Hello,

2010/3/26 David Duffy <David.Duffy@qimr.edu.au>

> On Thu, 25 Mar 2010, Christophe Dutang wrote:
>
>  I try to model a binary response variable over a small period of time. The
>>>> problem is that for some lines, the response is missing. In this mailing
>>>> list archive, I do not find response to this question.
>>>>
>>>>  fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)
>> sleepstudy2 <- sleepstudy
>> sleepstudy2[180, "Reaction"] <- NA
>> fm2 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy2)
>>
>> What am I doing wrong?
>>
>
> This worked perfectly, did it not?

the observation number is reduced by 1.


>  As Emmanuel Charpentier summarized, you can't use information from the
> "lines" where the response is missing (expect for prediction, the BLUP)
> unless you move to some type of multivariate model that explicitly models
> the interrelationships of the covariates, like the multiple imputation
> models or SEM.

I don't receive anything from E. Charpentier?!


> But in that case, all that happens is you gain a little bit of information
> about the distributions of the covariates, which may or may not influence
> your model for the response variable.
>

By "some lines are missing", I mean I don't have both the response and the
covariate. Let me explain what I'm doing. I work on default of individual.
Every 6 month for each indvidual the response variable equals to 1 if he
defaults on the period, 0 otherwise. For each time period I also observe
explanatory variables (age, job, marital status,...).

The problem is that my response is always of this pattern:
0 0 0 1
0 0 0 0
0 1 NA NA
That's wher I had missing data, after the default, I don't have any data for
that individual. And the variable is necessary a sequence of 0 with a
possible 1 at the end.

I'm trying to use something better than the logistic GLM at each time
period.

Thanks in advance for any advice

Christophe


>
> PS what are the "lines" you refer to?  What is the actual problem you are
> working on?
>
>
> --
> | David Duffy (MBBS PhD)                                         ,-_|\
> | email: davidD@qimr.edu.au  ph: INT+61+7+3362-0217 fax: -0101  /     *
> | Epidemiology Unit, Queensland Institute of Medical Research   \_,-._/
> | 300 Herston Rd, Brisbane, Queensland 4029, Australia  GPG 4D0B994A v
>



-- 
Christophe DUTANG
Ph. D. student at ISFA

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