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st: Hosmer-Lemeshow sticky issues

From   Ashwin Ananthakrishnan <[email protected]>
To   [email protected]
Subject   st: Hosmer-Lemeshow sticky issues
Date   Thu, 7 Sep 2006 05:28:38 -0700 (PDT)


I"m trying to confirm goodness of fit for a logistic
regression model I'm working on, but I keep ending up
with very small p-values implying poor fit.

My outcome is a dichotomous variable - screened vs.
not screened. My predictor variables are age category
(in 5 year intervals), income tertiles, race, and
gender. My final model constructed through stepwise
backward elimination includes all the variables and
some interaction terms. However, when I try to run the
goodness of fit test (Pearson or Hosmer Lemeshow), I
keep getting extremely small p-values. 

Can someone explain to me what this means? Does this
mean that the model is not valid, and the odds ratios
are incorrect?

Can you get poor fit simply as a marker of large
sample size (my sample size is 500 000)

I'm not able to understand why the model doesn't fit
when it has been constructed from the data stepwise
backward elimination, and all the variables are
univariately significant?


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