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stroop_bayesreg.m
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clear
clc
%bayes_reg tests
%J Ruffle [email protected]
%%
%configure paths
addpath('/home/jruffle/Documents/MATLAB/bayesreg');
addpath('/home/jruffle/Documents/MATLAB/bayesreg/examples');
nsamples = 1e5;
burnin = 1e5;
prior = 'ridge';
%{'g','ridge','lasso','horseshoe','horseshoe+','logt'}
dist = 'gaussian';
%{'gaussian','laplace','t','binomial','poisson','geometric'}
counter=1;
model_results = table;
%% cingulate parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter=counter+1;
%% stroop parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
% change prior
prior = 'g'
%% cingulate parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter=counter+1;
%% stroop parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% change prior
prior = 'hs'
%% cingulate parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter=counter+1;
%% stroop parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% change prior
prior = 'hs+'
%% cingulate parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter=counter+1;
%% stroop parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_pro';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% change prior
prior = 'lasso'
%% cingulate parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter=counter+1;
%% stroop parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_bin';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% cingulate parcellation volume
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_cin_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_str_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% all parcellation
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
model_results.model(counter,:) = 'df_all_vol';
model_results.prior(counter,1:length(prior)) = prior;
model_results.r2(counter,:) = retval.modelstats.r2;
model_results.waic(counter,:) = retval.modelstats.waic;
counter = counter+1;
%% save results
writetable(model_results,'/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/bayes_reg.csv');
model_results
%% final full model with coefficents
prior = 'g';
%dist = 'geometric';
dist = 'gaussian';
%proportionate
%df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_prop.csv','ReadVariableNames',true,'ReadRowNames',false);
%with categoricals
%binary only
%df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df.csv','ReadVariableNames',true,'ReadRowNames',false);
%volumetric
df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume.csv','ReadVariableNames',true,'ReadRowNames',false);
%volumetric just l frontal
%df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_stroop.csv','ReadVariableNames',true,'ReadRowNames',false);
%volumetric just l frontal
%df = readtable('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/df_volume_cingulate.csv','ReadVariableNames',true,'ReadRowNames',false);
df = removevars(df,{'Var1'});
y = df(:,["Stroop_words_correct"]);
X = removevars(df,{'Stroop_words_correct'});
varnames = X.Properties.VariableNames;
catvars = 1:width(X);
X = table2array(X);
y = table2array(y);
%no categoricals
[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'sortrank',true);
%with categoricals
%[beta, beta0, retval] = bayesreg(X,y,dist,prior,'nsamples',nsamples,'burnin',burnin,'thin',5,'displayor',true,'varnames',varnames,'display',true,'catvars',catvars,'sortrank',true);
diary on
diary('/home/jruffle/OneDrive/PhD/Stroop_GLDM/11_CORTEX_PAPER_analysis/results/bayes_reg_posteriors.txt')
br_summary(beta,beta0,retval);
diary off
% mean_coeff = retval.muB;
% coef_names = retval.Xstats.varnames(1:length(retval.Xstats.varnames)-1);
% tstats = retval.tStat;
% ranks = retval.varranks;