| mu.acc {SampleSizeMeans} | R Documentation |
Bayesian sample size determination for estimating a single normal mean using the Average Coverage Criterion
Description
The function mu.acc returns the required sample size
to reach a given coverage probability on average for a posterior credible interval of fixed length for a normal mean.
Usage
mu.acc(len, alpha, beta, n0, level=0.95)Arguments
len |
The desired fixed length of the posterior credible interval for the mean |
alpha |
First parameter of the Gamma prior density for the precision (reciprocal of the variance) |
beta |
Second parameter of the Gamma prior density for the precision (reciprocal of the variance) |
n0 |
Prior sample size equivalent for the mean |
level |
The desired average coverage probability of the posterior credible interval (e.g., 0.95) |
Details
Assume that a sample will be collected in order to estimate
the mean of a normally distributed random variable. Assume that the precision (reciprocal of the variance) of
this random variable is unknown, but has prior information in the form of a
Gamma(alpha, beta) density. Assume that the mean is unknown, but has
prior information equivalent to n0 previous observations . The function mu.acc returns the
required sample size to attain the desired average coverage probability level
for the posterior credible interval of fixed length len for the unknown mean.
This function uses a fully Bayesian approach to sample size determination.
Therefore, the desired coverages and lengths are only realized if the prior distributions input to the function
are used for final inferences. Researchers preferring to use the data only for final inferences are encouraged
to use the Mixed Bayesian/Likelihood version of the function.
Value
The required sample size given the inputs to the function.
Note
The sample size returned by this function is exact.
Author(s)
Lawrence Joseph lawrence.joseph@mcgill.ca and Patrick Bélisle
References
Joseph L, Bélisle P.
Bayesian sample size determination for Normal means and differences between Normal means
The Statistician 1997;46(2):209-226.
See Also
mu.alc, mu.modwoc, mu.varknown, mu.mblacc, mu.mblalc, mu.mblmodwoc, mu.mbl.varknown, mu.freq, mudiff.acc, mudiff.alc, mudiff.modwoc, mudiff.acc.equalvar, mudiff.alc.equalvar, mudiff.modwoc.equalvar, mudiff.varknown, mudiff.mblacc, mudiff.mblalc, mudiff.mblmodwoc, mudiff.mblacc.equalvar, mudiff.mblalc.equalvar, mudiff.mblmodwoc.equalvar, mudiff.mbl.varknown, mudiff.freq
Examples
mu.acc(len=0.2, alpha=2, beta=2, n0=10)