fitnocorr: Run mixed-effects model using ('lmer')

In dalejbarr/simgen: Monte Carlo Simulations of Simultaneous Generalization

Description

Fits a LMEM with random slopes and random intercepts but no random correlations (one-factor design only).

Usage

fitnocorr(mcr.data, wsbi = FALSE)

Arguments

mcr.data	A dataframe formatted as described in mkDf.
wsbi	Whether the design is between-items (TRUE) or within-items (FALSE).

Value

A vector with elements:

fm	Code for the model that converged: (1) dropped one slope; (2) dropped two slopes; (3) main model did not converge; (4) comparision model for likelihood ratio test did not converge.
t	t-statistic for the treatment effect
chi	chi-square statistic for the likelihood ratio test (1 df)
pt	p-value for the t-statistic (normal distribution)
pchi	p-value for the chi-square statistic

See Also

mkDf, fitlmer.mcmc

Examples

nmc <- 10
pmx <- cbind(randParams(genParamRanges(), nmc, 1001), seed=mkSeeds(nmc, 1001))

# between-items dataset
x.bi <- mkDf(nsubj=24, nitem=24, mcr.params=pmx[1,], wsbi=TRUE)

# within-items dataset
x.wi <- mkDf(nsubj=24, nitem=24, mcr.params=pmx[1,], wsbi=FALSE)

# maximal model
fitnocorr(x.bi, wsbi=TRUE)
fitnocorr(x.wi, wsbi=FALSE)

dalejbarr/simgen documentation built on May 14, 2019, 3:32 p.m.