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help for ^wsanova^                                      (STB-47: sg103)
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within subjects ANOVA, with zero or more between subjects factors
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   ^wsanova^ yvar wfact [weight] [^if^ exp] [^in^ range] , ^id(^svar^)^
               [^bet^ween^(^beffects^) wo^nly^(^weffects^) eps^ilon ^nom^atr ]

^aweights^ and ^fweights^ are allowed; see help @weights@.


Description
-----------

^wsanova^ performs a within subjects (repeated measures) analysis of variance for
the response variable yvar classified by the within subjects factor wfact.  The
subjects are identified by the variable svar, and may be classified by one or
more between subjects factors. Within subjects F tests can be adjusted for lack
of sphericity using the Greenhouse-Geisser or Huynh-Feldt correction factor.


Options
-------

^id(svar)^ declares that the variable svar uniquely identifies each subject to be
    used in the analysis.  [Not optional.]

^between(beffects)^ supplies a list of between subjects factors that classify the
    subjects, along with zero or more of their interactions.  Up to 7 such fac-
    tors can be used; their interactions must be explicitly requested.

^wonly(weffects)^ selects within subjects effects that should be included in the
    analysis.  By default, wfact and all of its interactions with the elements
    of the ^between^ option are included.

^epsilon^ requests that p-values for within subjects F-tests be adjusted for lack
    of sphericity using the Greenhouse-Geisser and Huynh-Feldt adjustment fac-
    tors.  [Requires that yvar be non-missing for each subject.]

^nomatr^ discards covariance and cell mean matrices at exit.  The ^epsilon^ option
    creates a (pooled) covariance matrix WSAoV_ and a matrix WSAov_ of marginal
    means of yvar across levels of wfact.  In addition, when there are between
    subjects factors epsilon creates a cell means matrix and a within group co-
    variance matrix for each distinct group of subjects; these matrices will be
    named WSAov1 WSAoV1, WSAov2 WSAoV2, ... .  By default, all these matrices
    are left in memory; ^nomatr^ erases each of them before wsanova exits.


Examples
--------

 . ^wsanova lhist time, id(dog)^
 . ^predict resid, res^
   (One-way repeated measures ANOVA; save residuals in resid)

 . ^wsanova rtime trial, id(subj) between(age) epsilon^
   (Split-plot ANOVA, with subjects grouped by levels of age; adjust trial and
   age*trial F-tests for lack of sphericity)

 . ^wsanova rtime trial, id(subj) bet(age sex age*sex)^
   (Traditional analysis of a "two between, one within" design:  age, sex, and
   age*sex as between effects; trial, trial*age, trial*sex, trial*age*sex as
   within effects; assume sphericity)

 . ^wsanova rtime trial, id(subj) bet(age sex) wonly(trial) eps nomatr^
   (Main effects only version of the last example; adjust the trial F-test for
   lack of sphericity, and discard the matrices used)


Author
------

       John R. Gleason
       Syracuse University
       Syracuse NY, USA
       loesljrg@@ican.net


Also see
--------

    STB:  STB-47 sg103
 Manual:  [R] anova; [R] predict
On-line:  ^help^ for @anova@, @predict@