mudiff.mbl.varknown returns the required sample sizes
to reach a given posterior credible interval length and coverage probability for the difference between two normal means - using a mixed Bayesian/likelihood approach - when variances are known.
The desired total length of the posterior credible interval for the difference between the two unknown means
The known precision (reciprocal of variance) for the first population
The known precision (reciprocal of variance) for the second population
The desired coverage probability of the posterior credible interval (e.g., 0.95)
logical. Whether or not the final group sizes (n1, n2) are forced to be equal:
Assume that a sample from each of two populations will be
collected in order to estimate the difference between two independent normal means
when the variances are known.
mudiff.mbl.varknown returns the required sample sizes to attain the
desired length len and coverage probability level for the posterior credible interval
for the difference between the two unknown means.
This function uses a Mixed Bayesian/Likelihood (MBL) approach. MBL approaches use the prior information to derive the predictive distribution of the data, but use only the likelihood function for final inferences. This approach is intended to satisfy investigators who recognize that prior information is important for planning purposes but prefer to base final inferences only on the data.
The required sample sizes (n1, n2) for each group given the inputs to the function.
The sample sizes returned by this function are exact.
Lawrence Joseph [email protected] and Patrick Belisle
Joseph L, Belisle P.
Bayesian sample size determination for Normal means and differences between Normal means
The Statistician 1997;46(2):209-226.
mudiff.mbl.varknown(len=0.2, lambda1=1, lambda2=1/1.5)
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