Hi PLS experts,
I'm having a bit of trouble interpreting my brain score values. I ran a non-rotated PLS with only one condition on some structural MRI data. I have two groups and have thus specified a contrast to pull apart any group differences. My contrast datamat consists of one column, two rows, -1 for group A and 1 for group B. When I run the analysis and print my brain scores, I have all positive values, despite my salience values being both positive and negative... If brain scores are derived by multiplying the raw brain data with the saliences, shouldn't at least a subset of my bs values be negative?
Thanks in advance for the help!
The brain scores are the dot-product of the saliences and data (sum of the cross-product), so it's hard to predict the sign of a score becuase it will depend on the relative number of positive and negatives saliences and the data (voxel) values themselves
The brain scores are the dot-product of the saliences and data (sum of the cross-product), so it's hard to predict the sign of a score becuase it will depend on the relative number of positive and negatives saliences and the data (voxel) values themselves
Thanks, Randy. I have more positive salience values than negative and even the means of the raw data between the two groups are very close together, which supports my non-significant LV. Could these two reasons be why my brain scores are all positive?
Thanks, Randy. I have more positive salience values than negative and even the means of the raw data between the two groups are very close together, which supports my non-significant LV. Could these two reasons be why my brain scores are all positive?
Probably that is the reason, yes. :)
Probably that is the reason, yes. :)
Thanks, Randy. So am I correct to interpret my salience values in this case as ROIs that more (+ salience value) or less (- salience value) contribute to the non-significant difference between the groups?
Thanks, Randy. So am I correct to interpret my salience values in this case as ROIs that more (+ salience value) or less (- salience value) contribute to the non-significant difference between the groups?
Think of it this way. The saliences are similar to regression coefficients and the bootstrap ratios are like a t-value for each. If your design lv has positive weights for group1 and negative for group 2, then positive weights for the brain would indicate regions that are higher in group1 and the negative would be lower in group 1 all relative to group 2. The reason for the non-significant LV is that these differences, considered across the brain, are not high enough to permit significant differentiation of the two groups.
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