Power and Sample Size Calculation for Survival Analysis of Epidemiological Studies

Functions to calculate power and sample size for testing main effect or interaction effect in the survival analysis of epidemiological studies (non-randomized studies), taking into account the correlation between the covariate of the interest and other covariates. Some calculations also take into account the competing risks and stratified analysis. This package also includes a set of functions to calculate power and sample size for testing main effect in the survival analysis of randomized clinical trials and conditional logistic regression for nested case-control study.


News

v0.1.0 Feb 7, 2018

(1) Thank Aurélien Latouche [email protected] for pointing out a typo in the Notes of several Rd files. The correct one is:

"In Latouche et al. (2004), the hazard ratio θ measures the difference of effect of a covariate on the subdistribution hazard ratio

, while in Schoenfeld (1983), on the cause specific hazard ratio."

v0.0.9 July 23, 2015

(1) explicitly import 'optim' function in 'NAMESPACE'

v0.0.8 July 22, 2015

(1) rename 'log.txt' as 'NEWS'

(2) fixed a warning:

The Title field should be in title case, current version then in title case:

'Power and sample size calculation for survival analysis of epidemiological studies'

'Power and Sample Size Calculation for Survival Analysis of Epidemiological Studies'

v0.0.7 April 1, 2012

(1) change 'GPL version 2 or newer' to 'GPL (>=2)

in the file 'DESCRIPTION'

v0.0.6 March 28, 2012

(1) added functions 'power.stratify' and 'ssize.stratify'

to calculate power/sample size for stratified survival analysis

Reference manual

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install.packages("powerSurvEpi")

0.1.3 by Weiliang Qiu, 2 months ago


Browse source code at https://github.com/cran/powerSurvEpi


Authors: Weiliang Qiu , Jorge Chavarro , Ross Lazarus , Bernard Rosner , Jing Ma.


Documentation:   PDF Manual  


Task views: Survival Analysis


GPL (>= 2) license


Imports stats, survival, pracma


Imported by PSS.Health.


See at CRAN