[Octave-cvsupdate] SF.net SVN: octave:[8423] trunk/octave-forge/main/statistics/inst/repanova. m

[<ha...@us...>]

Revision: 8423
          http://octave.svn.sourceforge.net/octave/?rev=8423&view=rev
Author:   hauberg
Date:     2011-07-29 12:33:53 +0000 (Fri, 29 Jul 2011)

Log Message:
-----------
New function (repanova) from Kyle Winfree

Added Paths:
-----------
    trunk/octave-forge/main/statistics/inst/repanova.m

Added: trunk/octave-forge/main/statistics/inst/repanova.m
===================================================================
--- trunk/octave-forge/main/statistics/inst/repanova.m	                        (rev 0)
+++ trunk/octave-forge/main/statistics/inst/repanova.m	2011-07-29 12:33:53 UTC (rev 8423)
@@ -0,0 +1,96 @@
+## Copyright (C) 2011   Kyle Winfree   <kyl...@gm...>
+##
+## This program is free software; you can redistribute it and/or modify
+## it under the terms of the GNU General Public License as published by
+## the Free Software Foundation; either version 3 of the License, or
+## (at your option) any later version.
+##
+## This program is distributed in the hope that it will be useful,
+## but WITHOUT ANY WARRANTY; without even the implied warranty of
+## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+## GNU General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with this program; if not, see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {[@var{pval}, @var{table}, @var{st}] =} repanova (@var{X}, @var{cond})
+## @deftypefnx {Function File} {[@var{pval}, @var{table}, @var{st}] =} repanova (@var{X}, @var{cond}, ['string' | 'cell'])
+## Perform a repeated measures analysis of variance (Repeated ANOVA).
+## X is formated such that each row is a subject and each column is a condition.
+##
+## condition is typically a point in time, say t=1 then t=2, etc
+## condition can also be thought of as groups.
+##
+## The optional flag can be either 'cell' or 'string' and reflects
+## the format of the table returned.  Cell is the default.
+##
+## NaNs are ignored using nanmean and nanstd.
+## 
+## This fuction does not currently support multiple columns of the same
+## condition!
+## @end deftypefn
+
+function [p, table, st] = repanova(varargin)
+
+switch nargin
+     case 0
+	  error('Too few inputs.');
+     case 1
+	  error('Too few inputs.');
+     case 2
+	  X = varargin{1};
+	  condition = varargin{2};
+	  option = 'cell';
+     case 3
+	  X = varargin{1};
+	  condition = varargin{2};
+	  option = varargin{3};
+     otherwise
+	  error('Too many inputs.');
+end
+     % Find the means of the subjects and measures, ignoring any NaNs
+     u_subjects = nanmean(X,2);
+     u_measures = nanmean(X,1);
+     u_grand = nansum(nansum(X)) / (size(X,1) * size(X,2));
+     % Differences between rows will be reflected in SS subjects, differences
+     % between columns will be reflected in SS_within subjects.
+     N = size(X,1); % number of subjects
+     J = size(X,2); % number of samples per subject
+     SS_measures = N * nansum((u_measures - u_grand).^2);
+     SS_subjects = J * nansum((u_subjects - u_grand).^2);
+     SS_total = nansum(nansum((X - u_grand).^2));
+     SS_error = SS_total - SS_measures - SS_subjects;
+     df_measures = J - 1;
+     df_subjects = N - 1;
+     df_grand = (N*J) - 1;
+     df_error = df_grand - df_measures - df_subjects;
+     MS_measures = SS_measures / df_measures;
+     MS_subjects = SS_subjects / df_subjects;
+     MS_error = SS_error / df_error; % variation expected as a result of sampling error alone
+     F = MS_measures / MS_error;
+     p = 1 - fcdf(F,df_measures,df_subjects); % Probability of F given equal means.
+
+     if strcmp(option, 'string')
+	  table  = [sprintf('\nSource\tSS\tdf\tMS\tF\tProb > F'), ...
+		    sprintf('\nSubject\t%g\t%i\t%g', SS_subjects, df_subjects, MS_subjects), ...
+		    sprintf('\nMeasure\t%g\t%i\t%g\t%g\t%g', SS_measures, df_measures, MS_measures, F, p), ...
+		    sprintf('\nError\t%g\t%i\t%g', SS_error, df_error, MS_error), ...
+		    sprintf('\n')];
+     else
+	  table  = {'Source', 'Partial SS', 'df', 'MS', 'F', 'Prob > F'; ...
+		    'Subject', SS_subjects, df_subjects, MS_subjects, '', ''; ...
+		    'Measure', SS_measures, df_measures, MS_measures, F, p};
+     end
+
+     st.gnames = condition'; % this is the same struct format used in anova1
+     st.n = repmat(N, 1, J);
+     st.source = 'anova1'; % it cannot be assumed that 'repanova' is a supported source for multcompare
+     st.means = u_measures;
+     st.df = df_error;
+     st.s = sqrt(MS_error);
+end
+
+% This function was created with guidance from the following websites:
+% http://courses.washington.edu/stat217/rmANOVA.html
+% http://grants.hhp.coe.uh.edu/doconnor/PEP6305/Topic%20010%20Repeated%20Measures.htm


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