help ci, help cii dialogs: ci cii (binomial)
cii (normal) cii (poisson)
-------------------------------------------------------------------------------
Title
[R] ci -- Confidence intervals for means, proportions, and counts
Syntax
Syntax for ci
ci [varlist] [if] [in] [weight] [, options]
Immediate command for variable distributed as normal
cii #obs #mean #sd [, ciin_option]
Immediate command for variable distributed as binomial
cii #obs #succ [, ciib_options]
Immediate command for variable distributed as Poisson
cii #exposure #events , poisson [ciip_options]
options description
-------------------------------------------------------------------------
Main
binomial binomial 0/1 variables; compute exact confidence
intervals
poisson Poisson variables; compute exact confidence
intervals
exposure(varname) exposure variable; implies poisson
exact calculate exact confidence intervals; the default
wald calculate Wald confidence intervals
wilson calculate Wilson confidence intervals
agresti calculate Agresti-Coull confidence intervals
jeffreys calculate Jeffreys confidence intervals
total add output for all groups combined (for use with
by only)
separator(#) draw separator line after every # variables;
default is separator(5)
level(#) set confidence level; default is level(95)
-------------------------------------------------------------------------
by is allowed with ci; see [D] by.
aweights and fweights are allowed, but aweights may not be specified with
the binomial or poisson option, see weight.
ciin_option description
-------------------------------------------------------------------------
level(#) set confidence level; default is level(95)
-------------------------------------------------------------------------
ciib_options description
-------------------------------------------------------------------------
level(#) set confidence level; default is level(95)
exact calculate exact confidence intervals; the default
wald calculate Wald confidence intervals
wilson calculate Wilson confidence intervals
agresti calculate Agresti-Coull confidence intervals
jeffreys calculate Jeffreys confidence intervals
-------------------------------------------------------------------------
ciip_options description
-------------------------------------------------------------------------
* poisson numbers are Poisson-distributed counts
level(#) set confidence level; default is level(95)
-------------------------------------------------------------------------
* poisson is required.
Menu
ci
Statistics > Summaries, tables, and tests > Summary and descriptive
statistics > Confidence intervals
cii for variable distributed as normal
Statistics > Summaries, tables, and tests > Summary and descriptive
statistics > Normal CI calculator
cii for variable distributed as binomial
Statistics > Summaries, tables, and tests > Summary and descriptive
statistics > Binomial CI calculator
cii for variable distributed as Poisson
Statistics > Summaries, tables, and tests > Summary and descriptive
statistics > Poisson CI calculator
Description
ci computes standard errors and confidence intervals for each of the
variables in varlist.
cii is the immediate form of ci; see immed for a general discussion of
immediate commands.
In the binomial and Poisson variants of cii, the second number specified
(#succ or #events) must be an integer or between 0 and 1. If the number
is between 0 and 1, Stata interprets it as the fraction of successes or
events and converts it to an integer number representing the number of
successes or events. The computation then proceeds as if two integers
had been specified.
Options
+------+
----+ Main +-------------------------------------------------------------
binomial tells ci that the variables are 0/1 variables and that binomial
confidence intervals will be calculated. (cii produces binomial
confidence intervals when only two numbers are specified.)
poisson specifies that the variables (or numbers for cii) are
Poisson-distributed counts; exact Poisson confidence intervals will
be calculated.
exposure(varname) is used only with poisson. You do not need to specify
poisson if you specify exposure(); poisson is assumed. varname
contains the total exposure (typically a time or an area) during
which the number of events recorded in varlist were observed.
exact, wald, wilson, agresti, and jeffreys specify that variables are 0/1
and specify how binomial confidence intervals are to be calculated.
exact is the default and specifies exact (also known in the
literature as Clopper-Pearson [1934]) binomial confidence intervals.
wald specifies calculation of Wald confidence intervals.
wilson specifies calculation of Wilson confidence intervals.
agresti specifies calculation of Agresti-Coull confidence intervals.
jeffreys specifies calculation of Jeffreys confidence intervals.
See Brown, Cai, and DasGupta (2001) for a discussion and comparison
of the different binomial confidence intervals.
total is for use with the by prefix. It requests that, in addition to
output for each by-group, output be added for all groups combined.
separator(#) specifies how often separation lines should be inserted into
the output. The default is separator(5), meaning that a line is
drawn after every five variables. separator(10) would draw the line
after every 10 variables. separator(0) suppresses the separation
line.
level(#) specifies the confidence level, as a percentage, for confidence
intervals. The default is level(95) or as set by set level.
Examples
---------------------------------------------------------------------------
Setup
. sysuse auto
Obtain normal-approximation 90% confidence intervals for means
. ci mpg price, level(90)
---------------------------------------------------------------------------
Setup
. webuse promonone
Obtain various binomial confidence intervals for proportions
. ci promoted, binomial
. ci promoted, binomial wilson
. ci promoted, binomial agresti
. ci promoted, binomial jeffreys
---------------------------------------------------------------------------
Setup
. webuse petri
Obtain exact Poisson confidence interval for a count variable
. ci count, poisson
---------------------------------------------------------------------------
Setup
. webuse rm
Obtain confidence intervals for total exposure variables
. ci deaths, exposure(pyears)
Obtain confidence intervals for mean for data with 166 observations,
mean=19509, and sd=4379
. cii 166 19509 4379
Same as above, but obtain 90% confidence intervals
. cii 166 19509 4379, level(90)
Obtain binomial confidence intervals for data with 10 binomial events and
1 observed success
. cii 10 1
Same as above, but obtain the Wilson confidence interval
. cii 10 1, wilson
Obtain Poisson confidence intervals for data with 1 exposure and 27
events
. cii 1 27, poisson
---------------------------------------------------------------------------
Saved results
ci and cii saves the following in r():
Scalars
r(N) number of observations or exposure
r(mean) mean
r(se) estimate of standard error
r(lb) lower bound of confidence interval
r(ub) upper bound of confidence interval
References
Brown, L. D., T. T. Cai, and A. DasGupta. 2001. Interval estimation for
a binomial proportion. Statistical Science 16: 101-133.
Clopper, C. J., and E. S. Pearson. 1934. The use of confidence or
fiducial limits illustrated in the case of the binomial. Biometrika
26: 404-413.
Also see
Manual: [R] ci
Help: [R] bitest, [R] centile, [R] ameans, [D] pctile, [R] prtest, [R]
summarize, [R] ttest
