| mu.alc {SampleSizeMeans} | R Documentation |
Bayesian sample size determination for estimating a single normal mean using the Average Length Criterion
Description
The function mu.alc returns the required sample size
to reach a given posterior credible interval length on average for a fixed coverage probability for a normal mean.
Usage
mu.alc(len, alpha, beta, n0, level = 0.95)Arguments
len |
The desired average length of the posterior credible interval for the mean |
alpha |
First prior parameter of the Gamma density for the precision (reciprocal of the variance) |
beta |
Second prior parameter of the Gamma density for the precision (reciprocal of the variance) |
n0 |
Prior sample size equivalent for the mean |
level |
The desired fixed 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.alc returns the required sample size
to attain the desired average length len for the posterior credible interval
of fixed coverage probability level 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.acc, 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.alc(len=0.2, alpha=2, beta=2, n0=10)