covpCLT: Coverage Probability of Continuity corrected Logit Wald...

In RajeswaranV/proportion: Inference on Single Binomial Proportion and Bayesian Computations

Coverage Probability of Continuity corrected Logit Wald method

Description

Coverage Probability of Continuity corrected Logit Wald method

Usage

covpCLT(n, alp, c, a, b, t1, t2)

Arguments

n	- Number of trials
alp	- Alpha value (significance level required)
c	- Continiuty correction
a	- Beta parameters for hypo "p"
b	- Beta parameters for hypo "p"
t1	- Lower tolerance limit to check the spread of coverage Probability
t2	- Upper tolerance limit to check the spread of coverage Probability

Details

Evaluation of continuity corrected Wald-type interval based on the logit transformation of p using coverage probability, root mean square statistic, and the proportion of proportion lies within the desired level of coverage

Value

A dataframe with

mcpALT	Continuity corrected Logit Wald Coverage Probability
micpALT	Continuity corrected Logit Wald minimum coverage probability
RMSE_N	Root Mean Square Error from nominal size
RMSE_M	Root Mean Square Error for Coverage Probability
RMSE_MI	Root Mean Square Error for minimum coverage probability
tol	Required tolerance for coverage probability

References

[1] 1998 Agresti A and Coull BA. Approximate is better than "Exact" for interval estimation of binomial proportions. The American Statistician: 52; 119 - 126.

[2] 1998 Newcombe RG. Two-sided confidence intervals for the single proportion: Comparison of seven methods. Statistics in Medicine: 17; 857 - 872.

[3] 2008 Pires, A.M., Amado, C. Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods. REVSTAT - Statistical Journal, 6, 165-197.

See Also

Other Coverage probability for continuity corrected methods: PlotcovpCAS(), PlotcovpCAll(), PlotcovpCLT(), PlotcovpCSC(), PlotcovpCTW(), PlotcovpCWD(), covpCAS(), covpCAll(), covpCSC(), covpCTW(), covpCWD()

Examples

n= 10; alp=0.05;c=1/(2*n); a=1;b=1; t1=0.93;t2=0.97
covpCLT(n,alp,c,a,b,t1,t2)

RajeswaranV/proportion documentation built on June 17, 2022, 9:11 a.m.