Linear model analyses: meta-regression
This procedure calculates linear meta-regressions, with their statistical significance based on Monte Carlo randomizations. You can specify a filter for subgroup analyses. The following estimates are returned:
- 0: intercept, i.e. prediction from the minimum value of the regressor (which is scaled to 0).
- 1: prediction from the maximum value of the regressor (which is scaled to 1).
- 1m0: slope, i.e. difference between both predictions above.
Variables are automatically scaled to have values between 0 and 1.
Please be aware that meta-regressions should be generally understood as exploratory and their threshold should be lower than the usual threshold.
To calculate a meta-regression
Press the button [Linear model] and [Meta-regression] or [Multiple meta-regression]
Select [Linear model] in the Statistics menu, to open the following dialog:
Command-line and batch usage
lm regressor, filter
AdultsAgeEffect = lm age, adults
The p = 0.005 thresholds obtained after each randomization are saved in a text file called (name_of_the_regression)_z.htm, e.g. MyRegression_1_z.htm. This is useful for studying the stability of the threshold.
(original algorithms): Radua J and Mataix-Cols D. Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. Br J Psychiatry 2009; 195:393-402. .