## Stata 15 help for centile

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[R] centile -- Report centile and confidence interval

Syntax

centile [varlist] [if] [in] [, options]

options               Description
-------------------------------------------------------------------------
Main
centile(numlist)    report specified centiles; default is centile(50)

Options
cci                 binomial exact; conservative confidence interval
normal              normal, based on observed centiles
meansd              normal, based on mean and standard deviation
level(#)            set confidence level; default is level(95)
-------------------------------------------------------------------------
by and statsby are allowed; see prefix.

Statistics > Summaries, tables, and tests > Summary and descriptive
statistics > Centiles with CIs

Description

centile estimates specified centiles and calculates confidence intervals.
If no varlist is specified, centile calculates centiles for all the
variables in the dataset.  If no centiles are specified, medians are
reported.

By default, centile uses a binomial method for obtaining confidence
intervals that makes no assumptions about the underlying distribution of
the variable.

Options

+------+
----+ Main +-------------------------------------------------------------

centile(numlist) specifies the centiles to be reported.  The default is
to display the 50th centile.  Specifying centile(5) requests that the
fifth centile be reported.  Specifying centile(5 50 95) requests that
the 5th, 50th, and 95th centiles be reported.  Specifying
centile(10(10)90) requests that the 10th, 20th, ..., 90th centiles be
reported.

+---------+
----+ Options +----------------------------------------------------------

cci (conservative confidence interval) forces the confidence limits to
fall exactly on sample values.  Confidence intervals displayed with
the cci option are slightly wider than those with the default (nocci)
option.

normal causes the confidence interval to be calculated by using a formula
for the standard error of a normal-distribution quantile given by
Kendall and Stuart (1969, 237). The normal option is useful when you
want empirical centiles -- that is, centiles based on sample order
statistics rather than on the mean and standard deviation -- and are
willing to assume normality.

meansd causes the centile and confidence interval to be calculated based
on the sample mean and standard deviation, and it assumes normality.

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

Calculate the 50th centile for all variables in the dataset
. centile

Calculate the 50th centile for price
. centile price

Calculate the 50th centile for price, showing 99% CI
. centile price, level(99)

Calculate the 5th, 50th, and 95th centiles for price
. centile price, centile(5 50 95)

Calculate the 10th, 20, 30th, ..., 90th centiles for price
. centile price, centile(10(10)90)

Calculate the 10th centile for price, assuming normality
. centile price, centile(10) normal

Stored results

centile stores the following in r():

Scalars
r(N)           number of observations
r(n_cent)      number of centiles requested
r(c_#)         value of # centile
r(lb_#)        #-requested centile lower confidence bound
r(ub_#)        #-requested centile upper confidence bound

Macros
r(centiles)    centiles requested

Reference

Kendall, M. G., and A. Stuart. 1969.  The Advanced Theory of Statistics,
Vol. 1: Distribution Theory. 3rd ed.  London: Griffin.

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