*Dear R experts:*
*
*
*I am running R version 2.12.1 on Windows 2007. I am studying the effects
maternal behavior in the body condition of sea lion pups from California. *

*
*

*I'm trying to make a hierarchical linear model*

*When I run the full model if I get these results:*

*> LevelModel7 <- lme(PBC ~ Sex*Dur.nurse + Sex*Freq.interaction +
Sex*Density.females , random=~Sex|Trip, data=Dataset)*

*> summary (LevelModel7)*

*Linear mixed-effects model fit by REML*

* Data: Dataset*

*       AIC      BIC    logLik*

*  446.1461 478.1074 -211.0730*

* *

*Random effects:*

* Formula: ~Sex | Trip*

* Structure: General positive-definite, Log-Cholesky parametrization*

*            StdDev    Corr *

*(Intercept) 0.5250613 (Intr)*

*Sex         0.0614132 0    *

*Residual    1.4865472      *

* *

*Fixed effects: PBC ~ Sex * Dur.nurse + Sex * Freq.interaction + Sex *
Density.females*

*                         Value Std.Error  DF    t-value p-value*

*(Intercept)            3.32002 13.521223 105  0.2455415  0.8065*

*Sex                    0.76586  1.584268 105  0.4834144  0.6298*

*Dur.nurse              1.95957  1.798351 105  1.0896502  0.2784*

*Freq.interaction      -0.22624  0.219637 105 -1.0300505  0.3054*

*Density.females      -32.19456 19.335512 105 -1.6650480  0.0989*

*Sex:Dur.nurse         -0.21788  0.209796 105 -1.0385351  0.3014*

*Sex:Freq.interaction   0.02165  0.025693 105  0.8426169  0.4014*

*Sex:Density.females    3.15918  2.258348 105  1.3988881  0.1648*

* Correlation:*

*                     (Intr) Sex    Dr.nrs Frq.nt Dnsty. Sx:Dr. Sx:Fr.*

*Sex                  -0.998                                         *

*Dur.nurse            -0.928  0.924                                  *

*Freq.interaction     -0.194  0.195  0.103                           *

*Density.females       0.613 -0.609 -0.809 -0.346                    *

*Sex:Dur.nurse         0.928 -0.928 -0.996 -0.109  0.802             *

*Sex:Freq.interaction  0.196 -0.198 -0.108 -0.994  0.353  0.108      *

*Sex:Density.females  -0.611  0.609  0.802  0.354 -0.991 -0.807 -0.350*

* *

*Standardized Within-Group Residuals:*

*        Min          Q1         Med          Q3         Max*

*-2.46806088 -0.47865795 -0.05134942  0.57369682  2.64445772*

* *

*Number of Observations: 114*

*Number of Groups: 2*

* *

*When I run simple models (one variable included: females Density,
 Frequency interaction) I have no problem either.*

* *

*> LevelModel3 <- lme(PBC ~ Sex*Density.females , random=~Sex|Trip,
data=Dataset)*

*> summary (LevelModel3)*

*Linear mixed-effects model fit by REML*

* Data: Dataset*

*       AIC      BIC    logLik*

*  428.5119 450.1158 -206.2560*

* *

*Random effects:*

* Formula: ~Sex | Trip*

* Structure: General positive-definite, Log-Cholesky parametrization*

*            **StdDev       Corr *

*(Intercept) 1.076517e+00 (Intr)*

*Sex         5.258193e-05 0    *

*Residual    1.489254e+00      *

* *

*Fixed effects: PBC ~ Sex * Density.females*

*                         Value Std.Error  DF   t-value p-value*

*(Intercept)          14.774095  4.876298 109  3.029777  0.0031*

*Sex                  -0.646479  0.566328 109 -1.141528  0.2562*

*Density.females     -18.980461 10.099637 109 -1.879321  0.0629*

*Sex:Density.females   1.892986  1.185115 109  1.597302  0.1131*

* Correlation:*

*                    (Intr) Sex    Dnsty.*

*Sex                 -0.984             *

*Density.females     -0.857  0.862      *

*Sex:Density.females  0.855 -0.869 -0.995*

* *

*Standardized Within-Group Residuals:*

*         Min           Q1          Med           Q3          Max*

*-2.678669640 -0.591855777  0.006108111  0.543417969  2.424555266*

* *

*Number of Observations: 114*

*Number of Groups: 2*



*> LevelModel4 <- lme(PBC ~ Sex*Freq.interaction , random=~Sex|Trip,
data=Dataset)*

*> summary (LevelModel4)*

*Linear mixed-effects model fit by REML*

* Data: Dataset*

*       AIC      BIC    logLik*

*  451.1833 472.7872 -217.5917*

* *

*Random effects:*

* Formula: ~Sex | Trip*

* Structure: General positive-definite, Log-Cholesky parametrization*

*            **StdDev       Corr *

*(Intercept) 1.934101e+00 (Intr)*

*Sex         3.442453e-05 0    *

*Residual    1.527767e+00      *

* *

*Fixed effects: PBC ~ Sex * Freq.interaction*

*                         Value Std.Error  DF   t-value p-value*

*(Intercept)          12.595151  4.211533 109  2.990633  0.0034*

*Sex                  -0.535742  0.465667 109 -1.150484  0.2525*

*Freq.interaction     -0.334393  0.199095 109 -1.679564  0.0959*

*Sex:Freq.interaction  0.039834  0.023241 109  1.713935  0.0894*

* Correlation:*

*                     (Intr) Sex    Frq.nt*

*Sex                  -0.943             *

*Freq.interaction     -0.745  0.783      *

*Sex:Freq.interaction  0.743 -0.788 -0.996*

* *

*Standardized Within-Group Residuals:*

*        Min          Q1         Med          Q3         Max*

*-2.79224714 -0.46765869 -0.04400343  0.66192444  2.53486123*

* *

*Number of Observations: 114*

*Number of Groups: 2*

* *

* *

*However, when I include only variable Dur.nurse, I get the following error
message:*

> LevelModel2 <- lme(PBC ~ Sex*Dur.nurse, random=~Sex|Trip, data=Dataset)

Error in lme.formula(PBC ~ Sex * Dur.nurse, random = ~Sex | Trip, data =
Dataset) :

  nlminb problem, convergence error code = 1

  message = iteration limit reached without convergence (9)



*We thought it was a problem with the number of iterations and I increased
the iterations, but I still get the error:*

> LevelModel1 <- lme(PBC ~ Sex*Dur.nurse, random=~Sex|Trip, data=Dataset,
control=lmeControl(maxIter=200))

Error in lme.formula(PBC ~ Sex * Dur.nurse, random = ~Sex | Trip, data =
Dataset,  :

  nlminb problem, convergence error code = 1

  message = iteration limit reached without convergence (9)



*Somebody has any idea?*



*Thanks and regards*

*Karina*

-- 
Biol. Karina Villegas Cervantes
Estudiante de Maestría PCMyL - UNAM

Laboratorio de Ecologia de Pinnipedos Burney J. Le Boueuf.
CICIMAR-IPN
Av. Instituto Politecnico Nacional s/n.Col.Playa Palo de Santa Rita
La Paz Baja California Sur, Mexico.

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