# Logpower.bin: Sample size and power for logistic regression with a binary... In aabydava/regpoweR: Power and Sample Size Calculation for Logistic and Poisson Regression

## Description

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

## Usage

 ```1 2``` ```Logpower.bin(alpha = NULL, power = NULL, P0 = NULL, OR = NULL, R = 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) `P0` baseline probability that Y=1 `OR` odds ratio (odds(Y=1|X=1) / odds(Y=1|X=0)) `R` proportion of sample (N) with X1=1 `N` sample size

## Value

Return one of the following parameters

`alpha`, `power`, `OR`, `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`, `P0`, `OR`, `N` can be input as either single values or vectors. Only one parameter can be input as a vector.

## Author(s)

David Aaby <[email protected]>

## References

Hsieh, F.Y., Block, D.A., and Larsen, M.D. 1998. A Simple Method of Sample Size Calculation for Linear and Logistic Regression, Statistics in Medicine, Volume 17, pages 1623-1634.

## Examples

 ```1 2 3 4 5``` ```Logpower.bin(alpha=0.05, power=.90, P0=0.07, OR=1.5, R=.50) #outputs N Logpower.bin(alpha=0.05, power=.90, P0=0.07, OR=c(1.5,2.0), R=.50) #outputs a vector of Ns Logpower.bin(alpha=0.05, power=.90, P0=0.07, R=.50, N=3326) #outputs OR Logpower.bin(power=.90, P0=0.07, OR=1.5, R=.50, N=3326) #outputs alpha Logpower.bin(alpha=0.05, P0=0.07, OR=1.5, R=.50, N=3326) #outputs beta ```

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