Thanks again Richard it certainly is a disadvantage to what i am doing. I just want to be clear I understood you comment correctly. In my case the DV is how related a person's job is to thier formal education. So it could be that my immigrant group maybe has a lower standard of what an education-related job is compared to the Canadian-born. Maybe the Canadian-born is more picky in terms of what they think a related job is to immigrants. Thus, comparison between these groups is not really 100% valid. Any advantage of immigrants, for example, could simply be due to this different interpretation of the depedent variable?
Is there anyway to tease this out of the data? Cause I find that the threshold parameters are much lower for immigrants than the canadian-born. And in these models means that their predicated probabilities will be higher (lower) for the highest (lowest) category. Can I interpret this as evidence for immigrants just having a lower standard?
One of the interpretation problems that I am having, interms of understanding my results, is that I find that some of my explanitory variables (most relevant is the effect of education) is lower for immigrants thus reducing their predicted probabilities relative to the Canadian-born. But at the same time the lower cut points completely offset this disadvantage. Thus, I am finding that the effect of immigrants foreign education is much lower than the canadian-born's education. But when I look at differences in the prediected probabilities these two groups are generally on par with each other. So overall immigrants are not at an overall disadvantage in terms of finding jobs related to their education but their foreign education (one of the most important effects) has a much lower impact. And the reason for this is simply because of these cut point parameters being so low compared to the Canadian-born. Can I say that these results could be a result of an immigrant's lower st!
andard in terms of what they think a related job is? I am just a little confused on this.
Sorry to pester you. I am a bit new to empircal research and really appreciate your input.
Thanks,
Jason
________________________________________
From: [email protected] [[email protected]] On Behalf Of Richard Williams [[email protected]]
Sent: Thursday, May 07, 2009 12:03 PM
To: [email protected]; [email protected]
Subject: Re: st: St: Ordered Logit Question
At 06:15 PM 5/6/2009, Jason Dean, Mr wrote:
>I am running two ordered logits equations. One for immigrants and
>one for the native-born. Each has the exact same independent and
>dependent variables. There are 3 categories for the depedent
>variable. I find that the threshhold parameters are quite different
>for these two groups. Specifically, both cutpoints are much lower
>for immigrants. Can anyone enlighten me as to how I should interpret
>this? To me this means, all else equal, immigrants are much more
>likely to be in the highest category and much less likely to be in
>the lowest category. Can I just interpret this in a similar manor as
>if these two groups had different intercepts in a linear regression?
>Also, is it appropriate to compare marginal effects between
>immigrants and the native-born.
>
>Any help would be greatly appreciated.
In general, I don't recommend eyeball comparisons of separate models
estimated on different populations, and I especially don't recommend
it with techniques like ordinal regression. Without going into all
the gory details, it can have much the same problems that comparing
standardized coefficients across populations does. (If you do want
the gory details, see
http://www.nd.edu/~rwilliam/oglm/RW_Hetero_Choice.pdf and/or
http://www.nd.edu/~rwilliam/oglm/oglm_Stata.pdf ).
Suppose you follow Clive's advice and estimate a pooled model with a
dummy variable for group membership, and suppose the coefficient for
that dummy is significant and positive. The usual interpretation is
that, when all other things are equal, members of one group tend to
score higher on your dependent variable than do members of the other group.
The more annoying possibility, that you may at least want to
consider, is that there is "index shift", i.e. people are using
different criteria when responding to the question. So, for example,
suppose the question has to do with pain and the options are "Lot of
pain, moderate pain, little or no pain." A man and a woman might
feel the same amount of pain; but if men tend to be big babies, a man
might say he has a lot of pain while a woman with the same amount of
pain would only say it was moderate.
Or, suppose the DV has something to do with accomplishments or
abilities. If one culture tends to be more modest than the other, it
might tend to report lower values on the ordinal DV than the other
does even if the level of accomplishments/abilities is identical.
Put another way, there is always the question of whether observed
differences are real or whether they are artifacts of group
differences in measurement. Cross-group differences in measurement
are going to be problematic in any analysis; but they may be
especially problematic with an ordinal DV. With an ordinal DV, you
are usually (or at least often) thinking that it is a collapsed
version of some underlying continuous DV, e.g. pain falls along a
continuum, it doesn't have just 3 values. The problem is that people
decide for themselves how the collapsing should be done, and there is
nothing that says all members of all groups are going to do it the same way.
I must say that, the more I learn about categorical data analysis,
the more I think you should kill to try to get variables that work in
an OLS-type framework... :)
-------------------------------------------
Richard Williams, Notre Dame Dept of Sociology
OFFICE: (574)631-6668, (574)631-6463
HOME: (574)289-5227
EMAIL: [email protected]
WWW: http://www.nd.edu/~rwilliam
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