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help for {hi:ciw}, {hi:ciwi}
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{title:Binomial confidence intervals for proportions (Wilson score)}
{p 15 19}{cmd:ciw}{space 2}[{it:varlist}] [{it:weight}] [{cmd:if} {it:exp}]
[{cmd:in} {it:range}] [{cmd:,} {cmdab:l:evel(}{it:#}{cmd:)} {cmdab:t:otal} ]
{p 15 19}{cmd:ciwi} {it:#obs} {space 4} {it:#succ} {space 3}
[{cmd:,} {cmdab:l:evel(}{it:#}{cmd:)} ]
{p}{cmd:by} {it:...} {cmd::} may be used with {cmd:ciw} (but not with
{cmd:ciwi}); see help {help by}.
{p}{cmd:fweight}s are allowed with {cmd:ciw}; see help {help weights}.
{title:Description}
{p}{cmd:ciw} computes standard errors and binomial confidence intervals for
each variable in {it:varlist}, which should be 0/1 binomial variables.
{cmd:ciwi} is the immediate form of {cmd:ciw}, for which specify the number of
observations and the number of successes. See help {help immed}
for more on immediate commands. With both commands
confidence intervals are calculated as Wilson score intervals.
{title:Remarks}
{p}Suppose we observe {it:n} events and record {it:k} successes. Here as usual
"success" is conventional terminology for whatever is coded 1. For a 95%
confidence interval, for example, we then solve the quadratic equation in {it:p}
{p}({it:k} / {it:n} - {it:p}) / sqrt[{it:p} (1 - {it:p}) / {it:n}] = +/-{it:z}
{p}where {it:z} is {cmd:invnorm(0.975)}. See Wilson (1927). This contribution
is of historical interest as an anticipation of Neyman's subsequent formulation
of confidence intervals. It is equivalent to adding {it:z}^2 observations to a
sample, half of them successes and half failures. (At a 95% level, {it:z}^2 /
2 = 1.921 to 3 d.p. and so is nearly 2.) Among other properties, note that this
interval is typically less conservative than the exact interval, so that
coverage probabilities are on average close to the nominal confidence level.
{p}See Brown {it:et al.} (2001) for a much fuller discussion and an entry to
the literature. Brown {it:et al.} (2002) provide supporting technical
background to that paper.
Among many references, Agresti (2002, pp.14-21), Agresti and
Coull (1998), Newcombe (1998, 2001) and Vollset (1993) provide clear and helpful
context. Williams (2001, Ch.6) provides a lively alternative
treatment of confidence intervals for one-parameter models.
For more on the American mathematician, physicist and statistician
Edwin Bidwell Wilson (1879-1964), see Stigler (1997). He should not be
confused with the American biologist Edmund Beecher Wilson (1856-1939), who
worked on cytology, embryology and heredity, nor with the American physical
chemist Edgar Bright Wilson (1908-1992); the writings of the last include
statistical topics (Wilson 1952).
{p}Note that this is close to, but not identical to, a procedure implemented by
Gleason (1999).
{title:Options}
{p 0 4}{cmd:level(}{it:#}{cmd:)} specifies the confidence level, in percent,
for confidence intervals; see help {help level}.
{p 0 4}{cmd:total} is for use with the {cmd:by} {it:...} {cmd::} prefix; it
requests that, in addition to output for each by-group, output be added for all
groups combined.
{title:Examples}
{inp:. ciw foreign}
{inp:. ciwi 10 1}{right:(10 binomial events, 1 observed success)}
{title:References}
{p}Agresti, A. 2002. {it:Categorical data analysis.}
Hoboken, NJ: John Wiley.
{p}Agresti, A. and Coull, B.A. 1998. Approximate is better than "exact" for
interval estimation of binomial proportions. {it:American Statistician}
52: 119-126.
{p}Brown, L.D., Cai, T.T., DasGupta, A. 2001. Interval
estimation for a binomial proportion. {it:Statistical Science}
16: 101-133.
{p}Brown, L.D., Cai, T.T., DasGupta, A. 2002. Confidence intervals
for a binomial proportion and asymptotic expansions. {it:Annals of Statistics}
30: 160-201.
{p}Gleason, J.R. 1999. Improved confidence intervals for binomial proportions.
{it:Stata Technical Bulletin} 52: 16-18 ({it:STB Reprints} 9: 208-211).
{p}Newcombe, R.G. 1998. Two-sided confidence intervals for
the single proportion: comparison of seven methods.
{it:Statistics in Medicine} 17: 857-872.
{p}Newcombe, R.G. 2001. Logit confidence intervals and
the inverse sinh transformation.
{it:American Statistician} 55: 200-202.
{p}Stigler, S.M. 1997. Wilson, Edwin Bidwell.
In Johnson, N.L. and Kotz, S. (eds)
{it:Leading personalities in statistical sciences: from the seventeenth century to the present.}
New York: John Wiley, 344-346.
{p}Vollset, S.E. 1993. Confidence intervals for a
binomial proportion. {it:Statistics in Medicine} 12: 809-824.
{p}Williams, D. 2001.
{it:Weighing the odds: a course in probability and statistics.}
Cambridge: Cambridge University Press.
{p}Wilson, Edgar Bright. 1952.
{it:An introduction to scientific research.}
New York: McGraw-Hill.
{p}Wilson, Edwin Bidwell. 1927. Probable inference,
the law of succession, and statistical inference.
{it:Journal, American Statistical Association}
22: 209-212.
{title:Acknowledgements}
{p 8 8}John R. Gleason increased my interest in this problem.
Richard Williams found a bug in {cmd:ciwi}.
{title:Also see}
Manual: {hi:[R] ci}
{p 0 19}On-line: help for {help ci}, {help bitest}, {help immed}{p_end}