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Hi all

Sorry to bother you again. I have a problem of missing estimates when I look the output of models using time-covariate in age models.

To give you a rapid description of my models. I have three age-classes (young, mature, old):

vaut.ddl.age$S$a0=0
vaut.ddl.age$S$a0[vaut.ddl.age$S$Age==0]=1
vaut.ddl.age$S$a4_27=0
vaut.ddl.age$S$a4_27[vaut.ddl.age$S$age_covar=="[4,28)"]=1
vaut.ddl.age$S$a28_37=0
vaut.ddl.age$S$a28_37[vaut.ddl.age$S$age_covar=="[28,37]"]=1

If I do time-covariate models with 3 different intercepts and 3 different slopes on survival as :

S(~-1 + a0 + a1_27 + a28_37 + a0:Tmax + a1_27:Tmax + a28_37:Tmax)

as expected, I have 6 beta parameters which are estimated (3 intercepts and 3 slopes) but when I look real parameter estimates, I see that some years (normally 31 years) are not estimated. It is the same years for all age-classes. For old age class, I cannot have estimates before 2003 but it is normal. But for example the survival estimates of 2009 are missing for all age-classes and I do not understand why.

When I use other time-covariates, some years were also missing (but not the same)

I do not have problems when I fit temporal trend (with ~Time)

Has someone already encountered this problem ? What am I doing wrong?

Why Mark cannot estimate these parameters?

Thank in advance for treply

stephane

Did you check your design data to make sure it is all correctly specified? If it is and you are still having a problem you'll have to send the code and data to me offlist. Hard to tell otherwise. --jeff

Hi jeff

thank for the reply

I don't see any problem in the design matrix

ok I will contact you offlist

stephane

Hi all

I have discussed with Jeff offlist and he found the reason of my missing real estimates

the answer

When you have individual covariates the real values it provides are only for a specific set of values for those covariates. A simple example that is more obvious than your example, if you had a single covariate say mass that was a predictor for survival then there are many different real survival possible survival values but the output from MARK only provides the estimates for a single value of mass. To compute the real values for the various combinations of covariate values you need to use the function covariate.predictions."

In my data, I use temperature as covariate and for some year I have the same temperature, so the mark output only provided real estimates for one of these years.

I hope this could help someone

Stephane