Transcription of Title stata.com regress — Linear regression
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Title stata.com regress — Linear regression
Linear regressionDescriptionQuick startMenuSyntaxOptionsRemarks and examplesStored resultsMethods and formulasAcknowledgmentsReferencesAlso seeDescriptionregressperforms ordinary least-squares Linear also perform weightedestimation, compute robust and cluster robust standard errors, and adjust results for complex startSimple Linear regression ofyonx1regress y x1 regression ofyonx1,x2, and indicators for categorical variablearegress y x1 x2 the interaction between continuous variablex2andaregress y x1 ## model for observations wherev1is greater than zeroregress y x1 x2 if v1>0 With cluster robust standard errors for clustering by levels ofcvarregress y x1 x2 , vce(cluster cvar)With bootstrap standard errorsregress y x1 x2 , vce(bootstrap)Report standardized coefficientsregress y x1 x2 , betaAdjust for complex survey design usingsvysetdatasvy: regress y x1 x2 sampling weightwvarregress y x1 x2 [pweight=wvar]MenuStatistics> Linear models and related> Linear regression12 regress Linear regressionSyntaxregressdepvar[indepvars] [if] [in] [weight] [,options]optionsDescriptionModelnoconst antsuppress constant ter
regress performs ordinary least-squares linear regression. regress can also perform weighted estimation, compute robust and cluster–robust standard errors, and adjust results for complex survey ... estimating treatment effects, and providing answers to public policy questions. For a mathematically rigorous treatment, seePeracchi(2001, chap. 6
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