sr.mem: Implementation of SR-MEM: scale-reliant mixed effects models.

In ALDEx3: Linear Models for Sequence Count Data

Implementation of SR-MEM: scale-reliant mixed effects models.

Description

Implementation of SR-MEM: scale-reliant mixed effects models.

Usage

sr.mem(logW, formula, data, n.cores, method, mem.args)

Arguments

logW	a numeric array (N x D X S) where D is the number of taxa, N is the number of samples, and S is the number of posterior samples
formula	an lme4 formula with fixed and random effects for lmer
data	A data.frame with the random and fixed effects items in formula
n.cores	The number of cores for parallelization. If n.cores=1, no parallelization is used
method	The mem method to use: either nlme or lme4
mem.args	Additional arguments including random or correlation

Value

A list of (P x D x S)-arrays with the fixed effect point estimates, the standard errors, degrees of freedom and the lower and upper p-values for each coefficient (P), of each model fit to each taxa (D) and each posterior sample (S) and a (Pr x D x S)-array with (Pr) random effects.

Author(s)

Kyle McGovern

ALDEx3 documentation built on Oct. 20, 2026, 1:07 a.m.