ciCLT: Continuity corrected Logit Wald method of CI estimation

In proportion: Inference on Single Binomial Proportion and Bayesian Computations

Description

Continuity corrected Logit Wald method of CI estimation

Usage

ciCLT(n, alp, c)

Arguments

n	- Number of trials
alp	- Alpha value (significance level required)
c	- Continuity correction

Details

Wald-type interval for the logit transformation of the parameter p using the test statistic (abs(L(phat)-L(p))-c)/SE where c > 0 is a constant for continuity correction and L(y) = log(y/1-y) for all x = 0, 1, 2 ..n. Boundary modifications when x = 0 or x = n using Exact method values.

Value

A dataframe with

x	Number of successes (positive samples)
LCLT	Logit Wald Lower limit
UCLT	Logit Wald Upper Limit
LABB	Logit Wald Lower Abberation
UABB	Logit Wald Upper Abberation
ZWI	Zero Width Interval

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

prop.test and binom.test for equivalent base Stats R functionality, binom.confint provides similar functionality for 11 methods, wald2ci which provides multiple functions for CI calculation , binom.blaker.limits which calculates Blaker CI which is not covered here and propCI which provides similar functionality.

Other Continuity correction methods of CI estimation: PlotciCAS, PlotciCAllg, PlotciCAll, PlotciCLT, PlotciCSC, PlotciCTW, PlotciCWD, ciCAS, ciCAll, ciCSC, ciCTW, ciCWD

Examples

n=5; alp=0.05;c=1/(2*n)
ciCLT(n,alp,c)

Example output

  x       LCLT      UCLT LABB UABB ZWI
1 0 0.00000000 0.5218238   NO   NO  NO
2 1 0.02466007 0.7119784   NO   NO  NO
3 2 0.09156625 0.8151352   NO   NO  NO
4 3 0.18486483 0.9084338   NO   NO  NO
5 4 0.28802162 0.9753399   NO   NO  NO
6 5 0.47817625 1.0000000   NO   NO  NO

proportion documentation built on May 1, 2019, 7:54 p.m.