mixed.eff.params: Calculation of variance in Poisson mixed model setting.

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/simulationEngines.R

Description

This function is designed to calculate the overall variance for cluster-level outcomes in a mixedeffect Poisson model. Conditional expectation calculations are implemented.

Usage

1
mixed.eff.params(pi0, btw.clust.var, Tk)

Arguments

pi0

the baseline cluster-level mean on the scale of the link function

btw.clust.var

the between-cluster-variance

Tk

the at-risk time for each cluster

Details

The mixed.eff.params() function is used by the hayes.power.poisson() function to compute the effective coefficient of variation, or k, for a particular study design.

Value

A numeric vector with the following three named elements, in order: ["expectation"] the overall mean of cluster-level outcomes, ["variance"] the overall variance of cluster-level outcomes, ["hayes.k"] the estimated coefficient of variation.

Author(s)

Nicholas G. Reich

References

Reich NG et al. PLoS ONE. Empirical Power and Sample Size Calculations for Cluster-Randomized and Cluster-Randomized Crossover Studies. 2012. http://ow.ly/fEn39

Hayes RJ and Bennett S. Int J Epi. Simple sample size calculation for cluster-randomized trials. 1999. http://www.ncbi.nlm.nih.gov/pubmed/10342698

See Also

hayes.power.poisson

Examples

1
mixed.eff.params(pi0=log(1), btw.clust.var=.5, Tk=100)

clusterPower documentation built on Sept. 5, 2017, 9:06 a.m.