Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down on April 23, and its replacement, is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

Re: st: Nonparametric Methods for Longitudinal Data

From   Ronan Conroy <>
To   "<>" <>
Subject   Re: st: Nonparametric Methods for Longitudinal Data
Date   Mon, 11 Feb 2013 17:06:09 +0000

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:
> *
> *
> *

Ronán Conroy
Associate Professor
Division of Population Health Sciences
Royal College of Surgeons in Ireland
Beaux Lane House
Dublin 2

*   For searches and help try:

© Copyright 1996–2016 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index