View source: R/123.ConfidenceIntervals_CC_n_x.R
ciCAllx | R Documentation |
CI estimation of 5 continuity corrected methods (Wald, Wald-T, Score, Logit-Wald, ArcSine)
ciCAllx(x, n, alp, c)
x |
- Number of sucess |
n |
- Number of trials |
alp |
- Alpha value (significance level required) |
c |
- Continuity correction |
The Confidence Interval of 5 continuity corrected methods (Wald, Wald-T, Score, Logit-Wald, ArcSine) for n
given alp
and x
A dataframe with
method |
- Name of the method |
x |
- Number of successes (positive samples) |
LLT |
- Lower limit |
ULT |
- Upper Limit |
LABB |
- Lower Abberation |
UABB |
- Upper Abberation |
ZWI |
- Zero Width Interval |
[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.
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 given x and n:
PlotciCAllxg()
,
PlotciCAllx()
,
ciCLTx()
,
ciCSCx()
,
ciCTWx()
,
ciCWDx()
x=5; n=5; alp=0.05;c=1/(2*n) ciCAllx(x,n,alp,c)
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