Alive-----------Death
|
Lives in the address ----|----Has moved
|
|
At home ------|-----Absent
| Long absence
|
Interviewed --|---- Refuses
Angel Rodriguez-Laso
El día 10 de febrero de 2010 14:33, Ángel Rodríguez Laso
<[email protected]> escribió:
> Dear Maarten,
>
> I've read with interest your message describing the -seqlogit- package
> and your dissertation chapter where you apply it to describe
> inequalities of educational opportunities. I was thinking about the
> application of this model to outcomes of contact in a survey. I would
> appreciate your opinion very much.
>
> The possibilities of the outcome are incorporated to the variable
> inciden, with the codes: 1. death 2. moved 3. absent 4. long absence
> 5. refuses 6. interviewed. Of course there were more possibilities,
> but they were either too infrequent (incorrect address, hospitalised,
> ill, doesn’t speak Spanish) or equivocal (other). I understand these
> categories as steps in a continuum from being death to willing to
> participate in the survey that can be described as a tree (sorry, I
> have't managed to get a better presentation):
>
> Alive
> ------------------------------ Death
> |
> Lives in the address ----------|----------
> Has moved
> |
> |
> At home -----------|-------------- Absent
> | Long absence
> |
> Interviewed -----|------ Refuses
>
>
>
>
> The explanatory variables are sex (dichotomus), age (continuous; with
> allowance for non-linearity using mkspline), rent (continuous; mean
> rent of the census tract were the resident lives) and origin
> (categorical: Spanish, Latin-American, Eastern European, high-income
> countries, other).
>
> There is a cluster variable: censustract
>
> My first idea was to run logistic models with the dependent variables:
> death/alive, moved/living in the address, refuses/interviewed, and
> restricting the sample to those who have passed the previous
> transition (i.e. excluding death individuals in the model for
> moved/living in the address). There was also a multinomial model with
> the categories at home/absent/long absence. Nevertheless, I've come to
> the conclusion that -seqlogit- is a better alternative because it
> assesses the influence of each variable on the outcome of interest
> (being interviewed).
>
> What I would type then is:
>
> mkspline age1 30 age2 65 age3 = age
> xi?: seqlogit inciden sex age1 age2 age3 rent i.origin, tree(1:2 3 4 5
> 6, 2:3 4 5 6, 3 4?: 5 6, 5:6) ofinterest (sex?) over(origin age1 age2
> age3) levels(?) or cluster(censustract)
>
> I've included question marks where I have problems:
>
> 1) There is a categorical independent variable. Can xi be used with -seqlogit-?
>
> 2) One step of the process has three branches instead of two (at home,
> absent, long absence). Can this be modelled with -seqlogit-? Is 3 4:5
> 6 the correct way to define it?
>
> 3) It is difficult for me to give levels to the categories. Of course,
> being interviewed is the desired outcome, but I cannot say that it is
> x times more important that other outcomes, as you do in your
> dissertation. On the other hand, these other outcomes would definitely
> have to have the same value.
>
> 4) In this example, I try to decompose the effect of the variable sex,
> but I would like to investigate the decomposition of the effects of
> other explanatory variables. I suppose I only need to change the other
> variables for sex in ofinterest. I’m interested in the interaction:
> sex*origin and sex*age1 sex*age2 sex*age3. I’ve understood that the
> options ofinterest (sex) over(origin age1 age2 age3) generate the
> interaction terms.
>
> Many thanks for your time and interest.
>
>
> Angel Rodriguez-Laso
>
>
> 2010/1/22 Maarten buis <[email protected]>:
>> Thanks to Kit Baum an update of the -seqlogit- package is now
>> available from SSC. The -seqlogit- package can be used to study
>> a sequence of discrete events, for example some respondents
>> finish high school and others not, and those who finished high
>> school can either finish college or not. The -seqlogit- package
>> allows one to additionally study the interelationship between
>> effects of covariates on the individual transitions and the
>> effects of these covariates on the final outcome (in this case
>> highest achieved level of education). Moreover, it contains
>> tools for doing a sensitivity analysis regarding the potential
>> influence of unobserved heterogeneity. A describtion can be
>> found here: <http://www.maartenbuis.nl/software/seqlogit.html>.
>>
>> This update contains a fix for a bug that was introduced in Stata
>> 11, which made -uhdesc-, one of the tools for doing a sensitivity
>> analysis, fail to work.
>>
>> This package can be updated by typing in Stata -ssc instal seqlogit, replace-.
>>
>> -- Maarten
>>
>> --------------------------
>> Maarten L. Buis
>> Institut fuer Soziologie
>> Universitaet Tuebingen
>> Wilhelmstrasse 36
>> 72074 Tuebingen
>> Germany
>>
>> http://www.maartenbuis.nl
>> --------------------------
>>
>>
>>
>>
>> *
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>>
>
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