Re: Question about analysis of longitudinal data

Posted by Norberto Hernandez on Oct 25, 2016; 3:42pm
URL: http://spssx-discussion.165.s1.nabble.com/Question-about-analysis-of-longitudinal-data-tp5733371p5733384.html

Yhank you very much Chris, Davis and Rich. Actually it is possible to have seasonal trend, I'm thinking using ARIMA for the description of overall trend, but I don't know if ARIMA may be used for compare admission by year.

2016-10-24 16:59 GMT-05:00 Rich Ulrich <[hidden email]>:

The advisors here seem to be jumping ahead of the measurements.

A paired t-test for year 1 to year 2, for each hospital, will give the 32 averages, per week, for admissions, along with a

t-test whose p-value gives an indication of growth (positive or negative) and how systematic it is.  Comparing year 1 to

year 2 seems like an obvious way to present the data, so this is a start.  The t-test is useful because you can't readily

say that an "increase of 1.1"  per week is as meaningful in a large city as in a small one.

Auto-regression is a popular way to model, but it might be overkill at the start.  Do you care if there are seasonal trends?

--
Rich Ulrich

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From: SPSSX(r) Discussion <[hidden email]> on behalf of Norberto Hernandez <[hidden email]>
Sent: Monday, October 24, 2016 1:39 PM
To: [hidden email]
Subject: Re: Question about analysis of longitudinal data

 

Thank you very much Chris, but I am not sure if MLM could be used. I "knew" that MLM relies in the a priori specification of the different groups, and in my case the hospitals with "growing admission" and "stable admissions" are not specified. Am I correct?? Or I need to classify hospitals in "growing admission" and "stable admissions" before MLM analisys.

Thanks a lot

2016-10-24 12:01 GMT-05:00 Chris Stride <[hidden email]>:

Longitudinal MLM would be the most appropriate choice, observations (timepts) nested within cities. Will give equivalent results to LGM at most basic level.

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From: [hidden email]
Sent: ‎24/‎10/‎2016 17:37
To: [hidden email]
Subject: Question about analysis of longitudinal data

Hello everybody!! I'm asking for your kind advice because I have a consolidated weekly data of hospital admissions for the las 2 years (104 observation points) of 32 cities. I'm looking to estimate the mean growth of hospital admissions over this period, but a visual inspection of the data suggest that some cities shows a growth in hospital admission but others has stable records over time (admissions did not vary over time)

My first idea was use LGM, but i have no access to Mplus or Lisrel (I have no licence of this packages), so I want tos ask you suggest me any idea for analyse this set.

Any help or reference will be gratefully received.

Kind Regards

Norberto

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