proportion (version 2.0.0)

covpCTW: Coverage Probability of Continuity corrected Wald-T method

Description

Coverage Probability of Continuity corrected Wald-T method

Usage

covpCTW(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

Value

A dataframe with

mcpATW

Continuity corrected Wald-T Coverage Probability

micpATW

Continuity corrected Wald-T 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

Details

Evaluation of approximate and continuity corrected method based on a t_approximation of the standardized point estimator using coverage probability, root mean square statistic, and the proportion of proportion lies within the desired level of coverage

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, covpCLT, covpCSC, covpCWD

Examples

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