Dear List -

I am fitting some models and have a question regarding the interpretation.

When i fit the model with no interaction term   only one significant term - pollen dispersal - is significant

However when i introduce an interaction term ( based on a priori knowledge) not only do the interaction terms become significant ( A*B) but also the terms A + B become significant on there own. Furthermore, new factors become slightly significant.

Please see below for models ( sorry for formatting).

My question is, how do i interpret this? Is factor A or B significant on their own? Furthermore, what about the factor that appears significant when the interaction term is added?

Thanks for your help

Chris


NO INTERACTION TERMS

Starting model - model31 <- lmer(netf~1+(1|order/family) + endosperm + geophyte + breedingsystem + woodyness + seasonality + geophyte + fruit + pollendispersal, family=binomial)

MAM -  (by removing the factor with the highest pvalue) - model31 <- lmer(netf~1+(1|order/family) + pollendispersal, family=binomial)

Generalized linear mixed model fit by the Laplace approximation 
Formula: netf ~ 1 + (1 | order/family) + pollendispersal 
  AIC  BIC logLik deviance
 1245 1266 -618.6     1237
Random effects:
 Groups       Name        Variance Std.Dev.
 family:order (Intercept) 5.3978   2.3233  
 order        (Intercept) 0.0000   0.0000  
Number of obs: 1242, groups: family:order, 43; order, 9

Fixed effects:
                Estimate Std. Error z value Pr(>|z|)  
(Intercept)       0.9065     0.9071   0.999   0.3177  
pollendispersal  -1.7225     0.6782  -2.540   0.0111 *

INTERACTION TERM INCLUDED

Starting model - model32 <- lmer(netf~1+(1|order/family) + endosperm + geophyte + breedingsystem* woodyness + seasonality + geophyte + fruit + pollendispersal, family=binomial)

 MAM- model33 <- lmer(netf~1+(1|order/family) + breedingsystem*fruit + seasonality + fruit + pollendispersal, family=binomial)
Generalized linear mixed model fit by the Laplace approximation 
Formula: netf ~ 1 + (1 | order/family) + breedingsystem * fruit + seasonality +      fruit + pollendispersal 
  AIC  BIC logLik deviance
 1246 1287 -614.8     1230
Random effects:
 Groups       Name        Variance   Std.Dev.  
 family:order (Intercept) 4.8431e+00 2.2007e+00
 order        (Intercept) 4.2899e-11 6.5497e-06
Number of obs: 1242, groups: family:order, 43; order, 9

Fixed effects:
                     Estimate Std. Error z value Pr(>|z|)  
(Intercept)            2.9283     2.0712   1.414   0.1574  
breedingsystem        -1.4739     0.7695  -1.915   0.0554 .
fruit                 -2.4174     1.1130  -2.172   0.0299 *
seasonality            0.7199     0.4367   1.648   0.0993 .
pollendispersal       -1.6574     0.6686  -2.479   0.0132 *
breedingsystem:fruit   1.0401     0.5029   2.068   0.0386 *


Chris Mcowen
PhD Student

Room 15
Sir Harold Mitchell Building
University of St Andrews
St Andrews
Fife
KY16 9TH
UK
Phone 01334 463381 


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