Sorry for the inconvenience but I posted this message last week, but I did not receive any answer. I really need to keep going on with my analyses.
I have runned the following command line:
mri_glmfit --surf PLI_MCI_sample7_avg lh --C /root/trabajo/freesurfer/subjects/PLI_MCI_sample7_avg/stats_MRI_PET_Biomarkers/glm_files/contrast_withinE4_neg.mat --fsgd /root/trabajo/freesurfer/subjects/PLI_MCI_sample7_avg/stats_MRI_PET_Biomarkers/glm_files/lh.cortex_AVGthickness_APOB_fsgd.txt dods --label /root/trabajo/freesurfer/subjects/PLI_MCI_sample7_avg/label/lh.cortex.label --y /root/trabajo/freesurfer/subjects/PLI_MCI_sample7_avg/stats_MRI_PET_Biomarkers/lh.thickness_s12mm.mgh --no-prune --glmdir /root/trabajo/freesurfer/subjects/PLI_MCI_sample7_avg/stats_MRI_PET_Biomarkers/resultsthickness_cortex_s12mm_BiomrkrsWithin/lh.cortex_AVGthickness_APOB_contrast_withinE4_neg/
which is always prompts the following error:
--------------------------------
ERROR: matrix is ill-conditioned or badly scaled, condno = 1.75146e+07
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Possible problem with experimental design
I'm sending attached the fsgd.txt and contras.mat files used in case you need them
Does anyone knows what's wrong with my design?
Many thanks in advanced,
Gabriel.
contrast_withinE4_neg.mat
Description: Binary data
GroupDescriptorFile 1 Title PVEc-PET_with_MRI in sig_clusters of MC_3000 Class E4female Class E4male Class noE4female Class noE4male variables zAge zAPOB zlh.cortex_AVGthickness Input mci_01_year1 noE4male -0.025380 -0.495746 -0.569553 Input mci_02_year1 noE4male 0.416237 -0.163064 -1.388804 Input mci_04_year1 noE4female -0.466997 -1.018533 1.324541 Input mci_10_year1 noE4male -0.319792 -1.351215 0.286936 Input mci_11_year1 noE4female 0.563442 -0.400694 -0.384206 Input mci_14_year1 noE4male -0.466997 -0.281879 0.611082 Input mci_15_year1 noE4female 1.152265 -0.567035 0.446893 Input mci_16_year1 noE4male 0.857854 0.549827 -1.563149 Input mci_20_year1 noE4male -0.614203 -1.066059 -0.254717 Input mci_23_year1 noE4male 1.299471 -0.780902 -0.043134 Input mci_25_year1 noE4male -0.761409 -0.899718 0.469744 Input mci_33_year1 noE4male -0.908614 0.858747 0.584846 Input mci_36_year1 noE4male -0.025380 2.260766 -0.997798 Input mci_38_year1 noE4male -2.822288 2.759790 1.354163 Input mci_39_year1 noE4male -1.350231 2.569685 0.621238 Input mci_06_year1 E4female -0.172586 -0.234353 -0.633028 Input mci_07_year1 E4male -1.350231 -0.139301 -0.126075 Input mci_08_year1 E4female -0.025380 0.383486 -1.171297 Input mci_09_year1 E4female 0.857854 -0.234353 -0.370665 Input mci_13_year1 E4male 0.121825 -0.495746 0.904760 Input mci_17_year1 E4male -0.466997 -0.044248 -0.776059 Input mci_18_year1 E4female 1.005059 -0.163064 -0.820915 Input mci_19_year1 E4male 1.152265 0.074567 -2.081952 Input mci_21_year1 E4female 0.121825 -0.091774 1.423562 Input mci_27_year1 E4female -1.350231 -0.543272 2.172568 Input mci_29_year1 E4male 1.888294 0.240908 0.683020 Input mci_35_year1 E4male 0.710648 -0.567035 1.014783 Input mci_41_year1 E4female 0.269031 0.169619 -0.510310 Input mci_42_year1 E4male 0.710648 -0.329405 -0.206476
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