SeqAllocplot: Plot the evaluation criteria for the designs

In SeqAlloc: Sequential Allocation for Prospective Experiments

Description

Provides boxplots and scatterplots of balance and predictability measures for candidate sequential allocations.

Usage

SeqAllocplot(mysim, bporder = NULL, stratum = F, cexsize = 0.7)

Arguments

mysim	output from function SeqAlloc
bporder	vector giving the randomization methods to be plotted, corresponding to the positions in mysim$schemes
stratum	logical variable of whether PBD designs should be plotted, default is FALSE
cexsize	size of characters in plot and axis, default is 0.7

Value

Produces selected plots of predictability and balance for randomization schemes.Requires user to click window or press "enter" to progress through plots.

Note

These are example plots; the plotting code can be extracted from this function or the function is easily modified if different plots are desired.

Author(s)

Xiaoshu Zhu [e-mail] and Sharon Lohr

References

Lohr, S. and X. Zhu (2015). Randomized Sequential Individual Assignment in Social Experiments: Evaluating the Design Options Prospectively. Sociological Methods and Research. [Advance online publication: December 27, 2015] doi: 10.1177/0049124115621332

See Also

SeqAlloc

Examples

sampsize <- 200
percent <- c(0.5,0.8,0.2,0.4)
set.seed(200)

xmat <- matrix(rbinom(sampsize*length(percent),1,rep(percent,sampsize)),
              nrow=sampsize,ncol=length(percent),byrow=TRUE)
colnames(xmat) <- c("C1","C2","C3","C4")
strat_factor <- xmat[,1]*4 + xmat[,2]*2 + xmat[,4] + 1

mysim <- SeqAlloc(xmat,carwt=c(.4,.3,.2,.1),strata=strat_factor,blksize=c(2,6),
                   pbcd=.7,pcar=.67,bsdtol=2,caittol=3,niter=10, seed = 30924)

SeqAllocplot(mysim,bporder = c(3,4,7,8), stratum = FALSE, cexsize=0.6)

SeqAlloc documentation built on May 2, 2019, 3:14 p.m.