# SDM calculations

## 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.

### Notes

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]

*or:*

Select [Linear model] in the *Statistics* menu, to open the following dialog:

### Command-line and batch usage

lm *regressor*, *filter*

*Example:*

AdultsAgeEffect = lm age, adults

### Log

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.

### References

(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.
.