ss.fromdata.pois {ssanv} | R Documentation |
Find sample sizes when 2 Poisson means are estimated from data
Description
Calculate sample sizes for two-sample differences in Poisson means when means are estimated from existing data
Usage
ss.fromdata.pois(xbar0, xbar1, m0, m1, ss.ratio = 1, sig.level = 0.05,
real.power = 0.8, nominal.power = NULL,
alternative = c("two.sided", "one.sided"), MINN0 = 1, MAXN0 = 10^5)
Arguments
xbar0 |
mean from control group of existing data |
xbar1 |
mean from treatment group of existing data |
m0 |
sample size of control group of existing data |
m1 |
sample size of treatment group of existing data |
ss.ratio |
n1/n0, where n0 (n1) is sample size of control (treatment) group for proposed study |
sig.level |
significance level (Type I error) |
real.power |
minimum power that you want the sample size to achieve, only .8 or .9 allowed |
nominal.power |
see details |
alternative |
One- or two-sided test |
MINN0 |
minimum sample size for control group |
MAXN0 |
maximum sample size for control group |
Details
Calculates the sample sizes for a study designed to test the difference between the means of two groups,
where it is assumed that the responses from both groups are distributed Poisson.
The means from each group (xbar0
and xbar1
) come from existing data that is assumed to also follow the
same Poisson distributions. The method is inherently conservative, so that with a nominal power of .77 the real power
will be about .80, and a nominal power of .89 the real power will be about .90. Other values of nominal power are
allowed, but only real powers of .80 or .90 are allowed.
If mu0 and mu1 are the means from the two groups,
the one-sided tests are designed to test either
H_0: \mu_0 \leq \mu_1
vs.
H_1: \mu_0 > \mu_1
or to test
H_0: \mu_0 \geq \mu_1
vs.
H_1: \mu_0 < \mu_1
.
We estimate \mu_0
and \mu_1
with
\hat{\mu}_0 = xbar0 + \frac{1}{2m_0}
and
\hat{\mu}_1 = xbar1 + \frac{1}{2m_1}
.
The choice of hypotheses is determined by the value of \hat{\mu}_0
and \hat{\mu}_1
;
if \hat{\mu}_0 > \hat{\mu}_1
then the former hypotheses are tested, otherwise the latter are.
See Fay, Halloran and Follmann (2007) for details.
Value
Object of class "power.htest", a list of the arguments (including the computed sample sizes) augmented with 'METHOD' and 'NOTE' elements. The values 'n0' and 'n1' are the samples sizes for the two groups, rounded up to the nearest integer.
Note
The function ss.fromdata.pois
calls uniroot.integer
, a function written for this package that
finds the nearest integer to the root.
Author(s)
Michael P. Fay
References
Fay, M.P., Halloran, M.E., and Follmann, D.A. (2007). 'Accounting for Variability in Sample Size Estimation with Applications to Nonadherence and Estimation of Variance and Effect Size' Biometrics 63: 465-474.
See Also
ss.fromdata.nvar
,
ss.fromdata.neff
,
ss.nonadh
,
uniroot.integer
Examples
ss.fromdata.pois(1.65,.88,23,25)