[R] mixed-effects model with two fixed effects: interaction

[Setlhare Lekgatlhamang]

When I replied to this message I just hit the reply button. I am
resending it using reply to all, in case it did not go to the list.

Dear Ilona,

Looking at the estimation results you have, I think your regression
equations are correctly specified. Just thinking aloud, I do not think
the results are surprising. Model2 includes more (relevant) regressors
than model1. In this green house experiment, one would expect
performance in some cases to be jointly determined by the specifies and
level of moisture. In that case, the explanatory power of
non-interactive terms will drop or vanish when the interactive terms are
also included - meanwhile the interactive terms would be significant. I
may be wrong but that is my initial thought.

Regards
Lexi

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of Ilona Leyer
Sent: Tuesday, June 29, 2010 11:10 AM
To: r-help at r-project.org
Subject: [R] mixed-effects model with two fixed effects: interaction

Dear all,
In a greenhouse experiment we tested performance of 4 different species
(B,H,P,R) under 3 different water levels in 10 replications. As response
variable e.g. the number of emerging sprouts were measured on three
dates. A simple Anova considering every measurement date separately
shows a higly significant effect of species and moisture (and partly the
interaction of both). The mixed-effects model with species and moisture
shows a highly significant effect of species and moisture as well.
However, when I included the interaction the t-values of the species
dropped strongly and the SE increase and the results for the species are
not significant anymore. For me this does not seem plausible. Has
anybody an idea, how this can be interpreted and if I have done a
mistake in calculating the data? 

Thanks in advance for any help!
Ilona


model1<-lme(sprouts~species+moisture,random=~time|ID)
model2<-lme(sprouts~species*moisture,random=~time|ID)


Fixed effects: sprouts ~ species + moisture 
                         Value Std.Error  DF   t-value p-value
(Intercept)           7.971267  1.330500 240  5.991180  0.0000
speciesH             -6.459344  1.536329 114 -4.204400  0.0001
speciesP            -10.063604  1.536329 114 -6.550421  0.0000
speciesR             -5.051894  1.536329 114 -3.288288  0.0013
moisturemoist         2.228835  1.330500 114  1.675185  0.0966
moisturewaterlogged  17.111149  1.330500 114 12.860688  0.0000


Fixed effects: sprouts ~ species * moisture 
                                  Value Std.Error  DF   t-value p-value
(Intercept)                    4.831965  1.750970 240  2.759594  0.0062
speciesH                      -4.464197  2.476245 108 -1.802809  0.0742
speciesP                      -3.986787  2.476245 108 -1.610013  0.1103
speciesR                      -0.809376  2.476245 108 -0.326856  0.7444
moisturemoist                  3.505506  2.476245 108  1.415654  0.1598
moisturewaterlogged           24.766934  2.476245 108 10.001811  0.0000
speciesH:moisturemoist        -0.457291  3.501939 108 -0.130582  0.8963
speciesP:moisturemoist        -2.458125  3.501939 108 -0.701932  0.4842
speciesR:moisturemoist        -2.555356  3.501939 108 -0.729697  0.4672
speciesH:moisturewaterlogged  -5.597498  3.501939 108 -1.598400  0.1129
speciesP:moisturewaterlogged -15.538272  3.501939 108 -4.437048  0.0000
speciesR:moisturewaterlogged -10.206874  3.501939 108 -2.914635  0.0043


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