91 lines
3.1 KiB
Plaintext
91 lines
3.1 KiB
Plaintext
{smcl}
|
||
{hline}
|
||
help for {cmd:checkvars} {right:Amadou B. DIALLO}
|
||
{right:Jean-Benoit HARDOUIN}
|
||
{hline}
|
||
|
||
{title:Allows checking whether a variable exists or not in a dataset.}
|
||
|
||
|
||
{p 4 8 2}{cmd:checkvars} {it:anything} [{cmd:,}
|
||
{cmdab:t:olerance}({it:#}) {cmdab:ta:ble} {cmdab:nol:ist} {cmdab:nosu:m}
|
||
{cmdab:genm:iss}({it:newvarname})]
|
||
|
||
{title:Description}
|
||
|
||
{p 4 4 2}{cmd:checkvars} is a routine to check for existence of variables
|
||
within a (usually big) data set.
|
||
|
||
{p 4 4 2}{cmd:checkvars} searchs through the data whether each variable exists.
|
||
The variables are clustered between unavailable variables, available variables with
|
||
a little amount of missing values and available variables with too many missing values.
|
||
|
||
{p 4 4 2}{cmd:isvar} must be installed ({stata ssc install isvar:ssc install isvar}).
|
||
|
||
{title:Options}
|
||
|
||
{p 4 4 2}{it:anything} is composed of variable names or lists of variables,
|
||
|
||
{p 4 4 2}{cmd:tolerance} is the tolerance level (in percentage) to consider a variable as available, with default 0,
|
||
|
||
{p 4 4 2}{cmd:nolist} avoids displaying availability status at the end of the process,
|
||
|
||
{p 4 4 2}{cmd:nosum} avoids displaying summary statistics of available variables,
|
||
|
||
{p 4 4 2}{cmd:table} displays the results in a table (instead as text),
|
||
|
||
{p 4 4 2}{cmd:genmiss} creates a new variable containing the number of missing values among the available variables.
|
||
|
||
|
||
|
||
{title:Saved results}
|
||
|
||
{p 4 4 2} {cmd:r(unavailable)} names of unavailable variables.{p_end}
|
||
|
||
{p 4 4 2} {cmd:r(available)} names of available variables with a small amount of missing values.{p_end}
|
||
|
||
{p 4 4 2} {cmd:r(manymissings)} names of variables but with too missings.{p_end}
|
||
|
||
{title:Examples}
|
||
|
||
{p 4 4 2}{cmd:. use mydata, clear }{p_end}
|
||
|
||
{p 4 4 2}{cmd:. checkvars x y z ,genmiss(countmiss) }{p_end}
|
||
|
||
{p 4 4 2}{cmd:. su `r(available)' }{p_end}
|
||
|
||
{p 4 4 2}{cmd:. tab countmiss }{p_end}
|
||
|
||
{p 4 4 2}{cmd:. u bigdataset in 1/100, clear // Big data set}{p_end}
|
||
|
||
{p 4 4 2}{cmd:. checkvars v1 v2 v3 xx yy , nosum tol(5) tab}{p_end}
|
||
|
||
{p 4 4 2}{cmd:. use `r(available)' using bigdataset, clear }{p_end}
|
||
|
||
{title:Remarks}
|
||
|
||
{p 4 4 2}{cmd:checkvars} and its primary versions ({cmd:checkfor} and {cmd:checkfor2}) have been primarily written for comparable surveys such as the Demography and
|
||
Health Surveys (DHS) or the Multiple Indicator Cluster Surveys (MICS). But this could easily applied
|
||
to any other survey.
|
||
|
||
{title:Authors}
|
||
|
||
{p 4 4 2}Amadou Bassirou DIALLO.
|
||
Poverty and Health Specialist. AFTPM, The World Bank.{p_end}
|
||
{p 4 4 2}Email: {browse "mailto:adiallo5@worldbank.org":adiallo5@worldbank.org}
|
||
|
||
{p 4 4 2}Jean-Benoit HARDOUIN.
|
||
Regional Health Observatory of Orl<72>ans, France.{p_end}
|
||
{p 4 4 2}Email: {browse "mailto:jean-benoit.hardouin@orscentre.org":jean-benoit.hardouin@orscentre.org}
|
||
|
||
{title:Aknowledgements}
|
||
|
||
{p 4 4 2}We would like to thank Christophe Rockmore and also Nick Cox
|
||
and Kit Baum for their comments.
|
||
|
||
{title:Also see}
|
||
|
||
{p 4 13 2}Online: help for {help checkfor}, {help checkfor2}, {help isvar}, {help nmissing}, {help npresent}, {help missing} and {help dropmiss} if installed.{p_end}
|
||
|
||
|