Sample Size for 2-sample Binomial

Computes sample size(s) for 2-sample binomial problem given vector or scalar probabilities in the two groups.

Usage

samplesize.bin(alpha, beta, pit, pic, rho=0.5)

Arguments

alpha

scalar ONE-SIDED test size, or two-sided size/2

beta

scalar or vector of powers

pit

hypothesized treatment probability of success

pic

hypothesized control probability of success

rho

proportion of the sample devoted to treated group (\(0 <\code{rho} < 1\))

Value

TOTAL sample size(s)

AUTHOR

Rick Chappell
Dept. of Statistics and Human Oncology
University of Wisconsin at Madison
chappell@stat.wisc.edu

Examples

alpha <- .05
beta <- c(.70,.80,.90,.95)


# N1 is a matrix of total sample sizes whose
# rows vary by hypothesized treatment success probability and
# columns vary by power
# See Meinert's book for formulae.


N1 <- samplesize.bin(alpha, beta, pit=.55, pic=.5)
N1 <- rbind(N1, samplesize.bin(alpha, beta, pit=.60, pic=.5))
N1 <- rbind(N1, samplesize.bin(alpha, beta, pit=.65, pic=.5))
N1 <- rbind(N1, samplesize.bin(alpha, beta, pit=.70, pic=.5))
attr(N1,"dimnames") <- NULL


#Accounting for 5% noncompliance in the treated group
inflation <- (1/.95)**2
print(round(N1*inflation+.5,0))
#>      [,1] [,2] [,3] [,4]
#> [1,] 2079 2732 3784 4782
#> [2,]  516  676  937 1184
#> [3,]  225  296  409  518
#> [4,]  125  163  225  284