Hi,
I'm analysing a dataset in which the same 5 subjects (male.pair) were subjected
to two treatments (treatment) and were measured for 12 successive days within
each treatment (layingday). Overall 5*2*12=120 observations.
I want to test the effect of treatment, time (layingday) and their interaction.
I have done so through the ANOVA below:
> bmc3<-aov(Mean1~treatment*layingday+Error(male.pair/treatment/layingday))
> summary(bmc3)
Error: male.pair
Df Sum Sq Mean Sq F value Pr(>F)
Residuals 1 0.13850 0.13850
Error: male.pair:treatment
Df Sum Sq Mean Sq
treatment 1 0.60525 0.60525
Error: male.pair:treatment:layingday
Df Sum Sq Mean Sq
layingday 1 0.64037 0.64037
Error: Within
Df Sum Sq Mean Sq F value Pr(>F)
treatment 1 0.02015 0.02015 0.7340 0.3934
layingday 1 0.52937 0.52937 19.2878 2.545e-05 ***
treatment:layingday 1 0.02959 0.02959 1.0782 0.3013
Residuals 113 3.10135 0.02745
---
Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
I then wanted to compare this outcome with an lme, and used the model below.
However, its outcome doesn't make much sense to me.
> bmc4<- lme(Mean1 ~ treatment*layingday, random = ~1|male.pair)
> summary(bmc4)
Linear mixed-effects model fit by REML
Data: NULL
AIC BIC logLik
-118.4522 -101.9306 65.22609
Random effects:
Formula: ~1 | male.pair
(Intercept) Residual
StdDev: 0.1313573 0.1185902
Fixed effects: Mean1 ~ treatment * layingday
Value Std.Error DF t-value p-value
(Intercept) 0.5311005 0.09369140 112 5.668615 0.0000
treatment 0.0495373 0.04616116 112 1.073138 0.2855
layingday -0.0488055 0.00991701 112 -4.921389 0.0000
treatment:layingday 0.0138449 0.00627207 112 2.207388 0.0293
Correlation:
(Intr) trtmnt lyngdy
treatment -0.739
layingday -0.688 0.838
treatment:layingday 0.653 -0.883 -0.949
Standardized Within-Group Residuals:
Min Q1 Med Q3 Max
-2.44529424 -0.68505388 0.01663401 0.59009515 3.53354000
Number of Observations: 120
Number of Groups: 5
I struggle to understand the discrepancy in df between the anova and lme, and
the fact that the interaction term is not significant in the anova but
significant in lme. Any help would be greatly appreciated.
Best
Tom
--
Dr. Tommaso Pizzari
Edward Grey Institute, Dept of Zoology,
University of Oxford, Oxford OX1 3PS
Tel: (44) 1865 271279, Fax: (44) 1865 271168
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