I have a little question with respect to the output of my regression below. I ran a mixed-effects GLM regression on several bond characteristics using the meglm command. I conducted a Gaussian distribution and the identity link as you can see in the output below, which I assume to be equivalent with the correlated random effects model aka the Mundlak model. Can anybody confirm this?
Additionally, the meglm command displays no classic goodness-of-fit measure, such as the (adjusted) R-square. Does anybody know whether there is any comparable goodness of fit measure in this output? Or do you guys know a way to run goodness-of-fit tests for GLMs in Stata?
Thank you guys very much and all the best,
Hans
Code:
. meglm YieldtoMaturityMid Standards2 ExternalReview2 Reporting2 BidAsk Ticker_num Currency_num PaymentRank_num MaturityYears2 AmountIssued Iteration 0: log likelihood = -25559.669 Iteration 1: log likelihood = -25559.669 Mixed-effects GLM Number of obs = 9,411 Family: Gaussian Link: identity Wald chi2(8) = . Log likelihood = -25559.669 Prob > chi2 = . ------------------------------------------------------------------------------------------- YieldtoMaturityMid | Coef. Std. Err. z P>|z| [95% Conf. Interval] --------------------------+---------------------------------------------------------------- Standards2 | -1.354097 .4394719 -3.08 0.002 -2.215446 -.4927475 ExternalReview2 | .2656997 .4194891 0.63 0.526 -.5564838 1.087883 Reporting2 | .9717874 .2680178 3.63 0.000 .4464823 1.497093 BidAsk | -.479644 .0244378 -19.63 0.000 -.5275412 -.4317468 Ticker_num | -.0003272 .0002069 -1.58 0.114 -.0007326 .0000783 Currency_num | .0267972 .0033955 7.89 0.000 .0201422 .0334523 PaymentRank_num | .1183414 .0266971 4.43 0.000 .0660161 .1706666 MaturityYears2 | .0067621 .0062303 1.09 0.278 -.0054491 .0189732 AmountIssued | 1.24e-13 5.09e-14 2.44 0.015 2.44e-14 2.24e-13 _cons | .4719899 .2108222 2.24 0.025 .058786 .8851937 --------------------------+---------------------------------------------------------------- var(e.YieldtoMaturityMid)| 13.38312 .1950987 13.00614 13.77102 -------------------------------------------------------------------------------------------
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