[R-sig-ME] Is it possible to compute pairwise differences of LS-mean for all factors in a Generalized linear mixed model.

[Julian Gaviria Lopez]

Hi everyone,


I am fitting the next model with the glmm TMB package:

> fit_zipoisson2 <- glmmTMB(Observations ~ CAP * Time + (1|ID), data=mDATA,

ziformula=~ 1 , family=poisson)

and I obtain as output the next one:


> summary(fit_zipoisson2)

 Family: poisson  ( log )

Formula:          Observations ~ CAP * Time + (1 | ID)

Zero inflation:                ~1

Data: mDATA



     AIC      BIC   logLik deviance df.resid

  1252.8   1339.5   -604.4   1208.8      358



Random effects:



Conditional model:

 Groups Name        Variance Std.Dev.

 ID     (Intercept) 0.03325  0.1824

Number of obs: 380, groups:  ID, 19



Conditional model:

                Estimate Std. Error z value Pr(>|z|)

(Intercept)      1.29264    0.14364   8.999   <2e-16 ***

CAPinsC5        -0.70525    0.29149  -2.419   0.0155 *

CAPpreC1        -0.21058    0.21474  -0.981   0.3268

CAPpreC3        -0.14764    0.24991  -0.591   0.5547

Timem1          -0.06505    0.22609  -0.288   0.7736

Timem3          -0.11959    0.21359  -0.560   0.5755

Timem4          -0.37762    0.21934  -1.722   0.0851 .

Timem5          -0.31970    0.22905  -1.396   0.1628

CAPinsC5:Timem1  0.19259    0.47302   0.407   0.6839

CAPpreC1:Timem1 -0.73915    0.49687  -1.488   0.1368

CAPpreC3:Timem1 -1.02677    0.54285  -1.891   0.0586 .

CAPinsC5:Timem3  0.11425    0.43376   0.263   0.7923

CAPpreC1:Timem3 -0.42517    0.35701  -1.191   0.2337

CAPpreC3:Timem3 -0.14454    0.42445  -0.341   0.7335

CAPinsC5:Timem4  0.76611    0.39757   1.927   0.0440 *

CAPpreC1:Timem4  0.26068    0.32745   0.796   0.4260

CAPpreC3:Timem4 -0.06192    0.41907  -0.148   0.8825

CAPinsC5:Timem5  0.30779    0.50160   0.614   0.5395

CAPpreC1:Timem5  0.42848    0.37898   1.131   0.2582

CAPpreC3:Timem5  0.37346    0.35116   1.063   0.2876


Signif. codes:  0 �***� 0.001 �**� 0.01 �*� 0.05 �.� 0.1 � � 1



Zero-inflation model:

            Estimate Std. Error z value Pr(>|z|)

(Intercept)  -0.2467     0.1282  -1.924   0.0543 .

---

Signif. codes:  0 �***� 0.001 �**� 0.01 �*� 0.05 �.� 0.1 � � 1

How can I observe the changes of the same CAP across time? Regardless if it is the intercept or not? E.g.:
preC5 m1 vs preC5 m2
preC5 m1 vs preC5 m3
preC5 m1 vs preC5 m4
preC5 m1 vs preC5 m4

preC1 m1 vs preC1 m2
� etc.

And how can I observe the changes
of the CAPs in relation to the predictor CAP (preC5) over time? E.g.:
preC1 m1 vs preC5 m1
preC1 m1 vs preC5 m2
preC1 m1 vs preC5 m3
preC1 m1 vs preC5 m4
preC1 m1 vs preC5 m5

I look for something similar to the Least-Square means and pairwise differences functions implemented in other packages for mixed models, such as
the lmerTest:
https://cran.r-project.org/web/packages/lmerTest/lmerTest.pdf


 Thanks a lot in advance

Julian Gaviria
Neurology and Imaging of cognition lab (Labnic)
University of Geneva. Campus Biotech.
9 Chemin des Mines, 1202 Geneva, CH
Tel: +41 22 379 0380
Email: Julian.GaviriaLopez using unige.ch

	[[alternative HTML version deleted]]