Error: In mer_finalize(ans) : false convergence (8)
Hello all, I am running an mixed effects model on the attached data. I initially used the following code mod1<- lmer(log(Y)~TMT1*TMT2*Year+(1|Block/TMT1)+(1|Year),data=lmerdat,verbose=TRUE) Which gives me the following: 0: 77.714051: 0.666667 0.471405 0.333333 1: 74.110931: 0.842664 1.45578 0.328587 2: 72.264680: 0.440773 1.34787 0.215307 3: 72.215476: 0.405289 1.27443 0.208252 4: 72.206023: 0.430340 1.25642 0.208492 5: 72.203289: 0.423498 1.22704 0.214935 6: 72.202721: 0.422680 1.22886 0.209101 7: 72.202679: 0.424822 1.23459 0.208315 8: 72.202679: 0.424822 1.23459 0.208315 9: 72.202679: 0.424822 1.23459 0.208315 Warning message: In mer_finalize(ans) : false convergence (8) I thought that I might have too many parameters, so I removed the three way interaction thus: mod1<- lmer(logY)~TMT1+TMT2+Year+TMT1:TMT2+TMT1:Year+TMT2:Year+(1|Block/TMT1)+(1|Year),data=lmerdat,verbose=TRUE) 0: 82.176953: 0.666667 0.471405 0.333333 1: 80.060839: 0.932569 1.42347 0.182093 2: 79.408200: 0.00000 1.72496 0.180290 3: 78.436511: 0.00107482 1.31540 0.182908 4: 78.313534: 0.00586792 1.19163 0.169823 5: 78.292542: 0.0255058 1.16060 0.176287 6: 78.204264: 0.195335 0.918497 0.214946 7: 77.959243: 0.166960 1.02200 0.173634 8: 77.325791: 0.416075 1.15366 0.271404 9: 77.240857: 0.377681 1.16245 0.202179 10: 77.237968: 0.381277 1.16539 0.190858 11: 77.237719: 0.380920 1.16760 0.187107 12: 77.237718: 0.379746 1.17007 0.187519 13: 77.237695: 0.381074 1.16994 0.187148 14: 77.237695: 0.380772 1.16969 0.187087 15: 77.237695: 0.380778 1.16974 0.187092 16: 77.237695: 0.380806 1.16978 0.187098 17: 77.237695: 0.380906 1.16978 0.187107 18: 77.237695: 0.380999 1.16975 0.187128 19: 77.237695: 0.380982 1.16965 0.187105 20: 77.237695: 0.380961 1.16967 0.187112 21: 77.237695: 0.380961 1.16967 0.187112 Warning message: In mer_finalize(ans) : false convergence (8)
So the model seemed to get a bit further but still will not converge... I don't want to remove anything else as my model will then not invetsigate the relationships I want it to and I don't think it is overparameterised without that 3 way interaction... If i multiply Y by 10 it gets a bit further again but still stalls:
mod1<- lmer(log(I(10*Y))~TMT1+TMT2+Year+TMT1:TMT2+TMT1:Year+TMT2:Year+(1|Block/TMT1)+(1|Year),data=lmerdat,verbose=TRUE)
0: 82.176953: 0.666667 0.471405 0.333333 1: 80.059473: 0.932336 1.42350 0.181868 2: 79.407034: 0.00000 1.72457 0.181162 3: 78.529865: 0.00000 1.30356 0.0708756 4: 78.320758: 0.000702149 1.19618 0.193718 5: 78.308420: 0.00287500 1.16437 0.161311 6: 78.298595: 0.0199600 1.14541 0.174745 7: 78.198050: 0.0954940 1.07394 0.224686 8: 78.095409: 0.159180 1.01562 0.265286 9: 77.628631: 0.238546 1.05911 0.235037 10: 77.251998: 0.395868 1.12462 0.185342 11: 77.239703: 0.373209 1.15530 0.187029 12: 77.238348: 0.378481 1.15960 0.186789 13: 77.237962: 0.380487 1.16277 0.186797 14: 77.237766: 0.380997 1.16609 0.186947 15: 77.237720: 0.380749 1.16757 0.187021 16: 77.237698: 0.381015 1.16893 0.187108 17: 77.237697: 0.380978 1.16905 0.187112 18: 77.237696: 0.380954 1.16929 0.187109 19: 77.237696: 0.381002 1.16935 0.187111 20: 77.237695: 0.381017 1.16942 0.187070 21: 77.237695: 0.380947 1.16958 0.187109 22: 77.237695: 0.380947 1.16976 0.187103 23: 77.237695: 0.380948 1.16975 0.187105 24: 77.237695: 0.380948 1.16975 0.187105 25: 77.237695: 0.380948 1.16975 0.187105 26: 77.237695: 0.380948 1.16975 0.187105 Warning message: In mer_finalize(ans) : false convergence (8) Is there a solution to this? Can I trust the model outputs that I am getting in spite of this convergence issue? I can't use the suggested resolution of dividing or multiplying explanatory variables by 10/100/1000 etc as these variables are categorical.... Sorry to post another question about this - I just can't find an answer that fits my data. Any thoughts would be much appreciated Best wishes, Sarah -- NERC PhD Student Community Ecology and Global Change Department of Biology Imperial College, London email: sarah.dryhurst08 at imperial.ac.uk