mv.plots.SM {CLAST} R Documentation

## Diagnostic mean values plots.

### Description

Plots mean value of upper limit, lower limit and interval width for four different ranking methods. This function is basically a wrapper for mv.plot.

### Usage

mv.plots.SM(n, a, b, type = "interval",
B = 100, offset = TRUE, plt = c(1, 1, 1), p0 = NULL, p1 = NULL, focus = FALSE)


### Arguments

 n Design vector of planned sample sizes a Design vector of lower futility boundaries b Design vector of upper superiority boundaries type Either "upper", "lower" or "interval" (default) B Integer controlling fineness of plot (default=100) offset if TRUE then ML mean value is subtracted plt Logical vector indicating output plots of upper, lower and interval (default=c(1,1,1)) p0 Lower (null) benchmark for success probability p1 Upper (alternative) benchmark for success probability focus Logical. If true, plots are restricted to p between p0 and p1. (default=FALSE)

NULL

Chris J. Lloyd

### References

Lloyd, C.J. (2021) Exact confidence limits after a group sequential single arm binary trial. Statistics in Medicine, Volume 38, 2389-2399. doi: 10.1002/sim.8909

### Examples

# Figure 2 in Lloyd (2020)
n=c(5,6,5,9)
a=c(2,4,5,12)
b=c(5,9,11,13)
p0=.4
p1=.75
mv.plots.SM(n,a,b,p0=p0,p1=p1)
# Produces three panel graphic identical to Figure 2 in reference
mv.plots.SM(n,a,b,p0=p0,p1=p1,focus=TRUE)
# Produces alternative graphic focussed on relevant values of p.
# In both cases LR (in blue) appears best. CP can perform poorly
# for values of p outside the range of interest.



[Package CLAST version 1.0.1 Index]