Thank you very much Ben.

Yes, I forgot to convert lure to a factor.  Sorry.  The following is the 
output with lure converted, but I guess your comments still holds, right?

Best,

Manuel

 > mod1 = lmer(Swiftness.1 ~ Lure + Sex + Facility.Size + (1|Subject), 
data = otter)
 > summary(mod1)
Linear mixed model fit by REML
Formula: Swiftness.1 ~ Lure + Sex + Facility.Size + (1 | Subject)
    Data: otter
   AIC  BIC logLik deviance REMLdev
  1242 1271 -609.8     1300    1220
Random effects:
  Groups   Name        Variance Std.Dev.
  Subject  (Intercept)     0      0.00
  Residual             21946    148.14
Number of obs: 102, groups: Subject, 17

Fixed effects:
                Estimate Std. Error t value
(Intercept)      91.000     46.981   1.937
Lure2           -30.235     50.812  -0.595
Lure3            -9.059     50.812  -0.178
Lure4           -27.176     50.812  -0.535
Lure5            10.706     50.812   0.211
Lure6           -64.941     50.812  -1.278
Sex1             -3.266     29.461  -0.111
Facility.Size2   24.174     37.966   0.637
Facility.Size3   58.528     39.039   1.499

Correlation of Fixed Effects:
             (Intr) Lure2  Lure3  Lure4  Lure5  Lure6  Sex1   Fcl.S2
Lure2       -0.541
Lure3       -0.541  0.500
Lure4       -0.541  0.500  0.500
Lure5       -0.541  0.500  0.500  0.500
Lure6       -0.541  0.500  0.500  0.500  0.500
Sex1        -0.314  0.000  0.000  0.000  0.000  0.000
Facilty.Sz2 -0.495  0.000  0.000  0.000  0.000  0.000 -0.055
Facilty.Sz3 -0.499  0.000  0.000  0.000  0.000  0.000  0.000  0.617


On 18/03/2011 06:51 a.m., Ben Bolker wrote:
> On 11-03-18 08:19 AM, Manuel Spínola wrote:
>> Dear list members,
>>
>> I am trying to fit a linear mixed model using the following variables::
>>
>> Response variable:
>>
>> Swiftness.2 (This is the time it took for the otter to first approach
>> the lure.  The time ranges from 1 second (in which case the otter
>> approached the lure almost immediately) to 600 seconds (10 minutes).
>>
>> Explanatory variables:
>> 1) Subject (this is the individual otter -- each otter is measured for
>> response to each lure, so it is a repeated measure on the individual);
>> 2) sex;
>> 3)  facility size (small, med, large);
>> 4) lure type (there were 6).
>>
>> I would like to see if the response variable is influenced by the
>> explanatory variables including Subject like a "repeated measure" term
>> (same animal expose to different lures).
>>
>> I am fitting the model:
>>
>> otter$Facility.Size = factor(otter$Facility.Size)
>> otter$Sex = factor(otter$Sex)
>>
>> mod1 = lmer(Swiftness.1 ~ Lure + Sex + Facility.Size + (1|Subject), data
>> = otter)
>> summary(mod1)
>>
>>   >  mod1 = lmer(Swiftness.1 ~ Lure + Sex + Facility.Size + (1|Subject),
>> data = otter)
>>   >  summary(mod1)
>> Linear mixed model fit by REML
>> Formula: Swiftness.1 ~ Lure + Sex + Facility.Size + (1 | Subject)
>>      Data: otter
>>     AIC  BIC logLik deviance REMLdev
>>    1277 1295 -631.3     1302    1263
>> Random effects:
>>    Groups   Name        Variance Std.Dev.
>>    Subject  (Intercept)     0      0.00
>>    Residual             21558    146.83
>> Number of obs: 102, groups: Subject, 17
>>
>> Fixed effects:
>>                  Estimate Std. Error t value
>> (Intercept)      92.883     44.711   2.077
>> Lure             -6.286      8.513  -0.738
>> Sex1             -3.266     29.199  -0.112
>> Facility.Size2   24.174     37.628   0.642
>> Facility.Size3   58.528     38.692   1.513
>>
>> Correlation of Fixed Effects:
>>               (Intr) Lure   Sex1   Fcl.S2
>> Lure        -0.666
>> Sex1        -0.327  0.000
>> Facilty.Sz2 -0.516  0.000 -0.055
>> Facilty.Sz3 -0.519  0.000  0.000  0.617
>>
>>
>> Is the model a plausible model and is it well parameterized?
>    Plausible, yes, except that you have apparently failed to
> transform Lure into a factor -- as it stands, lmer is treating
> it as a continuous covariate.
>    Effects seem quite small.
>    I would worry a little about your distribution, because I would guess
> that elapsed times are likely to be skewed.  Have you looked at the
> residuals/thought about log-transforming?
>     You are getting zero variance for the random effect (and a huge
> residual variance), which suggests a general lack of power.
>
>    Ben Bolker
>
>
>


-- 
*Manuel Spínola, Ph.D.*
Instituto Internacional en Conservación y Manejo de Vida Silvestre
Universidad Nacional
Apartado 1350-3000
Heredia
COSTA RICA
mspinola@una.ac.cr
mspinola10@gmail.com
Teléfono: (506) 2277-3598
Fax: (506) 2237-7036
Personal website: Lobito de río 
<https://sites.google.com/site/lobitoderio/>
Institutional website: ICOMVIS <http://www.icomvis.una.ac.cr/>

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