Computed theoretical power for N=100 and N=200 scenarios

Modules/ado/plus/w/wsanova.hlp

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+.-
+help for ^wsanova^                                      (STB-47: sg103)
+.-
+
+within subjects ANOVA, with zero or more between subjects factors
+-----------------------------------------------------------------
+
+   ^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@