Hi all, I need help to understand convergence problems with my estimation.
I am using lmer to estimate a mixed-effects model of an index of teacher quality on student achievement gains. The dataset for female students is available in the link above and contains original and imputed data (m=5 and m=50) <https://www.dropbox.com/sh/fqpjtkkuz9y9mzr/MhrMXwlrFp> I want to understand the error messages above and their implications for my parameter estimates. 1: In mer_finalize(ans) : false convergence (8) 2: In mer_finalize(ans) : singular convergence (7) 3: In mer_finalize(ans) : singular convergence (7) 4: In mer_finalize(ans) : false convergence (8) 5: In mer_finalize(ans) : false convergence (8) Below you may find the script for my procedures. Any help will be appreciated! Thanks, Raquel ----------------------------------------------------------------- #Multiple imputation library("mice") md.pattern(data.f) md.pairs(data.f) # 5 imputations - Predictive mean matching imp.5.f<-mice(data.f,m=5,seed=23109) print(imp.5.f) # 50 imputations - Predictive mean matching imp.50.f<-mice(data.f,m=50,seed=23109) print(imp.50.f) #Running lmer library(lme4) #Imputed data #Females Uncpde.math.f.mi <- with(imp.50.f, lmer(gain ~ index + ( index | std_id), verbose=TRUE)) print(pool(Uncpde.math.f.mi)) round(summary(pool(Uncpde.math.f.mi)), 2) > Uncpde.math.f.mi <- with(imp.50.f, lmer(gain ~ index + + ( index | std_id), verbose=TRUE)) 0: 91323.888: 0.666667 0.0912755 0.000000 1: 90950.102: 0.579295 0.000000 -0.298895 2: 88854.168: 0.305206 0.000000 -0.0962998 3: 88814.543: 0.288910 8.27185e-010 -0.126235 4: 88797.001: 0.261789 0.00137943 -0.146833 5: 88783.121: 0.229797 0.000000 -0.136191 6: 88765.032: 0.163649 0.000000 -0.170033 7: 88764.059: 0.101518 0.00683235 -0.129860 8: 88757.161: 0.0894730 0.000000 -0.151620 9: 88756.669: 0.0802386 0.000000 -0.161394 10: 88756.413: 0.0692536 0.000000 -0.169148 11: 88756.296: 0.0566213 0.000000 -0.173754 12: 88756.276: 0.0473775 0.000000 -0.172026 13: 88756.268: 0.0454115 0.000000 -0.177962 14: 88756.268: 0.0445268 0.000000 -0.177518 15: 88756.268: 0.0445255 6.95905e-007 -0.177518 16: 88756.268: 0.0443349 1.91179e-007 -0.177519 17: 88756.268: 0.0443349 1.91179e-007 -0.177519 0: 90892.401: 0.666667 0.0901811 0.000000 1: 90565.986: 0.582914 0.000000 -0.301351 2: 88348.591: 0.262114 0.000000 -0.107499 3: 88300.308: 0.000000 0.000000 -0.259898 4: 88300.308: 0.000000 0.000000 -0.259898 0: 92116.635: 0.666667 0.0860717 0.000000 1: 91920.069: 0.589035 0.000000 -0.302245 2: 89502.995: 0.208420 0.000000 -0.118175 3: 89484.310: 0.000000 0.000000 -0.217057 4: 89484.310: 0.000000 0.000000 -0.217057 0: 90508.355: 0.666667 0.0907223 0.000000 1: 90069.269: 0.575010 0.000000 -0.303351 2: 87914.618: 0.289817 0.000000 -0.0984479 3: 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0.0721130 0.000000 -0.159438 12: 88538.184: 0.0695887 0.000000 -0.160606 13: 88538.183: 0.0680936 0.000000 -0.160978 14: 88538.183: 0.0677477 0.000000 -0.160916 15: 88538.183: 0.0676509 0.000000 -0.160808 16: 88538.183: 0.0676691 0.000000 -0.160770 0: 90816.807: 0.666667 0.0906318 0.000000 1: 90424.195: 0.578291 0.000000 -0.302393 2: 88300.640: 0.297094 0.000000 -0.100293 3: 88204.488: 0.000000 0.000000 -0.253910 4: 88204.488: 0.000000 0.000000 -0.253910 0: 91513.066: 0.666667 0.0905136 0.000000 1: 91059.392: 0.572808 0.000000 -0.304419 2: 88963.498: 0.308436 0.000000 -0.0961059 3: 88828.230: 0.00365434 0.000000 -0.238915 4: 88828.230: 0.00353298 2.48295e-007 -0.238904 5: 88828.228: 0.000809467 8.53595e-006 -0.238663 6: 88828.227: 0.000000 0.000000 -0.238628 7: 88828.227: 0.000000 0.000000 -0.238628 0: 91150.802: 0.666667 0.0891040 0.000000 1: 90889.912: 0.587635 0.000000 -0.295390 2: 88556.237: 0.240279 0.000000 -0.104882 3: 88549.670: 0.235780 0.000000 -0.114362 4: 88542.519: 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-0.249850 4: 88136.845: 0.000000 0.000000 -0.249850 0: 91038.775: 0.666667 0.0912136 0.000000 1: 90656.405: 0.581786 0.000000 -0.298768 2: 88476.176: 0.280341 0.000000 -0.100177 3: 88413.623: 0.000000 0.000000 -0.270528 4: 88413.623: 0.000000 4.32879e-009 -0.270528 5: 88413.623: 0.000000 4.32879e-009 -0.270528 0: 90534.064: 0.666667 0.0912434 0.000000 1: 90158.703: 0.581799 0.000000 -0.299923 2: 88007.169: 0.285653 0.000000 -0.101348 3: 87975.548: 0.270763 9.94850e-010 -0.132543 4: 87963.471: 0.241261 0.00166749 -0.150478 5: 87955.484: 0.212149 0.000000 -0.133227 6: 87948.984: 0.188039 0.000000 -0.157996 7: 87945.106: 0.157972 2.87461e-009 -0.140942 8: 87942.894: 0.135918 0.000655211 -0.167551 9: 87942.121: 0.110783 0.000000 -0.144511 10: 87941.407: 0.0820679 0.000000 -0.163754 11: 87941.374: 0.0874460 0.000000 -0.164379 12: 87941.366: 0.0924083 0.000000 -0.165031 13: 87941.366: 0.0921629 2.75824e-006 -0.164807 14: 87941.365: 0.0918365 0.000000 -0.164754 15: 87941.365: 0.0918121 1.05293e-009 -0.164776 16: 87941.365: 0.0916407 1.25385e-007 -0.164902 17: 87941.365: 0.0916280 0.000000 -0.164885 18: 87941.365: 0.0915976 1.78900e-007 -0.164855 19: 87941.365: 0.0915710 0.000000 -0.164868 20: 87941.365: 0.0915709 6.77374e-008 -0.164868 21: 87941.365: 0.0915707 0.000000 -0.164868 22: 87941.365: 0.0915706 0.000000 -0.164869 23: 87941.365: 0.0915706 0.000000 -0.164869 0: 90538.952: 0.666667 0.0906664 0.000000 1: 90188.780: 0.580152 0.000000 -0.298077 2: 87995.424: 0.280946 0.000000 -0.0982630 3: 87965.709: 0.263221 1.10254e-009 -0.127679 4: 87950.953: 0.232057 0.00156023 -0.142027 5: 87932.225: 0.160075 0.000000 -0.123961 6: 87924.828: 0.107481 0.000000 -0.177222 7: 87923.913: 0.101794 1.32194e-009 -0.172355 8: 87922.762: 0.0898806 0.000000 -0.163290 9: 87922.603: 0.0870883 2.97543e-007 -0.162210 10: 87921.808: 0.0643480 0.000000 -0.154688 11: 87921.756: 0.0619822 1.91616e-007 -0.155062 12: 87921.461: 0.0430376 0.000000 -0.157938 13: 87921.329: 0.0246316 0.000000 -0.160343 14: 87921.290: 0.0115580 0.000000 -0.161904 15: 87921.281: 0.00286298 0.000000 -0.162911 16: 87921.281: 0.00189741 3.55755e-005 -0.162906 17: 87921.280: 0.000934638 0.000000 -0.162938 18: 87921.280: 0.000000 0.000000 -0.162968 19: 87921.280: 0.000000 0.000000 -0.162968 0: 89913.444: 0.666667 0.0906915 0.000000 1: 89490.109: 0.578190 0.000000 -0.300666 2: 87265.611: 0.273646 0.000000 -0.0992267 3: 87184.839: 0.000000 0.000000 -0.273871 4: 87184.839: 0.000000 0.000000 -0.273871 0: 91445.647: 0.666667 0.0887779 0.000000 1: 91205.368: 0.586436 0.000000 -0.295702 2: 88923.840: 0.258811 0.000000 -0.103445 3: 88907.893: 0.242519 0.000000 -0.128815 4: 88901.918: 0.218662 0.000000 -0.147252 5: 88895.042: 0.195226 0.000965137 -0.128307 6: 88890.006: 0.169408 0.000000 -0.143102 7: 88886.667: 0.140591 0.000000 -0.134234 8: 88884.703: 0.113739 4.18354e-009 -0.147949 9: 88883.819: 0.0890199 0.000000 -0.150225 10: 88883.509: 0.0702513 0.000000 -0.151673 11: 88883.409: 0.0564583 0.000000 -0.152518 12: 88883.380: 0.0469538 0.000000 -0.152913 13: 88883.374: 0.0411088 0.000000 -0.152998 14: 88883.372: 0.0382539 0.000000 -0.152898 15: 88883.372: 0.0371689 0.000000 -0.152722 16: 88883.372: 0.0365899 0.000000 -0.152428 17: 88883.372: 0.0362285 0.000000 -0.151744 18: 88883.371: 0.0366140 0.000000 -0.150915 19: 88883.371: 0.0373644 0.000000 -0.150538 20: 88883.371: 0.0373648 4.72818e-007 -0.150539 21: 88883.371: 0.0375860 0.000000 -0.150728 22: 88883.371: 0.0378454 0.000000 -0.150594 Warning messages: 1: In mer_finalize(ans) : false convergence (8) 2: In mer_finalize(ans) : singular convergence (7) 3: In mer_finalize(ans) : singular convergence (7) 4: In mer_finalize(ans) : false convergence (8) 5: In mer_finalize(ans) : false convergence (8) > print(pool(Uncpde.math.f.mi)) Call: pool(object = Uncpde.math.f.mi) Pooled coefficients: (Intercept) index 1.90889735 0.02891385 Fraction of information about the coefficients missing due to nonresponse: (Intercept) index 0.9464698 0.9361655 > round(summary(pool(Uncpde.math.f.mi)), 2) est se t df Pr(>|t|) lo 95 hi 95 nmis fmi lambda (Intercept) 1.91 0.27 6.98 49.87 0.0 1.36 2.46 NA 0.95 0.94 index 0.03 0.03 0.85 51.68 0.4 -0.04 0.10 11776 0.94 0.93 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
