| fedesign {clinfun} | R Documentation |
Trial Designs Based On Fisher's Exact Test
Description
Calculates sample size, effect size and power based on Fisher's exact test
Usage
fe.ssize(p1, p2, alpha=0.05, power=0.8, r=1, npm=5, mmax=1000)
CPS.ssize(p1, p2, alpha=0.05, power=0.8, r=1)
fe.mdor(ncase, ncontrol, pcontrol, alpha=0.05, power=0.8)
mdrr(n, cprob, presp, alpha=0.05, power=0.8, niter=15)
fe.power(d, n1, n2, p1, alpha = 0.05)
or2pcase(pcontrol, OR)
Arguments
p1 |
response rate of standard treatment |
p2 |
response rate of experimental treatment |
d |
difference = p2-p1 |
pcontrol |
control group probability |
n1 |
sample size for the standard treatment group |
n2 |
sample size for the standard treatment group |
ncontrol |
control group sample size |
ncase |
case group sample size |
alpha |
size of the test (default 5%) |
power |
power of the test (default 80%) |
r |
treatments are randomized in 1:r ratio (default r=1) |
npm |
the sample size program searches for sample sizes in a range (+/- npm) to get the exact power |
mmax |
the maximum group size for which exact power is calculated |
n |
total number of subjects |
cprob |
proportion of patients who are marger positive |
presp |
probability of response in all subjects |
niter |
number of iterations in binary search |
OR |
odds-ratio |
Details
CPS.ssize returns Casagrande, Pike, Smith sample size which is a very close to the exact. Use this for small differences p2-p1 (hence large sample sizes) to get the result instantaneously.
Since Fisher's exact test orders the tables by their probability the test is naturally two-sided.
fe.ssize return a 2x3 matrix with CPS and Fisher's exact sample sizes with power.
fe.mdor return a 3x2 matrix with Schlesselman, CPS and Fisher's exact minimum detectable odds ratios and the corresponding power.
fe.power returns a Kx2 matrix with probabilities (p2) and exact power.
mdrr computes the minimum detectable P(resp|marker+) and P(resp|marker-) configurations when total sample size (n), P(response) (presp) and proportion of subjects who are marker positive (cprob) are specified.
or2pcase give the probability of disease among the cases for a given probability of disease in controls (pcontrol) and odds-ratio (OR).
References
Casagrande, JT., Pike, MC. and Smith PG. (1978). An improved approximate formula for calculating sample sizes for comparing two binomial distributions. Biometrics 34, 483-486.
Fleiss, J. (1981) Statistical Methods for Rates and Proportions.
Schlesselman, J. (1987) Re: Smallest Detectable Relative Risk With Multiple Controls Per Case. Am. J. Epi.