Dear All,

I am new to ordinal  logistic regression. Using ordinal regression within the R Commander GUI, I have  generated an independent variable that is  significant, but whose 95%  confidence intervals slightly  crosses "1".  Is this possible? Here is the syntax and output:

polr(formula = CDIcat ~ Employment, data = CDIallvariables, Hess = TRUE,
    method = "logistic")
Coefficients:
                                                Value        Std. Error t value
Employment[T.Parttime] -0.2523     0.2289     -1.102
Employment[T.fulltime]  -0.4425       0.2484    -1.781

Intercepts:
     Value    Std. Error t value
0|1   -6.2182   1.0045    -6.1903
1|2   -1.9272   0.1480   -13.0213
2|3   -0.9892   0.1177    -8.4068
3|4   -0.4036   0.1094    -3.6880
4|5   -0.0801   0.1078    -0.7426
5|6    0.3187   0.1088     2.9297
6|7    1.0335   0.1196     8.6445
7|8    1.3607   0.1290    10.5445
8|9    2.3018   0.1758    13.0909
9|10   6.0283   1.0028     6.0116

Residual Deviance: 1960.430
AIC: 1984.430
(1 observation deleted due to missingness)

When I  convert this to  OR's ( using the Epicalc package) here is the problem I  have with  the variable "Employment[T.fulltime]" which is significant ,but has too  wide a confidence interval.  How would I  interpret this ?

ordinal.or.display(OrdRegModel.5)
                       Ordinal OR lower95ci upper95ci P value
Employment[T.Parttime] 0.777      0.496     1.217     1.36e-01
Employment[T.fulltime] 0.642      0.395     1.045     3.78e-02


Russell " Skip" Barbour  Ph.D.
Associate Director for Statistics
Center for Interdisciplinary   Research  on AIDS
Yale School  of Medicine
135 College St.  Suit 200
New Haven ,  CT. 06510
Tel: 203 764 4332
Fax: 203 764 4353
Email: russell.barbour@yale.edu<mailto:russell.barbour@yale.edu>


Doubt grows with knowledge.
Johann Wolfgang von Goethe<http://www.brainyquote.com/quotes/quotes/j/johannwolf380192.html>



	[[alternative HTML version deleted]]

