# [R] How to intepret a factor response model?

From: Maciej Bliziński <m.blizinski_at_wsisiz.edu.pl>
Date: Wed 04 May 2005 - 17:23:17 EST

Hello,

``` one  :100   Min.   :-2.742877
three:100   1st Qu.:-0.009493
two  :100   Median : 2.361669
Mean   : 2.490411
3rd Qu.: 4.822394
Max.   : 6.924588
```

> mymodel = glm(factor_var ~ real_var, family = 'binomial', data = mydata)
> summary(mymodel)

Deviance Residuals:

Min 1Q Median 3Q Max -1.7442 -0.6774 0.1849 0.3133 2.1187

Coefficients:

```            Estimate Std. Error z value Pr(>|z|)
(Intercept)  -0.6798     0.1882  -3.613 0.000303 ***
real_var      0.8971     0.1066   8.417  < 2e-16 ***
```
```---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1

(Dispersion parameter for binomial family taken to be 1)

Null deviance: 381.91  on 299  degrees of freedom
Residual deviance: 213.31  on 298  degrees of freedom
AIC: 217.31

Number of Fisher Scoring iterations: 6

---------------------------------------------------------------------

For models with real-type response variable it's easy to figure out,
what's the equation for the response variable (in the model). But here
- how do I interpret the model?

--
God made the world in six days, and was arrested on the seventh.

______________________________________________
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help