Re: st: RE: FW: graphing ordinal panel data over time

[Roger Newson <r.newson@imperial.ac.uk>]

If Paul wants to track the proportions with the 3 values over time, with 
confidence limits, then Paul might define 3 identifier variables 
identifying the 3 values, and model the progress of the means 
(proportions) of these with time (possibly using -ci- with -statsby- to 
make an output dataset with 1 obs per time point), and then use 
-eclplot- to produce the confidence interval plots, Alternatively, if 
time is a continuous variable, then Paul might prefer to use a spline 
regression model of log(p/(1-p)) with respect to time, using the 
-frencurv- module of the -bspline- package to compute a spline basis 
whose parameter values are values of the spline at points on the time 
axis, and then use -logit-, -logistoc- or -glm-, with the -noconst- 
option, to define confidence intervals for the p/(1-p) values at these 
time points, and then to use -parmest- to produce an output dataset with 
1 observation per parameter and data on estimates and confidence limits, 
and then to do an end-point transformation of the confidence intervals 
to the original probability scale before plotting the confidence 
intervals over time using -eclplot-. The examples of Newson (2001) and 
Newson (2004) might be helpful here.

If Paul is principally interested in measuring the ordinal association 
of this 3-level ordinal variable with time, then the -somersd- package, 
downloadable from SSC, might provide a way to do this.

I hope this helps.

Best wishes

Roger



Newson R. 2001. Splines with parameters that can be explained in words 
to non-mathematicians. Presented at the 7th UK Stata User Meeting, 14 
May, 2001. Download from
http://ideas.repec.org/p/boc/usug01/11.html

Newson R. 2004. B-splines and splines parameterized by their values at 
reference points. (This is a manual for the bspline package, 
downloadable from the SSC archive site, and is a post-publication update 
of a Stata Technical Bulletin article.) Download from
http://www.imperial.ac.uk/nhli/r.newson/papers.htm#program_manuals


Roger B Newson BSc MSc DPhil
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton Campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: r.newson@imperial.ac.uk
Web page: http://www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/popgenetics/reph/

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

On 08/06/2010 13:16, Maarten buis wrote:
> --- Seed, Paul forwarding a.hense@jpberlin.de
> > I have got an ordered outcome variable with three values
> > over a period of 20 years. To describe the data, I want
> > to show how the three values of my outcome variable have
> > developed over time.
>
> --- On Tue, 8/6/10, Nick Cox wrote:
> > There are several possible graphs here. For example, you
> > can -contract- and then just draw line plots of frequencies
> > or percents. Another way to do it directly is using
> > -catplot- (SSC).
>
> Yet another way would be look at -proprcspline-, see
> -ssc d proprcspline- and
> <http://www.maartenbuis.nl/software/proprcspline.html>
>
> An important difference is that -proprcspline- also applies
> certain amount of smoothing, which can for example be helpful
> when some the of the periods contain relatively few cases, such
> that the changes between periods becomes too eratic.
>
> Hope this helps,
> Maarten
>
> --------------------------
> Maarten L. Buis
> Institut fuer Soziologie
> Universitaet Tuebingen
> Wilhelmstrasse 36
> 72074 Tuebingen
> Germany
>
> http://www.maartenbuis.nl
> --------------------------
>
>
>
>
>
>
>
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