+@item @subcmd{FIRST}
+ The first value in the category.
+@item @subcmd{LAST}
+ The last value in the category.
+@item @subcmd{SKEW}
+ The skewness.
+@item @subcmd{SESKEW}
+ The standard error of the skewness.
+@item @subcmd{KURT}
+ The kurtosis
+@item @subcmd{SEKURT}
+ The standard error of the kurtosis.
+@item @subcmd{HARMONIC}
+@cindex harmonic mean
+ The harmonic mean.
+@item @subcmd{GEOMETRIC}
+@cindex geometric mean
+ The geometric mean.
+@end itemize
+
+In addition, three special keywords are recognized:
+@itemize
+@item @subcmd{DEFAULT}
+ This is the same as @subcmd{MEAN} @subcmd{COUNT} @subcmd{STDDEV}.
+@item @subcmd{ALL}
+ All of the above statistics will be calculated.
+@item @subcmd{NONE}
+ No statistics will be calculated (only a summary will be shown).
+@end itemize
+
+
+More than one @dfn{table} can be specified in a single command.
+Each table is separated by a @samp{/}. For
+example
+@example
+MEANS TABLES =
+ @var{c} @var{d} @var{e} BY @var{x}
+ /@var{a} @var{b} BY @var{x} @var{y}
+ /@var{f} BY @var{y} BY @var{z}.
+@end example
+has three tables (the @samp{TABLE =} is optional).
+The first table has three dependent variables @var{c}, @var{d} and @var{e}
+and a single categorical variable @var{x}.
+The second table has two dependent variables @var{a} and @var{b},
+and two categorical variables @var{x} and @var{y}.
+The third table has a single dependent variables @var{f}
+and a categorical variable formed by the combination of @var{y} and @var{z}.
+
+
+By default values are omitted from the analysis only if missing values
+(either system missing or user missing)
+for any of the variables directly involved in their calculation are
+encountered.
+This behaviour can be modified with the @subcmd{/MISSING} subcommand.
+Three options are possible: @subcmd{TABLE}, @subcmd{INCLUDE} and @subcmd{DEPENDENT}.
+
+@subcmd{/MISSING = TABLE} causes cases to be dropped if any variable is missing
+in the table specification currently being processed, regardless of
+whether it is needed to calculate the statistic.
+
+@subcmd{/MISSING = INCLUDE} says that user missing values, either in the dependent
+variables or in the categorical variables should be taken at their face
+value, and not excluded.
+
+@subcmd{/MISSING = DEPENDENT} says that user missing values, in the dependent
+variables should be taken at their face value, however cases which
+have user missing values for the categorical variables should be omitted
+from the calculation.
+