rss.prop.test {generalRSS} | R Documentation |
RSS proportion test
Description
The rss.prop.test function performs the population proportion test on ranked set sample data, supporting both balanced and unbalanced RSS designs.
Usage
rss.prop.test(data, alpha = 0.05, alternative = "two.sided", p0)
Arguments
data |
A numeric data frame of ranked set samples with columns |
alpha |
A numeric value specifying the confidence level for the interval. |
alternative |
A character string specifying the alternative hypothesis. Must be one of "two.sided" (default), "greater", or "less". |
p0 |
A numeric value indicating the hypothesized proportion for the one-sample test. |
Details
This function performs a proportion test on ranked set samples. It uses the method introduced by Chen et al. (2006), Zamanzade and Mahdizadeh (2020), and Ahn. et al. (2022) . Provide data
as a data frame with columns rank
and y
. The function calculates the test statistic, confidence intervals, and p-value based on the RSS data.
Value
RSS_prop |
The RSS proportion estimate. |
CI |
The confidence interval for the population proportion. |
pstat |
The test statistic for the proportion test. |
p.value |
The p-value for the test. |
References
Chen, H., Stasny, E. A., & Wolfe, D. A. (2006). Unbalanced ranked set sampling for estimating a population proportion. Biometrics, 62(1), 150-158.
Zamanzade, E., & Mahdizadeh, M. (2020). Using ranked set sampling with extreme ranks in estimating the population proportion. Statistical methods in medical research, 29(1), 165-177.
Ahn, S., Wang, X., Wang, M., & Lim, J. (2022). On continuity correction for RSS-structured cluster randomized designs with binary outcomes. Metron, 80(3), 383-397.
See Also
rss.prop.simulation
: used for simulating Ranked Set Samples (RSS) for proportions, which can serve as input.
rss.prop.sampling
: used for sampling Ranked Set Samples (RSS) from a population data set for proportions, providing input data.
Examples
## Unbalanced RSS with a set size 3 and different sample sizes of 12, 9, 6 for each stratum,
## with a population proportion of 0.6.
rss.prop.data=rss.prop.simulation(H=3,nsamp=c(12,9,6),p=0.6)
## RSS proportion test
rss.prop.test(data=rss.prop.data, alpha=0.05, alternative="two.sided", p0=0.2)