proportion (version 2.0.0)

covpASC: Coverage Probability of Adjusted Score method for given n

Description

Coverage Probability of Adjusted Score method for given n

Usage

covpASC(n, alp, h, a, b, t1, t2)

Arguments

n

- Number of trials

alp

- Alpha value (significance level required)

h

- Adding factor

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

mcpAS

Adjusted Score Coverage Probability

micpAS

Adjusted Score 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 adjusted score test approach 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 of adjusted methods: PlotcovpAAS, PlotcovpAAll, PlotcovpALR, PlotcovpALT, PlotcovpASC, PlotcovpATW, PlotcovpAWD, covpAAS, covpAAll, covpALR, covpALT, covpATW, covpAWD

Examples

n= 10; alp=0.05; h=2; a=1;b=1; t1=0.93;t2=0.97
covpASC(n,alp,h,a,b,t1,t2)