Description Usage Arguments Details Value Note Author(s) References See Also Examples
View source: R/powerLogisticsReg.R
Calculating sample size for simple logistic regression with continuous predictor.
1 2 3 4 | SSizeLogisticCon(p1,
OR,
alpha = 0.05,
power = 0.8)
|
p1 |
the event rate at the mean of the continuous predictor |
OR |
Expected odds ratio. \log(OR) is the change in log odds for the difference between at the mean of X and at one SD above the mean. |
alpha |
Type I error rate. |
power |
power for testing if the odds ratio is equal to one. |
The logistic regression mode is
\log(p/(1-p)) = β_0 + β_1 X
where p=prob(Y=1), X is the continuous predictor, and \log(OR) is the the change in log odds for the difference between at the mean of X and at one SD above the mean. The sample size formula we used for testing if β_1=0 or equivalently OR=1, is Formula (1) in Hsieh et al. (1998):
n=(Z_{1-α/2} + Z_{power})^2/[ p_1 (1-p_1) [log(OR)]^2 ]
where n is the required total sample size, OR is the odds ratio to be tested, p_1 is the event rate at the mean of the predictor X, and Z_u is the u-th percentile of the standard normal distribution.
total sample size required.
The test is a two-sided test. For one-sided tests, please double the
significance level. For example, you can set alpha=0.10
to obtain one-sided test at 5% significance level.
Weiliang Qiu stwxq@channing.harvard.edu
Hsieh, FY, Bloch, DA, and Larsen, MD. A SIMPLE METHOD OF SAMPLE SIZE CALCULATION FOR LINEAR AND LOGISTIC REGRESSION. Statistics in Medicine. 1998; 17:1623-1634.
1 2 3 | ## Example in Table II Design (Balanced design (1)) of Hsieh et al. (1998 )
## the sample size is 317
SSizeLogisticCon(p1 = 0.5, OR = exp(0.405), alpha = 0.05, power = 0.95)
|
[1] 317
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