vif_gee_crt: Variance inflation factor for a generalized estimating...

In sjpierce/piercer: Functions for Research and Statistical Computing

Variance inflation factor for a generalized estimating equation (GEE) analysis of a 3-level cluster randomized trial

Description

Compute the variance inflation factor applicable to a maximum likelihood analysis via a generalized estimating equation (GEE) for a three-level cluster randomized trial.

Usage

vif_gee_crt(r, rho, n_e = 1, n_s = 1)

Arguments

r	A numeric value for r: the correlation between evaluations from the same subject.
rho	A numeric value for \rho: the correlation between outcome evaluations from different subjects in the same cluster.
n_e	A numeric vector for n_e: the number of outcome evaluations per subject (level 1 observations of the binary outcome variable), which is assumed to be constant across subjects.
n_s	A numeric vector for n_s: the number of subjects (level 2 units) per cluster (i.e., the cluster size), which is assumed to be constant across clusters.

Details

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This function is useful for power analysis calculations based on the methods described in Teerenstra et. al (2010).

Value

A numeric value.

References

Teerenstra, S., Lu, B., Preisser, J. S., van Achterberg, T., & Borm, G. F. (2010). Sample size considerations for GEE analyses of three-level cluster randomized trials. Biometrics, 66(4), 1230-1237. doi:10.1111/j.1541-0420.2009.01374.x

Examples

vif_gee_crt(r = .18, rho = .02, n_e = 15, n_s = 22.1)

sjpierce/piercer documentation built on Dec. 30, 2024, 3:28 p.m.