Submitted by Patrizia on Tue, 05/29/2018 - 09:40 Dear Chao-Gan,in SPM, when a correlation analysis in performed, it is necessary to specify the study design (eg. multiple regression).I am wondering what is the model used in DPABI->Statistical Analysis->Correlation Analysis.Thank you,P. It's simply Pearson It's simply Pearson correlation coefficient.If you added covariates, then it's partial correlation. Log in or register to post comments Thank you for your answer. Thank you for your answer. Yes, I have included two covariates.Just to be clear, does the correlation implemented in DPARSFA use the GLM function of SPM? In any case, is specified any model? Clearly some modeling must have been done but the methods description does not make it apparent what it was. Thanks. Log in or register to post comments You can look at y_Correlation You can look at y_Correlation_Image.m[b_OLS_brain, t_OLS_brain, TTest1_T, r_OLS_brain, Header] = y_GroupAnalysis_Image(DependentVolume,Regressors,OutputName,MaskFile,CovariateVolume,Contrast,'T',0,Header); Df_E = size(Regressors,1) - size(Contrast,2); rCorr = TTest1_T./(sqrt(Df_E+TTest1_T.*TTest1_T));It used a regression model, and then convert the T value to r value. Log in or register to post comments Forums DPABI/DPABISurf/DPARSF Log in or register to post comments
It's simply Pearson It's simply Pearson correlation coefficient.If you added covariates, then it's partial correlation. Log in or register to post comments
Thank you for your answer. Thank you for your answer. Yes, I have included two covariates.Just to be clear, does the correlation implemented in DPARSFA use the GLM function of SPM? In any case, is specified any model? Clearly some modeling must have been done but the methods description does not make it apparent what it was. Thanks. Log in or register to post comments
You can look at y_Correlation You can look at y_Correlation_Image.m[b_OLS_brain, t_OLS_brain, TTest1_T, r_OLS_brain, Header] = y_GroupAnalysis_Image(DependentVolume,Regressors,OutputName,MaskFile,CovariateVolume,Contrast,'T',0,Header); Df_E = size(Regressors,1) - size(Contrast,2); rCorr = TTest1_T./(sqrt(Df_E+TTest1_T.*TTest1_T));It used a regression model, and then convert the T value to r value. Log in or register to post comments
It's simply Pearson
It's simply Pearson correlation coefficient.
If you added covariates, then it's partial correlation.
Thank you for your answer.
Thank you for your answer.
Yes, I have included two covariates.
Just to be clear, does the correlation implemented in DPARSFA use the GLM function of SPM?
In any case, is specified any model? Clearly some modeling must have been done but the methods description does not make it apparent what it was.
Thanks.
You can look at y_Correlation
You can look at y_Correlation_Image.m
[b_OLS_brain, t_OLS_brain, TTest1_T, r_OLS_brain, Header] = y_GroupAnalysis_Image(DependentVolume,Regressors,OutputName,MaskFile,CovariateVolume,Contrast,'T',0,Header);
Df_E = size(Regressors,1) - size(Contrast,2);
rCorr = TTest1_T./(sqrt(Df_E+TTest1_T.*TTest1_T));
It used a regression model, and then convert the T value to r value.