# samplesize.bin

From Hmisc v4.1-1
by Frank E Harrell Jr

##### 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

```
# NOT RUN {
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))
# }
```

*Documentation reproduced from package Hmisc, version 4.1-1, License: GPL (>= 2)*

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