View source: R/221.CoverageProb_CC_All.R
| covpCSC | R Documentation | 
Coverage Probability of Continuity corrected Score method
covpCSC(n, alp, c, a, b, t1, t2)
| 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 | 
Evaluation of continuity corrected score test approach using coverage probability, root mean square statistic, and the proportion of proportion lies within the desired level of coverage
A dataframe with
| mcpAS | Continuity corrected Score Coverage Probability | 
| micpAS  | Continuity corrected 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 | 
[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.
Other Coverage probability for continuity corrected methods: 
PlotcovpCAS(),
PlotcovpCAll(),
PlotcovpCLT(),
PlotcovpCSC(),
PlotcovpCTW(),
PlotcovpCWD(),
covpCAS(),
covpCAll(),
covpCLT(),
covpCTW(),
covpCWD()
n= 10; alp=0.05; c=1/(2*n); a=1;b=1; t1=0.93;t2=0.97 covpCSC(n,alp,c,a,b,t1,t2)
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