Stata The Stata listserver
[Date Prev][Date Next][Thread Prev][Thread Next][Date index][Thread index]

Re: st: regression models with small number of clusters

From   Roger Newson <[email protected]>
To   [email protected]
Subject   Re: st: regression models with small number of clusters
Date   Thu, 06 Jan 2005 21:44:01 +0000

Krishna doesn't tell us which "factors" are being assessed as predictors of patient satisfaction. However, I think I would probably use a fixed-effects model here. It seems more realistic to calculate clinic-adjusted mean satisfaction differences (or geometric mean satisfaction ratios) for the population of patients in these 12 clinics than to attempt to make inferences about the population of clinics at large, based on such a small sample of clinics.

Hope this helps.


At 22:06 05/01/2005, Krishna wrote:

Dear All:

I had previously posted this and would like to thank
Roger Newson for his reply. Here is my problem in more

I am trying to fit a regression model to data which
was generated from cluster sampling. There are 12
clusters (clinics) and the  average cluster size is
around 30. The outcome of interest is a continuous
variable (patient satisfaction) and I am interested in
the factors which affect it. Since the data is
clustered and it is potentially correlated, I need to
adjusted for this in my regression model. What would
be the appropriate regression technique/model to do
this ? I understand that models such as multiple
regression with sandwich estimator (regress with
cluster option), and GEE are not appropriate as they
require a large number of clusters to provide
consistent estimates. Would a Random Effects (xtreg,
re) or Fixed Effects (xtreg, fe) model be appropriate
? Are there any others you would recomend ? Many
thanks for all your help..

Best regards
Dept. of International Health
Johns Hopkins University

Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
King's College London
5th Floor, Capital House
42 Weston Street
London SE1 3QD
United Kingdom

Tel: 020 7848 6648 International +44 20 7848 6648
Fax: 020 7848 6620 International +44 20 7848 6620
  or 020 7848 6605 International +44 20 7848 6605
Email: [email protected]

Opinions expressed are those of the author, not the institution.

*   For searches and help try:

© Copyright 1996–2024 StataCorp LLC   |   Terms of use   |   Privacy   |   Contact us   |   What's new   |   Site index