View source: R/321.Expec_Leng_CC_All.R
| lengthCLT | R Documentation | 
Expected Length summary of continuity corrected Logit Wald method
lengthCLT(n, alp, c, a, b)
n | 
 - Number of trials  | 
alp | 
 - Alpha value (significance level required)  | 
c | 
 - Continuity correction  | 
a | 
 - Beta parameters for hypo "p"  | 
b | 
 - Beta parameters for hypo "p"  | 
Evaluation of continuity corrected Wald-type interval based on the logit transformation of p using sum of length of the n + 1 intervals
A dataframe with
sumLen | 
 The sum of the expected length  | 
explMean | 
 The mean of the expected length  | 
explSD | 
 The Standard Deviation of the expected length  | 
explMax | 
 The max of the expected length  | 
explLL | 
 The Lower limit of the expected length calculated using mean - SD  | 
explUL | 
 The Upper limit of the expected length calculated using mean + SD  | 
[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 Expected length  of continuity corrected methods: 
PlotexplCAS(),
PlotexplCAll(),
PlotexplCLT(),
PlotexplCSC(),
PlotexplCTW(),
PlotexplCWD(),
PlotlengthCAS(),
PlotlengthCAll(),
PlotlengthCLT(),
PlotlengthCSC(),
PlotlengthCTW(),
PlotlengthCWD(),
lengthCAS(),
lengthCAll(),
lengthCSC(),
lengthCTW(),
lengthCWD()
n= 10; alp=0.05; c=1/(2*n);a=1;b=1; lengthCLT(n,alp,c,a,b)
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