RRreg (version 0.4.1)

powerplot: Power plots for multivariate RR methods

Description

Uses the function RRsimu to estimate the power of the multivariate RR methods (correlation RRcor, logistic regression RRlog, and/or linear regression RRlin.

Usage

powerplot(numRep, n = c(100, 500, 1000), pi, cor = c(0, 0.1, 0.3),
  b.log = NULL, model, p, method = c("RRcor", "RRlog", "RRlin"),
  complyRates = c(1, 1), sysBias = c(0, 0), groupRatio = 0.5,
  alpha = 0.05, nCPU = 1, show.messages = TRUE)

Arguments

numRep

number of boostrap replications

n

vector of samples sizes

pi

true prevalence

cor

vector of true correlations

b.log

vector of true logistic regression coefficients

model

randomized response model

p

randomization probability

method

multivariate RR method

complyRates

probability of compliance within carriers/noncarriers of sensitive attribute

sysBias

probability of responding 'yes' in case of noncompliance

groupRatio

ratio of subgroups in two-group RR designs

alpha

type-I error used to estimate power

nCPU

number of CPUs to be used

show.messages

toggle printing of progress messages

Value

• a list of the class powerplot containing an array res with the power estimates and details of the simulation (e.g., model, p, pi, etc.)

See Also

RRsimu for Monte-Carlo simulation / parametric bootstrap

Examples

# Not run
# pplot <- powerplot(100, n=c(150,250), cor=c(0,.3,.5),
#                   method="RRlog", pi=.6, model="Warner", p=.3)
# plot(pplot)