  # Re: st: RRR with CI from logit model

 From Michael Ingre To statalist@hsphsun2.harvard.edu Subject Re: st: RRR with CI from logit model Date Tue, 2 Nov 2004 18:27:20 +0100

```On 2004-11-02, at 16.05, Leonelo Bautista wrote:

```
On the other hand, I fail to see why you want to calculate relative risks
from a logistic model.
I have estimated an ordinal (relaxed proportional odds) model with -gllamm- and I want to use the estimated parameters to predict probabilities and estimate RRRs comparing different levels of my independent variable. Despite the ordinal approach, after estimating the coefficients, my problem can be reduced to a simple logit with two covariates and a constant to predict the outcome. As far as I can tell, it is not possible to estimate my model with a log link. But I will appreciate any suggestions.

Predicting probabilities (with confidence intervals) are straight forward. Calculating the point estimate of RRR is also no problem. However, I also want to calculate confidence intervals.

If I use -nlcom- , I get the point estimate and confidence intervals (CI) but with the paradoxical result that small (very small) differences in risks are significant with narrow CIs and large differences in risks are NOT significant with HUGE CIs. The paradox can also be illustrated with auto.dta. Try it to see for your self (code was posted earlier: http://www.stata.com/statalist/archive/2004-11/msg00049.html).

On 2004-11-02, at 17.26, Ronán Conroy wrote:

```Relative risks make so much more sense than odds ratios
```
I totally agree. That's why I'm trying to estimate RRRs with my logit model. RRRs make a nice addition to the predicted probabilities. I also have the objective to show that individuals differ in their subject specific RRRs because of differences in overall propensity (the random intercept).

I appreciate any suggestions.

Michael

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