knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The goals of the factorial2x2
package are twofold: First, to provide power calculations for a two-by-two factorial design in which the effects of the two factors may be sub-additive. Power is provided for the overall effect test for as well as the multiple testing procedures described in Leifer, Troendle, Kolecki, and Follmann (2019). Second, to analyze two-by-two factorial trial data which may include baseline adjustment covariates. Further details are described in the factorial2x2 vignette.
You can install the released version of factorial2x2 from CRAN with:
install.packages("factorial2x2")
We reproduce the power calculations for scenario 5 from Table 2 in Leifer, Troendle, et al. using the fac2x2design
function.
n <- 4600 # total sample size rateC <- 0.0445 # one year event rate in the control group hrA <- 0.80 # simple A effect hazard ratio hrB <- 0.80 # simple B effect hazard ratio hrAB <- 0.72 # simple AB effect hazard ratio mincens <- 4.0 # minimum censoring time in years maxcens <- 8.4 # maximum censoring time in years fac2x2design(n, rateC, hrA, hrB, hrAB, mincens, maxcens, dig = 2, alpha = 0.05) $powerA [1] 0.7182932 # power to detect the overall A effect at the two-sided 0.05 level $power23.13 [1] 0.9290271 # power to detect the overall A or simple AB effects using the # 2/3-1/3 procedure $power13.13.13 [1] 0.9302084 # power to detect the overall A, simple A, or simple AB effects using # the 1/3-1/3-1/3 procedure $power12.12 [1] 0.9411688 # power to detect the simple A or simple AB effects using the # 1/2-1/2 procedure $events # expected number of events [1] 954.8738 $evtprob # event probabilities for the C, A, B, and AB groups, respectively probC probA probB probAB 0.2446365 0.2012540 0.2012540 0.1831806
Leifer, E.S., Troendle, J.F., Kolecki, A., Follmann, D. Joint testing of overall and simple effect for the two-by-two factorial design. 2019. Submitted.
Lin, D-Y., Gong, J., Gallo, P., et al. Simultaneous inference on treatment effects in survival studies with factorial designs. Biometrics. 2016; 72: 1078-1085.
Slud, E.V. Analysis of factorial survival experiments. Biometrics. 1994; 50: 25-38.
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