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000241330 037__ $$a199-2016-2828
000241330 037__ $$a199-2016-2877
000241330 041__ $$aen_US
000241330 245__ $$aRegression anatomy, revealed
000241330 260__ $$c2013
000241330 269__ $$a2013
000241330 270__ $$mfiloso@unina.it$$pFiloso,   Valerio
000241330 300__ $$a17
000241330 336__ $$aJournal Article
000241330 520__ $$aThe regression anatomy theorem (Angrist and Pischke, 2009, Mostly Harmless Econometrics: An Empiricist’s Companion [Princeton University Press]) is an alternative formulation of the Frisch–Waugh–Lovell theorem (Frisch and Waugh, 1933, Econometrica 1: 387–401; Lovell, 1963, Journal of the American Statistical Association 58: 993–1010), a key finding in the algebra of ordinary least-squares multiple regression models. In this article, I present a command, reganat, to implement graphically the method of regression anatomy. This addition complements the built-in Stata command avplot in the validation of linear models, producing bidimensional scatterplots and regression lines obtained by controlling for the other covariates, along with several fine-tuning options. Moreover, I provide 1) a fully worked-out proof of the regression anatomy theorem and 2) an explanation of how the regression anatomy and the Frisch–Waugh–Lovell theorems relate to partial and semipartial correlations, whose coefficients are informative when evaluating relevant variables in a linear regression model.
000241330 542__ $$fLicense granted by Lisa Gilmore (lgilmore@stata.com) on 2016-07-12T18:38:59Z (GMT):

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000241330 650__ $$aResearch Methods/ Statistical Methods
000241330 6531_ $$areganat
000241330 6531_ $$aregression anatomy
000241330 6531_ $$aFrisch–Waugh–Lovell theorem
000241330 6531_ $$alinear models
000241330 6531_ $$apartial correlation
000241330 6531_ $$asemipartial correlation
000241330 700__ $$aFiloso, Valerio
000241330 773__ $$d1st Quarter 2013$$jVolume 13$$kNumber 1$$o106$$q92$$tStata Journal
000241330 8564_ $$s293474$$uhttp://ageconsearch.umn.edu/record/241330/files/sjart_st0285.pdf
000241330 887__ $$ahttp://purl.umn.edu/241330
000241330 909CO $$ooai:ageconsearch.umn.edu:241330$$qGLOBAL_SET
000241330 912__ $$nSubmitted by Lisa Gilmore (lgilmore@stata.com) on 2016-07-12T18:40:38Z
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  Previous issue date: 2013
000241330 982__ $$gStata Journal>Volume 13, Number 1, 1st Quarter 2013
000241330 980__ $$a199