Hi all,

I am trying to fit a simple mixed model for longitudinal data, but the
algorithm is not converging. When I add additional commands in the call I
am able to increase the number of iterations from the default of 50 to 146,
but no more than that. Does anyway have an idea about what is going on?  I
can provided data if needed.

Best, Antonio.

> model.c2 <- lme(log(child_mortality) ~  time + log(maternal_educ) +
log(maternal_educ)*time,
+                control=lmeControl(msMaxIter = 200, msVerbose = TRUE),
+                merged1, random= ~time + log(maternal_educ)*time
|country.x, na.action=na.omit,method="ML")
  0:     11378.396: -1.65670  2.44758 -3.03894  2.00310 -34.0487 0.186837
0.0637447  49.2689 -10.3311  5.94936
  1:     11375.740: -1.68701  2.45171 -3.03866  2.00265 -34.0499 0.302840
0.0305228  49.2682 -10.3309  5.94934
  2:     11375.323: -1.68664  2.45188 -3.03838  2.00234 -34.0499 0.302036
0.0279806  49.2682 -10.3309  5.94934
  3:     11375.161: -1.68509  2.45164 -3.03478  1.99830 -34.0500 0.301491
0.0299300  49.2682 -10.3309  5.94939
  4:     11374.835: -1.68137  2.45134 -3.03272  1.99601 -34.0499 0.290639
0.0313596  49.2682 -10.3310  5.94943
  5:     11361.671: -1.63878  2.45243 -2.66545  1.58982 -34.0573 0.726526
-0.0906120  49.2606 -10.3367  5.95909
  6:     11359.791: -1.65178  2.44927 -2.57664  1.47997 -34.0610 0.975864
-0.170656  49.2572 -10.3386  5.96736
  7:     11359.595: -1.65004  2.45965 -2.56790  1.46837 -34.0612  1.00787
-0.168258  49.2564 -10.3397  5.97066



132:     11307.797: -1.39340  3.37422 0.317114 0.526105 -90.6641  44.6928
-13.9187  667.927 -208.799  26.9546
133:     11307.797: -1.39346  3.38002 0.320773 0.526102 -91.1985  45.1140
-14.0518  675.133 -211.078  27.0564
134:     11307.796: -1.39350  3.38197 0.321697 0.525758 -91.3801  45.2651
-14.0996  677.663 -211.877  27.0798
135:     11307.795: -1.39360  3.38872 0.325211 0.525153 -92.0139  45.7838
-14.2635  686.411 -214.643  27.1729
136:     11307.794: -1.39365  3.39553 0.329183 0.525088 -92.6545  46.2974
-14.4259  695.158 -217.409  27.2829
137:     11307.792: -1.39368  3.40218 0.332937 0.525082 -93.2910  46.8111
-14.5883  703.905 -220.176  27.3876
138:     11307.791: -1.39373  3.40895 0.337031 0.525186 -93.9332  47.3224
-14.7500  712.652 -222.942  27.5031
139:     11307.790: -1.39378  3.41494 0.341038 0.525609 -94.5084  47.7708
-14.8918  720.413 -225.398  27.6206
140:     11307.789: -1.39382  3.41930 0.344713 0.526541 -94.9384  48.0868
-14.9919  726.060 -227.188  27.7364
141:     11307.788: -1.39387  3.42361 0.347375 0.526566 -95.3534  48.4155
-15.0959  731.709 -228.975  27.8133
142:     11307.788: -1.39393  3.42785 0.349776 0.526344 -95.7643  48.7467
-15.2006  737.357 -230.762  27.8810
143:     11307.787: -1.39401  3.43137 0.351265 0.525645 -96.1084  49.0365
-15.2922  742.207 -232.294  27.9192
144:     11307.786: -1.39407  3.43484 0.352910 0.525314 -96.4518  49.3214
-15.3823  747.014 -233.815  27.9635
145:     11307.786: -1.39410  3.43839 0.354938 0.525329 -96.8011  49.6024
-15.4711  751.820 -235.335  28.0217
146:     11307.786: -1.39410  3.43839 0.354938 0.525329 -96.8011  49.6024
-15.4711  751.820 -235.335  28.0217
Error in lme.formula(log(child_mortality) ~ time + log(maternal_educ) +  :
  nlminb problem, convergence error code = 1
  message = function evaluation limit reached without convergence (9)
>

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