Poissonpower.bin: Sample size and power for Poisson regression.

In aabydava/regpoweR: Power and Sample Size Calculation for Logistic and Poisson Regression

Description

Calculating power/sample size for simple Poisson regression with a binary predictor. The function solves for one of the following: alpha, power, incidence rate ratio, N.

Usage

Poissonpower.bin(alpha = NULL, power = NULL, exp.B0 = NULL,
  exp.B1 = NULL, muT = 1, phi = 1, R2 = 0, pi.x1 = NULL, N = NULL)

Arguments

alpha	type I error rate. Can range from 0 to 1 (typically 0.05)
power	1 - Pr(type II error) Can range from 0 to 1 (typically 0.80)
exp.B0	Baseline rate. The response rate when all covariates have a value of 0
exp.B1	Incidence rate ratio (IRR) comparing X=1 to X=0.
muT	Mean exposure time
phi	Measure of over-dispersion
R2	The square of the multiple correlation coefficient when the covariate of interst is regressed on the other covariates.
pi.x1	proportion of sample (N) with X1=1
N	sample size

Value

Return one of the following parameters

alpha, power, exp.B1, N

Note

The test is a two-sided test. For one-sided tests, double the significance level. For example, you can set alpha=0.10 to obtain one-sided test at 0.05 significance level.

alpha, power, exp.B0, exp.B1, pi.x1, N can be input as either single values or vectors. Only one parameter can be input as a vector.

Author(s)

David Aaby <[e-mail]>

References

Signorini, D. 1991. Sample Size for Poisson Regression, Biometrika (1991), 78, 2, pages 446-450..

Examples

Poissonpower.bin(alpha=NULL, power=.80, exp.B0=.85, exp.B1=1.3, muT=1, phi=1,R2=0, pi.x1=.5, N=406)
Poissonpower.bin(alpha=NULL, power=.80, exp.B0=.85, exp.B1=1.3, muT=1, phi=1, R2=0, pi.x1=.5, N=406)
Poissonpower.bin(alpha=.05, power=.80, exp.B0=.85, exp.B1=1.3, muT=1, phi=1, R2=0, pi.x1=.5, N=NULL)
Poissonpower.bin(alpha=.05, power=.80, exp.B0=.85, exp.B1=NULL, muT=1, phi=1, R2=0, pi.x1=.5, N=406)

aabydava/regpoweR documentation built on May 10, 2019, 9:59 a.m.