/usr/share/octave/packages/statistics-1.3.0/repanova.m is in octave-statistics 1.3.0-4.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | ## 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
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