DeaR mixed effect model users
I'm need some advice regarding interpretation of the lme () result. My
question is possible too basic, but I hope someone could help me with
advices (it may be valuable for other lme() new beginners).
Respons: Speed
Fixed effects: Fuel, CarMod (1,2&3), Driver (Old or Young), and
Fuel*CarMod.
Random effects: Place
Questions regarding my model, se below:
1. Is it right to interpret that CarMod2 is significant different
from CarMod1?
2. Is it right to interpret that the effect of Fuel is different in
CarMod2 compared to CarMod1?
3. Is there a guideline for reporting lme() result? I'm uncertain
whether to report this result as a table with only the estimates from
the lme () or a table with only the anova (mod1)?
mod1 <- lme(Speed ~ Fuel + Car + Driver + Fuel*Car, random=~1|
Place,data=test)
summary(mod1)
Linear mixed-effects model fit by REML
Data: test
AIC BIC logLik
261.2013 275.6996 -121.6007
Random effects:
Formula: ~1 | Place
(Intercept) Residual
StdDev: 0.0003238738 5.013858
Fixed effects: Speed ~ Fuel + Car + Driver + Fuel * Car
Value Std.Error DF t-
value p-value
(Intercept) -29.33479 12.743084 30 -2.302017 0.0285
Fuel 10.04684 1.408789 30 7.131542 0.0000
CarMod2 46.55593 14.192029 7 3.280428 0.0135
CarMod3 1.65157 18.247158 7 0.090511 0.9304
DriverYoung 26.65219 1.688643 30 15.783202 0.0000
Fuel:CarMod2 -5.53264 1.624159 30 -3.406464 0.0019
Fuel:CarMod3 -0.18452 2.010470 30 -0.091779 0.9275
Number of Observations: 44
Number of Groups: 10
numDF denDF F-value p-value
(Intercept) 1 30 8487.520 <.0001
Fuel 1 30 340.661 <.0001
Car 2 7 6.283 0.0274
Driver 1 30 235.860 <.0001
Fuel:Car 2 30 8.655 0.0011
Best regards R.S. Cotter