lme4, failure to converge with a range of optimisers, trust the fitted model anyway?
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On 15-04-04 02:15 PM, Hans Ekbrand wrote:
On Sat, Apr 04, 2015 at 09:10:35PM +1100, Ken Beath wrote:
One of the problems is that you have a relatively high random effects variance. A standard deviation of the intercept of 3 is a huge amount, it means that there is massive variation in the random effect value needed to model each cluster, to the point that some clusters will be all zeros and some will be all ones. In this situation the assumption of approximate normality of the likelihood around the nodes which is required for using Laplace's method is very far from met.
Thanks for your advice, I really appreciate it! I tried nAGQ=5, but met with: ## Error: nAGQ > 1 is only available for models with a single, scalar random-effects term As you point out, some clusters will be all zeros (and some will be all ones). While my data is on the individual level, a) the variable I'm mainly interested in, KilledPerMillion5Log, varies only at the country level, & b) I currently have no variables in the model that vary at the individual level So, perhaps I could aggregate the individual level data to the cluster level, and do without the random term for cluster? I mean, calculate the proportions of yes in each cluster and use that as the dependent variable. This would, I assume, require that each cluster was given a weight that corresponded to the number of individuals in it - or I would not be able to say anything about probabilities at the individual level, right?
I would say pretty much any time you can aggregate without losing information, you should, for ease of computation (this accords with the Murtaugh 2007 "Simplicity and complexity" paper that I cite here on a regular basis). If all of your covariates are at the cluster level, then this reduces to a binomial GLM (you can account for overdispersion either by using a quasi-binomial model in glm() or by staying with glmer() and keeping the random effect of cluster (now an observation-level random effect). Ben Bolker -----BEGIN PGP SIGNATURE----- Version: GnuPG v1.4.11 (GNU/Linux) iQEcBAEBAgAGBQJVIHVjAAoJEOCV5YRblxUHUYsH/243gzJN9hWayUICMmQop6iZ +p+RIxh3lpSmB1lnRX+VXpghNpB4a5s98m+q5HZJB2eUyBCJ7pwXbHuTaZZ2t2D0 v6V/Ih2VeoqnbVqaSrPDNgDufNO1RhHlc4h6L0bIGf/etmOHgtHaPnly5JUXUmq4 QZdt5Sxotqshdbqf+4FvMNFVa1cNWJNLBY0XB2GecSLa8MI7vF1UHvlqdtDWIO9e WalpfJq6C4oqIyz2kCsZWRijSHroFpPJ6eMlKmbLFLxfY6rP5dQZK11ktsANQ7lu bnPHoF1Xzwnl87XDl/v6K9P1ge2x7bvihDUVodjBoK31CHc8UAYvh/5Ud4AGKoY= =9xK3 -----END PGP SIGNATURE-----