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# Re: st: comparing two linear slopes

 From Steven Samuels To statalist@hsphsun2.harvard.edu Subject Re: st: comparing two linear slopes Date Sun, 31 Oct 2010 09:22:28 -0400

Ashwin, I have three comments:

1. It is unlikely that hospitalizations are independent events; therefore analyses based on the independence assumption will be faulty. Non-independence could arise, for example, from: repeated hospitalizations of the same person; seasonal variation; serial correlation; clustering of events in different departments and institutions.

2. Trends in the proportions of admissions for the two diseases are affected by trends in the numbers of admissions of other diseases.

3. Formally, comparison of trends in _numbers_ of admissions for the two diseases can be directly studied in a data set that excludes all other admissions.

Perhaps a multiple time-series analyses of the two types of admissions will address these issues. This is an area I haven't worked in, so I can't begin to recommend specific Stata commands.

Steve

Steven J. Samuels
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On Oct 29, 2010, at 4:40 PM, Ashwin Ananthakrishnan wrote:

Hi,

I'm examining the rate of change of two proportions over time. I'd be grateful if someone could help me figure this out:

I'm looking at the proportional increase in two specific disease (as a proportion of all hospitalizations) over time and need to see if the rate of increase for one disease is statistically greater than the rate of increase for disease 2.

I have the sum totals for the numerators (i.e disease 1 or disease 2) and denominators (total hospitalization 1 and total hospitalizations 2) for the start and the end year (the relationship is linear for the intervening years - that's been looked at).

Is there a way to compare these two trends statistically to say that the 4-fold increase for disease 1 is significant greater than the 2- fold increase for disease 2?

Should i calculate the annual percent change for each disease and then use the two-sample t test? How i get the Std dev for the annual percent change?

Thanks,

Ashwin

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