Home > marsbar > @mardo_5 > private > pr_stat_compute.m

pr_stat_compute

PURPOSE ^

private function to compute statistics for SPM2 design

SYNOPSIS ^

function [con,stat,Ps,Pc] = pr_stat_compute(SPM,Ic)

DESCRIPTION ^

 private function to compute statistics for SPM2 design
 FORMAT [con stat Ps Pc] = pr_stat_compute(SPM,Ic)
 
 Input
 SPM       - SPM design structure
 Ic        - indices into contrast structure (xCon in SPM)

 Output
 con       - contrast value (ess for F test)
 stat      - statistic value
 Ps        - uncorrected p value
 Pc        - P value Bonferroni corrected for number of columns analyzed

 Based on:
 @(#)spm_contrasts.m    2.3 Andrew Holmes, Karl Friston & Jean-Baptiste Poline 02/12/30

 $Id: pr_stat_compute.m 214 2004-01-22 20:23:58Z matthewbrett $

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [con,stat,Ps,Pc] = pr_stat_compute(SPM,Ic)
0002 % private function to compute statistics for SPM2 design
0003 % FORMAT [con stat Ps Pc] = pr_stat_compute(SPM,Ic)
0004 %
0005 % Input
0006 % SPM       - SPM design structure
0007 % Ic        - indices into contrast structure (xCon in SPM)
0008 %
0009 % Output
0010 % con       - contrast value (ess for F test)
0011 % stat      - statistic value
0012 % Ps        - uncorrected p value
0013 % Pc        - P value Bonferroni corrected for number of columns analyzed
0014 %
0015 % Based on:
0016 % @(#)spm_contrasts.m    2.3 Andrew Holmes, Karl Friston & Jean-Baptiste Poline 02/12/30
0017 %
0018 % $Id: pr_stat_compute.m 214 2004-01-22 20:23:58Z matthewbrett $
0019 
0020 %-Get contrast definitions (if available)
0021 %-----------------------------------------------------------------------
0022 try
0023     xCon  = SPM.xCon;
0024 catch
0025     xCon  = [];
0026 end
0027 
0028 %-set all contrasts by default
0029 %-----------------------------------------------------------------------
0030 if nargin < 2
0031   Ic    = 1:length(xCon);
0032 end
0033 if any(Ic > length(xCon))
0034   error('Indices too large for contrast structure');
0035 end
0036 
0037 % OLS estimators and error variance estimate
0038 %----------------------------------------------------------------
0039 betas = SPM.betas;
0040 Hp    = SPM.ResidualMS;
0041 
0042 %-Compute contrast and statistic parameters
0043 %=======================================================================
0044 df = [NaN SPM.xX.erdf];
0045 for i = 1:length(Ic)
0046 
0047   %-Canonicalise contrast structure with required fields
0048   %-------------------------------------------------------------------
0049   ic  = Ic(i);
0050   X1o           = spm_FcUtil('X1o',xCon(ic),SPM.xX.xKXs);
0051   [trMV,trMVMV] = spm_SpUtil('trMV',X1o,SPM.xX.V);
0052   df(1)         = trMV^2/trMVMV; % eidf
0053   
0054   switch(xCon(ic).STAT)
0055     
0056    case {'T'} %-Implement contrast as sum of betas
0057     
0058     con(i,:)   = xCon(ic).c'*betas;
0059     VcB        = xCon(ic).c'*SPM.xX.Bcov*xCon(ic).c; 
0060     stat(i,:)  = con(i,:)./sqrt(Hp*VcB);
0061     Ps(i,:)    = 1 - spm_Tcdf(stat(i,:),df(2));
0062 
0063    case 'F'  %-Implement ESS
0064     
0065     %-Residual (in parameter space) forming mtx
0066     %-----------------------------------------------------------
0067     h          = spm_FcUtil('Hsqr',xCon(ic),SPM.xX.xKXs);
0068     con(i,:)   = sum((h * betas).^2, 1);
0069     stat(i,:)  = con(i,:) ./ Hp / trMV;
0070     Ps(i,:)    = (1 - spm_Fcdf(stat(i,:),df));
0071 
0072    otherwise
0073     %---------------------------------------------------------------
0074     error(['unknown STAT "',xCon(ic).STAT,'"'])
0075     
0076   end % (switch(xCon...)
0077 end
0078 
0079 % Compute corrected Bonferroni (corrected for number of regions)
0080 n  = size(betas, 2);
0081 Pc = 1-(1-Ps).^n;
0082

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