--- /dev/null
+## Copyright (C) 2011 Kyle Winfree <kyle.winfree@gmail.com>
+##
+## 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
+ X = varargin{1};
+ for c = 1:size(X, 2)
+ condition{c} = ['time', num2str(c)];
+ end
+ option = 'cell';
+ 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_error); % 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