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Hello Everyone,</div>
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I fitted meta-analysis model using rma() function. I can extract all the fit statistics using fitstats() function. But it doesn't give degrees of freedom (d.f) for deviance. </div>
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Could you please let me know if it's possible to calculate the deviance degrees of freedom (d.f.) and derive its distribution in pairwise meta-analysis? If it's not feasible, I'd appreciate understanding the reasons behind it. Any insights or leads would be
greatly appreciated. Thank you for your time!</div>
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<b>Here is my code: </b></div>
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library(metafor)</div>
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dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg) ### fit random-effects model</div>
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res1 <- rma(yi, vi, data=dat, method="ML") </div>
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> fitstats(res1, REML=F)</div>
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ML</div>
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logLik: -12.66508</div>
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deviance: 37.11602</div>
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AIC: 29.33015</div>
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BIC: 30.46005</div>
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AICc: 30.53015</div>
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Regards,</div>
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Marimuthu,</div>
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Ph.D. candidate</div>
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McMaster University, Canada</div>
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