Check this box to estimate the covariance parameters, for the K matrix and/or additional random effects that can be specified, in a model including all non-genetic effects, and use these estimates in the association testing.
Having these parameters fixed eliminates the need for the covariance parameters to be re-computed for every SNP mixed model fit and saves computation time. This option is based on the population parameters previously determined approach (P3D) that was proposed concurrently with the optimized K matrix compression method in Zhang et al. (2010)1.
You should not check this option if you are already using the PARMS statement generated by K Matrix Compression.
Note: This option is ignored when no K Matrix Square Root Variables and no Additional Fixed Effects are specified.
Note: You cannot select this option when either SATTERTHWAITE or KENWARDROGER is selected as the Denominator Degrees of Freedom Method (on the Model Variables tab).
Zhang, Z., E. Erzoz, et al. (2010). Mixed linear model approach adapted for genome-wide association studies. Nature Genetics 42: 355-360.