Is it possible to generate AICs and BICs for a Difference-in-Difference Regression model that was fitted using didregress module in STATA?
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EDITED: Since didregress always reports clustered standard errors, it makes sense that no log-likelihood information is reported. See https://www.stata.com/support/faqs/s...od-ratio-test/. In case you want to calculate the statistics without clustering, use regress. Also, see https://www.statalist.org/forums/help#spelling on spelling Stata.
Res.:Code:use "https://www.stata-press.com/data/r17/hospdd.dta", clear didregress (satis)(procedure), group(hospital) time(month) aequations regress satis procedure i.month, absorb(hospital) estat ic
Code:. didregress (satis)(procedure), group(hospital) time(month) aequations Number of groups and treatment time Time variable: month Control: procedure = 0 Treatment: procedure = 1 ----------------------------------- | Control Treatment -------------+--------------------- Group | hospital | 28 18 -------------+--------------------- Time | Minimum | 1 4 Maximum | 1 4 ----------------------------------- Difference-in-differences regression Number of obs = 7,368 Data type: Repeated cross-sectional (Std. err. adjusted for 46 clusters in hospital) ------------------------------------------------------------------------------- | Robust satis | Coefficient std. err. t P>|t| [95% conf. interval] --------------+---------------------------------------------------------------- ATET | procedure | (New vs Old) | .8479879 .0321121 26.41 0.000 .7833108 .912665 --------------+---------------------------------------------------------------- Controls | month | February | -.0096077 .0184317 -0.52 0.605 -.0467311 .0275158 March | .0219686 .018251 1.20 0.235 -.0147907 .0587279 April | -.0032839 .0221028 -0.15 0.883 -.0478013 .0412335 May | -.0094027 .0232399 -0.40 0.688 -.0562103 .0374048 June | -.0038375 .0190634 -0.20 0.841 -.0422332 .0345581 July | -.0111941 .0230029 -0.49 0.629 -.0575244 .0351361 | _cons | 3.444675 .011354 303.39 0.000 3.421807 3.467543 ------------------------------------------------------------------------------- Note: ATET estimate adjusted for group effects and time effects. . . regress satis procedure i.month, absorb(hospital) Linear regression, absorbing indicators Number of obs = 7,368 F(7, 7315) = 146.83 Prob > F = 0.0000 R-squared = 0.5333 Adj R-squared = 0.5299 Root MSE = .72384 ------------------------------------------------------------------------------ satis | Coefficient Std. err. t P>|t| [95% conf. interval] -------------+---------------------------------------------------------------- procedure | .8479879 .0342191 24.78 0.000 .7809086 .9150672 | month | February | -.0096077 .0292119 -0.33 0.742 -.0668715 .0476561 March | .0219686 .0292119 0.75 0.452 -.0352952 .0792324 April | -.0032839 .0324936 -0.10 0.920 -.0669806 .0604129 May | -.0094027 .0324936 -0.29 0.772 -.0730995 .054294 June | -.0038375 .0324936 -0.12 0.906 -.0675343 .0598592 July | -.0111941 .0324936 -0.34 0.730 -.0748909 .0525026 | _cons | 3.444675 .0168655 204.24 0.000 3.411614 3.477736 ------------------------------------------------------------------------------ . . estat ic Akaike's information criterion and Bayesian information criterion ----------------------------------------------------------------------------- Model | N ll(null) ll(model) df AIC BIC -------------+--------------------------------------------------------------- . | 7,368 -8531.297 -8046.947 8 16109.89 16165.13 ----------------------------------------------------------------------------- Note: BIC uses N = number of observations. See [R] BIC note. .Last edited by Andrew Musau; 09 Mar 2023, 12:18. -
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Please, is didregress appropriate for categorical outcomes?Originally posted by Kehinde Atoloye View PostComment
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Please, is didregress appropriate for categorical outcomes?Comment
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If the outcome is ordered and has several levels, you may be fine with didregress. Otherwise, no. See some references on attempts at nonlinear DID: https://stats.stackexchange.com/ques...ic-regressionsComment
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