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help for kappci, kappaci                              (Author:  David Harrison)
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Confidence intervals for kappa

Two unique raters, two ratings:

kappci varname1 varname2 [if exp] [in range] [, positive(exp)
[exact|wilson|agresti|jeffreys] level(#) ]

Two or more (non-unique) raters, two ratings:

kappci varname1 varname2 varname3 [...] [if exp] [in range] [,
positive(exp) level(#) ]

kappaci varname1 varname2 [if exp] [in range] [, level(#) ]

Description

kappci (first syntax) calculates the kappa-statistic measure of
interrater agreement when there are two unique raters and two ratings,
with confidence interval using the goodness-of-fit approach of Donner &
Eliasziw (1992).

kappci (second syntax) and kappaci calculate the kappa-statistic in the
case of two or more (nonunique) raters and two ratings, with confidence
interval using an inverted modified Wald test approach applied to the
Fleis-Cuzick estimate of kappa as recommended by Zou & Donner (2004).

kappci (second syntax) and kappaci produce the same results; they merely
assume the data are organized differently.  Both commands assume each
observation is a subject.  In the case of kappci, varname1 contains the
ratings by the first rater, varname2 the ratings by the second rater, and
so on.  kappaci, on the other hand, assumes each variable records the
frequencies with which ratings were assigned.  The first variable records
the number of times a positive rating was assigned, and the second
variable the number of times a negative rating was assigned.  These
definitions follow the same patterns as kap and kappa; see help kappa.

Options

positive(exp) specifies an expression identifying the ratings that should
be considered to be positive; the default assumes non-zero (and
non-missing) for positive and 0 for negative.

exact, wilson, agresti, and jeffreys specify how binomial confidence
intervals for the observed agreement are to be calculated (see help
ci); the default is exact.

level(#) specifies the confidence level, in percent, for confidence
intervals; see help level.

Examples

Two raters, rating variables coded 0/1.

Two raters, rating variables coded Y/N, Wilson confidence interval on
observed agreement.

More than two raters, 99% confidence interval.

. kappaci pos neg, level(99)

References

Donner, A. and Eliasziw, M. 1992. A goodness-of-fit approach to inference
procedures for the kappa statistic: confidence interval construction,
significance-testing and sample size estimation. Statistics in Medicine
11: 1511-1519.

Zou, G. and Donner, A. 2004. Confidence interval estimation of the
intraclass correlation coefficient for binary outcome data. Biometrics
60: 807-811.

Maintainer

David A. Harrison
Intensive Care National Audit & Research Centre
david@icnarc.org

Also see

Online:  help for kappa, ci
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