# Re: st: RRR with CI from logit model

 From Michael Ingre <[email protected]> To [email protected] Subject Re: st: RRR with CI from logit model Date Mon, 1 Nov 2004 14:06:27 +0100

```On 2004-11-01, at 11.07, Joseph Coveney wrote:

```
Could you fit a different generalized linear model to your data? One with
directly. I'm not really sure what you mean by comparing the risk at
different levels of scale, but you can set each of the levels of scale of
the covariate as the reference level for estimating the risk ratios (and
their confidence intervals) of the other levels relative to it.
Thanks for your suggestion. It seems to be a nice solution for one set of models however, some of the information I left out complicate it a bit.

I have estimated a -gllamm , link(ologit) fam(binomial)- model on a dependent variable describing events on an ordinal scale. My independent variable of interest is a scale with a linear and a quadratic term. I have also used the -thresh()- option to relax the proportional odds assumption of the linear component of the scale.

Despite the above, because I'm only interested in one level of the dependent variable (the ordinal model is only used to maximise the use of information in data i.e. the event of interest is "borrowing strength" from other events) and the model can be reduced to a simple logit with one constant and two covariates (linear and quadratic).

What I want to do is to produce a table with absolute risks (probabilities) Relative Risk Ratios (RRR), and confidence intervals (CI) for all combinations of the scale (my independent variable) which would give 10*10 RRRs. I also want to produce tables where I have added 1 and 2 standard deviation of the estimated random intercept to the model, describing subjects with different event propensities.

I assume that if I predicted the probability score with CI, and calculated RRRs from the upper CIs as one limit and RRRs from the lower CIs as the other limit, that would not be correct? Or would it?

Any suggestions?

Thanks,

Michael

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