Description Usage Arguments Value AUTHOR Examples

View source: R/samplesize.bin.s

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

1 | ```
samplesize.bin(alpha, beta, pit, pic, rho=0.5)
``` |

`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 ( |

TOTAL sample size(s)

Rick Chappell

Dept. of Statistics and Human Oncology

University of Wisconsin at Madison

[email protected]

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
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))
``` |

harrelfe/Hmisc documentation built on Oct. 3, 2019, 9:34 p.m.

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