mss.bb {bssbinom} | R Documentation |
Bayesian sample size for a binomial proportion under a binomial/beta model
Description
Computes the minimum sample size for estimating a binomial proportion under a binomial/beta model using Average Coverage Criterion or Average Length Criterion.
Usage
mss.bb(
crit,
c,
d,
rho.min = NULL,
len = NULL,
rho = NULL,
len.max = NULL,
R = 1000,
n0 = 1
)
Arguments
crit |
A character string specifying the criterion. Available criteria: "ACC", "ALC" and "ALCApprox". |
c |
First parameter of the beta prior distribution. |
d |
Second parameter of the beta prior distribution. |
rho.min |
A number in (0, 1) representing the minimum admissible posterior probability for the HPD interval in the ACC. |
len |
A positive real number representing the length of the HPD interval in the ACC. |
rho |
A number in (0, 1) representing the posterior probability of the HPD in the ALC. |
len.max |
A positive real number representing the maximum admissible length for the HPD interval in the ALC. |
R |
Number of replicates used in the simulation. Default is 1000. |
n0 |
A positive integer, |
Value
An integer representing the minimum sample size.
Note
Depending on the fixed values for interval length and probability, the function may take a while to calculate the sample size. ALC tends to be faster than ACC. Since this function uses Monte Carlo simulations, the provided minimum sample sizes may vary from one call to the next. The difference is expected to decrease as the number of replicates (R
) used in the Monte Carlo simulation increases. For the "ALCApprox" criterion the function uses the result of Theorem 4.1 of M'Lan et al. (2008).
References
Costa, E. G. (2025). Bayesian Sample Size for Binomial Proportions with Applications in R. In: Awe, O.O., A. Vance, E. (eds) Practical Statistical Learning and Data Science Methods. STEAM-H: Science, Technology, Engineering, Agriculture, Mathematics & Health. Springer, Cham. doi:10.1007/978-3-031-72215-8_14.
M’Lan, C.E., Joseph, L., Wolfson, D.B. (2008). Bayesian sample size determination for binomial proportions. Bayesian Analysis, 3, 269–296.
Examples
mss.bb(crit = "ALC", c = 10, d = 2, rho = 0.9, len.max = 0.25)
mss.bb(crit = "ALCApprox", c = 10, d = 2, rho = 0.9, len.max = 0.25)
mss.bb(crit = "ACC", c = 2, d = 10, rho.min = 0.9, len = 0.25)