# Plot power and type 1 error of a "Modify margin" Non-inferiority trial design A function for plotting power and type 1 error of a "Modify margin" Non-inferiority trial design after running simulations . ```r figure.modify.margin(simulations, nominal=NULL, col=NULL, pch=16, lty=NULL, xlim=NULL, ylim=NULL) ``` ## Arguments - `simulations`: A list obtained as an output from function simulations.modify.margin. - `nominal`: An optional argument to draw a red horizontal line specifying the nominal power or type 1 error. - `col`: A vector with colors of the different lines. See help file for the general plot function. - `pch`: A vector with plotting characters of the different lines. See help file for the general plot function. - `lty`: A vector with line types of the different lines. See help file for the general plot function. - `xlim, ylim`: numeric vectors of length 2, giving the x and y coordinates ranges. ## Details This is a function to plot power (type 1 error) of the modify margin procedures for different values of actual control event risk. ## Examples ```r n.sim<-100 # In real applications use at least n.sim <- 10000 p0.expected<-0.05 # Expected control event rate p1.expected<-p0.expected # Same as expected active event rate p1.tolerable<-0.1 # Maximum tolerable active event rate NI.marg<-p1.tolerable-p0.expected r<-1 # Allocation ratio power<-0.9 # Power alph<-0.025 # Significance level alph.an<-c(0.01,0.015,0.02,0.025) # Significance level range.of.p0<-seq(0.005,0.20,0.005) # Power - risk difference res<-simulations.modify.margin(p0.expected, p1.expected, p1.tolerable, thresholds=c(Inf, 0.0125,0.025,0.05), range.of.p0=range.of.p0, sig.level.design=alph, sig.level.analysis=alph, power=power, r=r, scale="RD", print.out=TRUE, ran.seed=1, n.sim=n.sim) figure.modify.margin(res, 0.9) res2<-simulations.modify.margin(p0.expected, p1.expected, p1.tolerable, thresholds=c(Inf, 0.0125,0.025,0.05), range.of.p0=range.of.p0, sig.level.design=alph, sig.level.analysis=alph, power=power, r=r, scale="RD", print.out=TRUE, ran.seed=1, n.sim=n.sim, perf.measure="type1error") figure.modify.margin(res2, 0.025) ```

figure.modify.margin function