ssizeEpiCont.default {powerSurvEpi} | R Documentation |
Sample Size Calculation for Cox Proportional Hazards Regression with Nonbinary Covariates for Epidemiological Studies
Description
Sample size calculation for Cox proportional hazards regression with nonbinary covariates for Epidemiological Studies.
Usage
ssizeEpiCont.default(power,
theta,
sigma2,
psi,
rho2,
alpha = 0.05)
Arguments
power |
numeric. postulated power. |
theta |
numeric. postulated hazard ratio. |
sigma2 |
numeric. variance of the covariate of interest. |
psi |
numeric. proportion of subjects died of the disease of interest. |
rho2 |
numeric. square of the multiple correlation coefficient between the covariate of interest and other covariates. |
alpha |
numeric. type I error rate. |
Details
This is an implementation of the sample size calculation formula derived by Hsieh and Lavori (2000) for the following Cox proportional hazards regression in the epidemiological studies:
where the covariate is a nonbinary variable and
is a vector of other covariates.
Suppose we want to check if
the hazard ratio of the main effect to
is equal to
or is equal to
.
Given the type I error rate
for a two-sided test, the total
number of subjects required to achieve a sample size of
is
where is the
-th percentile of the standard normal distribution,
,
is the proportion of subjects died of
the disease of interest, and
is the multiple correlation coefficient
of the following linear regression:
That is, , where
is the proportion of variance
explained by the regression of
on the vector of covriates
.
Value
The total number of subjects required.
Note
(1) Hsieh and Lavori (2000) assumed one-sided test, while this implementation assumed two-sided test.
(2) The formula can be used to calculate
ssize for a randomized trial study by setting rho2=0
.
References
Hsieh F.Y. and Lavori P.W. (2000). Sample-size calculation for the Cox proportional hazards regression model with nonbinary covariates. Controlled Clinical Trials. 21:552-560.
See Also
Examples
# example in the EXAMPLE section (page 557) of Hsieh and Lavori (2000).
# Hsieh and Lavori (2000) assumed one-sided test,
# while this implementation assumed two-sided test.
# Hence alpha=0.1 here (two-sided test) will correspond
# to alpha=0.05 of one-sided test in Hsieh and Lavori's (2000) example.
ssizeEpiCont.default(power = 0.806,
theta = exp(1),
sigma2 = 0.3126^2,
psi = 0.738,
rho2 = 0.1837,
alpha = 0.1)