% -*- texinfo -*- % @deftypefn {Function File} {[@var{pval}, @var{f}, @var{df_b}, @var{df_e}] =} anovan (@var{data}, @var{grps}) % @deftypefnx {Function File} {[@var{pval}, @var{f}, @var{df_b}, @var{df_e}] =} anovan (@var{data}, @var{grps}, 'param1', @var{value1}) % Perform a multi-way analysis of variance (ANOVA). The goal is to test % whether the population means of data taken from @var{k} different % groups are all equal. % % Data is a single vector @var{data} with groups specified by % a corresponding matrix of group labels @var{grps}, where @var{grps} % has the same number of rows as @var{data}. For example, if % @var{data} = [1.1;1.2]; @var{grps}= [1,2,1; 1,5,2]; % then data point 1.1 was measured under conditions 1,2,1 and % data point 1.2 was measured under conditions 1,5,2. % Note that groups do not need to be sequentially numbered. % % By default, a 'linear' model is used, computing the N main effects % with no interactions. this may be modified by param 'model' % % p= anovan(data,groups, 'model', modeltype) % - modeltype = 'linear': compute N main effects % - modeltype = 'interaction': compute N effects and % N*(N-1) two-factor interactions % - modeltype = 'full': compute interactions at all levels % % Under the null of constant means, the statistic @var{f} follows an F % distribution with @var{df_b} and @var{df_e} degrees of freedom. % % The p-value (1 minus the CDF of this distribution at @var{f}) is % returned in @var{pval}. % % If no output argument is given, the standard one-way ANOVA table is % printed. % % BUG: DFE is incorrect for modeltypes ~= full % @end deftypefn

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