{smcl} {* *! version 1.1.0 7.October.2017}{...} {title:Title} {p2colset 5 18 20 2}{...} {p2col:{hi:cmatch}{hline 1}}Tabulation of matched pairs in 1:1 case control study by exposure status{p2colreset}{...} {title:Syntax} {p 4 4 2} {cmd:cmatch} {hi: Y} {hi: xvar} {hi: group} [if] [in] {p 4 4 2} where: {p_end} {p 4 4 2} {hi:Y}: The name of the binary indicator (0: control, 1: case) of the case and control status. {p_end} {p 4 4 2} {hi:xvar}: The name of the exposure categorical variable. {p_end} {p 4 4 2} {hi:group}: The name of the variable which identifies the matched 1:1 pair. {p_end} {title:Description} {p 4 4 2 120} Matched case-control studies are a {hi: classical Epidemiology} study design. Case-control study designs are used to estimate the relative risk for a disease from a specific risk factor. The estimate is the odds ratio, which is a good estimate of the relative risk especially when the disease is rare. {hi: cmatch} tabulates the number of matched pairs by {hi:c} levels of an exposure variable. {hi: cmatch} forms a {hi:c x c} table of matched pairs by the exposure status of the case and the exposure status of the control. The data must be in the form of individual records. {p_end} {title:Example} webuse lowbirth2 cmatch low smoke pairid clogit low smoke, group(pairid) or vsquish . webuse lowbirth2 (Applied Logistic Regression, Hosmer & Lemeshow) . cmatch low smoke pairid 1:1 matched pairs (case-control) by levels of the exposure variable: smoke | Cases Controls | 0 1 | Total -----------+----------------------+---------- 0 | 18 22 | 40 1 | 8 8 | 16 -----------+----------------------+---------- Total | 26 30 | 56 Matched pairs by smoke: 26 . clogit low smoke, group(pairid) or vsquish Conditional (fixed-effects) logistic regression Number of obs = 112 LR chi2(1) = 6.79 Prob > chi2 = 0.0091 Log likelihood = -35.419282 Pseudo R2 = 0.0875 ------------------------------------------------------------------------------ low | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- smoke | 2.75 1.135369 2.45 0.014 1.224347 6.176763 ------------------------------------------------------------------------------ {title:Remarks} {p 4 4 2 120} Remember: {hi:Y} must be a binary indicator variable coded (0, 1); {hi:xvar} must be a categorical variable and, {hi:group} is the variable that identifies the 1:1 matched pair. {p_end} {title:References} {p 4 4 2 120} Hosmer DW, Lemeshow S (2000) Applied logistic regression (Wiley series in probability and statistics). Wiley, New York {p_end} {title:Authorship and developer} {phang}Authorship: EPM304-London School of Hygiene and Tropical Medicine{p_end} {phang}Developer: Miguel Angel Luque-Fernandez{p_end} {phang}Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, U.K.{p_end} {phang}E-mail:{browse "mailto:miguel-angel.luque@lshtm.ac.uk":miguel-angel.luque@lshtm.ac.uk}{p_end} {title:Also see} {psee} Online: {helpb clogit} {p_end}