proportion (version 2.0.0)

ciALTx: Adjusted Logit-Wald method of CI estimation

Description

Adjusted Logit-Wald method of CI estimation

Usage

ciALTx(x, n, alp, h)

Arguments

x

- Number of successes

n

- Number of trials

alp

- Alpha value (significance level required)

h

- Adding factor

Value

A dataframe with

x

Number of successes (positive samples)

LALTx

Logit Wald Lower limit

UALTx

Logit Wald Upper Limit

LABB

Logit Wald Lower Abberation

UABB

Logit Wald Upper Abberation

ZWI

Zero Width Interval

Details

Wald-type interval for the logit transformation \(log(p/1-p)\) of the parameter p for the modified data eqnx + h and \(n + (2*h)\) , where \(h > 0\) and the given x and n.

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 Adjusted methods of CI estimation given x & n: PlotciAAllx, ciAASx, ciAAllx, ciALRx, ciASCx, ciATWx, ciAWDx

Examples

x=5; n=5; alp=0.05;h=2
ciALTx(x,n,alp,h)