28 Apr
2007
28 Apr
'07
3:55 p.m.
Why would it be that Mojtabai and Olfson (2003) find that more insurance
(I assume you mean) for drug coverage leads to higher levels of
cost-related nonadherence? that seems strange.
i'd try to make the abstract shorter. about 150 words. also, the
abstract is not (only) about what you did. its about what's news. you
need to make the case that your results are worth reading and publishing.
(which is why its good to start with things like "in this paper, we
demonstrate that..."). you want to get right to it.
it might be that the only news you have is that after trying more
sohpisticated methods, the original results stand up as they were
originally. that's ok if that's what you find, tho obviously that
would be less likely to be convincing to a journal. so if there is some
small piece of what you did that is different, or unusual, or new, THAT is
what I would focus the title and abstract on. you get to choose what the
reader will focus on (not the author of the paper you're replicating) .
so pick what will be to your advantage.
Gary
On Sat, 28 Apr 2007, Katy Backes Kozhimannil wrote:
Hi all,
We welcome your comments and feedback on our working title and abstract
for our paper.
Thanks,
Sheila and Katy
TITLE:
Scrimping, saving, and skipping pills: A matched analysis of how drug
coverage impacts cost-related nonadherence among elderly Americans.
ABSTRACT:
The goal of this study is to evaluate the relationship between drug
coverage and cost-related nonadherence of medicines among elderly
Americans. We used data from the 2000 wave of the Health and Retirement
Survey to further examine results presented by Mojtabai and Olfson,
2003. We used propensity score matching and a multivariate logit model
to study whether a lack of drug coverage is associated with cost-related
nonadherence. Using unmatched cohorts, Mojtabai and Olfson, (2003) finds
that an increasing levels of drug coverage is associated with increasing
levels of cost-related nonadherence. Our findings indicate that matching
attenuates point estimates but produces larger confidence intervals in
this analysis. The attenuation indicates that selection bias may not be
fully controlled in the original analysis. However, interpretation of
the substantive results does not differ greatly between the original and
matched analyses, due to the overlap in confidence intervals. In the
unmatched cohort the sample average treatment effect estimate is an odds
ratio of 2.91 (2.44, 3.47) and in the matched analysis it is 2.17 (1.72,
2.75). Respondents without drug coverage in the original cohort are
about three times as likely to report cost-related nonadherence, whereas
in matched analysis, these individuals were about twice as likely to
experience cost-related nonadherence as their counterparts with drug
coverage. Similar patterns hold for specific health conditions. This
study provides evidence for the utility of propensity score matching in
observational studies where selection into treatment or exposure is not
random.
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