{smcl}
{* 29sep2004}{...}
{hline}
help for {hi:kapci}, {hi:kappaci}{right:(Author:  David Harrison)}
{hline}

{title:Confidence intervals for kappa}

{p 4 4 2}
Two unique raters, two ratings:

{p 8 15 2}{cmd:kapci} {it:varname1} {it:varname2}
		[{cmd:if} {it:exp}] [{cmd:in} {it:range}]
		[{cmd:,} {cmdab:pos:itive(}{it:exp}{cmd:)}
        [{cmdab:exa:ct}|{cmdab:w:ilson}|{cmdab:a:gresti}|{cmdab:j:effreys}]
	    {cmdab:l:evel:(}{it:#}{cmd:)} ]

{p 4 4 2}Two or more (non-unique) raters, two ratings:

{p 8 15 2}{cmd:kapci} {it:varname1} {it:varname2} {it:varname3} [{it:...}]
		[{cmd:if} {it:exp}] [{cmd:in} {it:range}]
        [{cmd:,} {cmdab:pos:itive(}{it:exp}{cmd:)}
        {cmdab:l:evel:(}{it:#}{cmd:)} ]

{p 8 15 2}{cmd:kappaci} {it:varname1} {it:varname2}
		[{cmd:if} {it:exp}] [{cmd:in} {it:range}]
		[, {cmdab:l:evel:(}{it:#}{cmd:)} ]


{title:Description}

{p 4 4 2}
{cmd:kapci} (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).

{p 4 4 2}
{cmd:kapci} (second syntax) and {cmd: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).

{p 4 4 2}
{cmd:kapci} (second syntax) and {cmd: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 {cmd:kapci}, {it:varname1} contains the
ratings by the first rater, {it:varname2} the ratings by the second rater, and
so on.  {cmd: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 {cmd:kap} and {cmd:kappa}; see help {help kappa}.


{title:Options}

{p 4 8 2}{cmd:positive(}{it:exp}{cmd:)} 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.

{p 4 8 2}{cmd:exact}, {cmd:wilson}, {cmd:agresti}, and {cmd:jeffreys} specify
how binomial confidence intervals for the observed agreement are to be
calculated (see help {help ci}); the default is {cmd:exact}.

{p 4 8 2}{cmd:level(}{it:#}{cmd:)} specifies the confidence level, in percent,
for confidence intervals; see help {help level}.


{title:Examples}

{p 4 4 2}Two raters, rating variables coded 0/1.

{p 8 12 2}{cmd:. kapci rada radb}

{p 4 4 2}Two raters, rating variables coded Y/N, Wilson confidence interval on
observed agreement.

{p 8 12 2}{cmd:. kapci rada radb, pos("Y") wilson}

{p 4 4 2}More than two raters, 99% confidence interval.

{p 8 12 2}{cmd:. kappaci pos neg, level(99)}


{title:References}

{p 4 4 2}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. {it:Statistics in Medicine} 11: 1511-1519.

{p 4 4 2}Zou, G. and Donner, A. 2004. Confidence interval estimation of the
intraclass correlation coefficient for binary outcome data. {it:Biometrics} 60: 807-811.


{title:Maintainer}

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


{title:Also see}

    Online:  help for {help kappa}, {help ci}
