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 (2020). Second, to
analyze two-by-two factorial trial data which may include baseline
adjustment covariates. Further details are described in the factorial2x2
You can install the released version of factorial2x2 from CRAN with:
We reproduce the power calculations for scenario 4 from Table 2 in
Leifer, Troendle, et al. using the
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) $events  954.8738 # expected number of events $evtprob # event probabilities for the C, A, B, and AB groups, respectively probC probA probB probAB 0.2446365 0.2012540 0.2012540 0.1831806 $powerEA3overallA  0.5861992 # Equal Allocation 3's power to detect the overall A effect $powerEA3simpleA  0.5817954 # Equal Allocation 3's power to detect the simple A effect $powerEA3simplAB  0.9071236 # Equal Allocation 3's power to detect the simple AB effect $powerEA3anyA  0.7060777 # Equal Allocation 3's power to detect either the overall A or simple A effects $powerPA2overallA  0.6582819 # Proportional Allocation 2's power to detect the overall A effect $powerPA2simpleAB  0.9197286 # Proportional Allocation 2's power to detect the simple AB effect $powerEA2simpleA  0.6203837 # Equal Allocation 2's power to detect the simple A effect $powerEA2simpleAB  0.9226679 # Equal Allocation 2's power to detect the simple AB effect $powerA  0.7182932 # power to detect the overall A effect at the two-sided 0.05 level
Leifer, E.S., Troendle, J.F., Kolecki, A., Follmann, D. Joint testing of overall and simple effect for the two-by-two factorial design. 2020. 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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