re: Re: st: Nonparametric Methods for Longitudinal Data

["Ariel Linden, DrPH" <ariel.linden@gmail.com>]

This had been a fantastic thread, and the contributors have done an
excellent job is discussing the very salient points.

I would like to point Thomas to chapter 7 of Rabe-Hesketh & Skrondal*, where
they give specific direction for using GLLAMM (findit gllamm) for ordinal
outcomes in a longitudinal context. I've used the approach before for a
similar problem...

Ariel


* Rabe-Hesketh S, Skrondal A: Multilevel and Longitudinal Modeling Using
Stata, (2nd Ed.). College Station, TX: Stata Press, 2008.

Date: Mon, 11 Feb 2013 17:06:09 +0000
From: Ronan Conroy <rconroy@rcsi.ie>
Subject: Re: st: Nonparametric Methods for Longitudinal Data

On 2013 Feabh 11, at 13:32, Thomas Herold wrote:

> Dear Nick,
> 
> Thank you very much for your answer.
>> Questions like this raise more questions in their wake.
>> 
>> It is a bit puzzling that you have apparently only just discovered how
your response variable is defined. However, many medical and psychiatric
analyses make use of scores usually devised according to the answers to
multiple questions. They often work at least
>> approximately like measured variables; many researchers would argue that
treating them as ordinal is too pessimistic and indeed there are
>> usually too many distinct values for many standard models for ordinal
responses to work well.
>> 
>> IQ is an example familar to many.
> I have not been involved in the design of the study. I was just asked to
evaluate it. You certainly have a point when you say that my approach might
be too pessimistic. However, it seems to be common belief that the scale I
am talking about (Hospital Anxiety and Depression Scale - HADS) only
generates ordinal data. And if we take this seriously we have to admit that
one basic assumption of parametric analysis is not fulfilled. Would you
agree with that?

The HADS is a nightmare. See

1.	Cosco TD, Doyle F, Ward M, Mcgee H. Latent structure of the Hospital
Anxiety And Depression Scale: A 10-year systematic review. J Psychosom Res.
Elsevier Inc; 2011 Sep 13;:1?5. 
2.	Coyne JC, van Sonderen E. No further research needed: Abandoning the
Hospital and Anxiety Depression Scale. J Psychosom Res. Elsevier B.V; 2012
Jan 12;:1?2. 

I would disagree that it's a common belief that it generates ordinal data.
On the contrary, HADS scores are frequently analysed using regression
models. 

Ordinal data need not mean that no parameters can be calculated. I have been
experimenting with logistic quantile regression (see lqreg). 



> 
>> 
>> Statistically, it's a myth on several levels that "parametric analysis"
requires a response variable to be normally distributed. At
>> most, it's a secondary assumption of some regression-like methods that
error disturbances be normally distributed. There are also many
>> methods that are not non-parametric for other distributions (exponential,
gamma, etc., etc.).  Also, what about transformations or
>> similar link functions.
>> So, manifestly I can't see your data but I'd suggest that your impression
that you need quite different methods is jumping to conclusions prematurely.
>> 
> Again, I could not agree more. However, that does not really answer my
question. You have to know that my statistical background knowledge is
limited. For example, I would have thought that using parametric methods for
ordinal data is not only "optimistic" but simply wrong.
> Therefore, I would highly appreciate it if you (or someone else) could
tell me a regression type that is supported by Stata (sorry for the spelling
error in my first post) and might be worth having a look at in this context.
> 
> Many thanks,
> Thomas
> 
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/faqs/resources/statalist-faq/
> *   http://www.ats.ucla.edu/stat/stata/

Ronán Conroy
rconroy@rcsi.ie
Associate Professor
Division of Population Health Sciences
Royal College of Surgeons in Ireland
Beaux Lane House
Dublin 2




*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/