pamm (version 0.5)

PAMM: Simulation function to assess power of mixed models

Description

Given a specific varaince-covariance structure for random effect, the function simulate different group size and assess p-values and power of random intercept and random slope

Usage

PAMM(numsim, group, repl, randompart, fixed = c(0, 1, 0), intercept = 0)

Arguments

numsim

number of simulation for each step

group

number of group (individuals). Could be specified as a vector

repl

number of replicates (observations) per group . Could be specified as a vector

randompart

vector of lenght 4 or 5, with 1) variance component of intercept (VI); 2) variance component of slope (VS); 3) residual variance (VR); 4) relation between random intercept and random slope; 5) "cor" or "cov" determine if the relation 4) betwee

fixed

vector with mean, variance and estimate of fixed effect to simulate. c(0,1,0) by default

intercept

a numeric value giving the expected intercept value. Default:0

Value

• data frame reporting estimated P-values and power with CI for random intercept and random slope

Warning

the simulation is based on a balanced data set with unrelated group

Details

P-values for random effects are estimated using a log-likelihood ratio test between two models with and without the effect. Power represent the percentage of simulations providing a significant p-value for a given random structure

References

...

See Also

EAMM, SSF, plot.PAMM

Examples

ours=PAMM(numsim=10,group=c(seq(10,50,10),100),repl=c(2,4,6),
           randompart=c(0.4,0.1,0.5,0.1),fixed=c(0,1,0.7))       
  plot(ours,"both")