mincLogLikRatio: run log likelihood ratio tests for different mincLmer objects

In Mouse-Imaging-Centre/RMINC: Statistical Tools for Medical Imaging NetCDF (MINC) Files

run log likelihood ratio tests for different mincLmer objects

Description

Computes the log likelihood ratio of 2 or more voxel-wise lmer calls, testing the hypothesis that the more complex model better fits the data. Note that it requires the mixed effects to have been fitted with maximum likelihood, and not restricted maximum likelihood; in other words, if you want to use these log likelihood tests, make sure to specify REML=FALSE in mincLmer.

Usage

mincLogLikRatio(...)

Arguments

...	Two or more mincLmer objects

Value

the voxel wise log likelihood test. Will have a number of columns corresponding to the number of inputs -1. Note that it resorts the inputs from lowest to highest degrees of freedom

See Also

lmer and mincLmer for description of lmer and mincLmer. mincFDR for using the False Discovery Rate to correct for multiple comparisons, and mincWriteVolume for outputting the values to MINC files.

Examples

## Not run: 
m1 <- mincLmer(filenames ~ age + sex + (age|id), data=gf, mask="mask.mnc", REML=F)
m2 <- mincLmer(filenames ~ age + I(age^2) + sex + (age|id), 
               data=gf, mask="mask.mnc", REML=F)
m3 <- mincLmer(filenames ~ age + I(age^2) + I(age^3) + sex + (age|id), 
               data=gf, mask="mask.mnc", REML=F)
llr <- mincLogLikRatio(m1, m2, m3)
mincFDR(llr)
mincWriteVolume(llr, "m2vsm3.mnc", "m3")

## End(Not run)

Mouse-Imaging-Centre/RMINC documentation built on Nov. 12, 2022, 1:50 p.m.