[R-sig-ME] Basic question about interpretation of lme () result.

[MHH Stevens]

Hi RS,
The coefficients below need to be interpreted appropriately, and  
these (presumeably treatment contrasts or dummy coding) do not  
necessarily correspond directly to ANOVA type factor tests. I suggest  
consulting one of the R books listed on the R project web site under  
"Documentation/Books."
Cheers,
Hank
On Apr 1, 2008, at 6:54 AM, R.S. Cotter wrote:
> 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
>> anova(mod1)
>                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
>
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Dr. Hank Stevens, Assistant Professor
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Miami University
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(1803-1882)