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I am currently trying to find a best model using R for Panel Data. I have a project on Corporate Governance in which I collected data of various companies from 2009-2014. I found the best fit using Backward Elimination and Forward Selection using T values in R which concur with themselves (I think its expected as well). But, after reading various articles in academic community I realize T values can give dubious results and to gain any sort of credibility for my results it will be best to use AIC or BIC criteria (even though its not a big improvement by the looks of things in terms of credibility but still its some improvement). As I understand, the definition of AIC is as follows:

AIC = -2log-likelihood+2p (for BIC it will be plogn)

For normal data with no time series, R has a pre-defined function stepAIC which selects variables according to AIC values till AIC value cannot decrease.

But for panel data I havent found any way to find AIC value. I have tried searching for this but in vain.

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    $\begingroup$ Stepwise regression should be avoided, for reasons that are well documented on this site. It is not only not good for prediction; it distorts all aspects of statistical inference. $\endgroup$ – Frank Harrell Apr 28 at 12:09
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Hi I know it is an old Question but i had a similar problem:

I ended up using the lmer/lme4 packages and I was able to force option="ML" to force the use of the conventional Maximum likelihood function, instead of using the REML (restricted maximum likelihood) default option. so stepAIC from mass package could optimize by AIC.

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  • $\begingroup$ What do you mean by force a ML function? $\endgroup$ – mdewey Aug 4 '16 at 15:58
  • $\begingroup$ mdewey - rlme functions by defaust uses “restricted maximum likelihood” method (REML) and I couldnt find a way to optimize by AIC using this REML default option. but I was able to run the optimization by AIC if setting the option="ML", using the standar Maximum likelihood function. please refer to: stats.stackexchange.com/questions/48671/… $\endgroup$ – Alexandre Ludolf Aug 4 '16 at 17:49

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