On Thu, 19 Sep 2002 12:37:38 -0400, "Scott Richardson" <[EMAIL PROTECTED]> wrote:
> I am trying to evaluate the explanatory power of various (X1, X2, X3) > variables to predict an event, Y. I would like know if there is a test > statistic that allows me to compare the goodness of fit across several > logistic regressions. I know that such a test exists for continuous > dependent variables (there is a paper by Vuong 1989 in Econometrica titled > "Likelihood ratio tests for model selection and non-nested hypotheses"). > It is the same rather-illegimate testing, in one setting or the other. Regression with R-squared; maximum likelihood with Chi-squared. You can do a search on < AIC BIC > . > > At the moment all I have is the output from 3 logistic regressions as > follows: Y = f(X1) Y = f(X2) Y = f(X3) > [...] Is there any reason you can't do a *nested* test, since the nested tests are legitimate? -- to see if X1 adds to the prediction of X2, and vice-versa. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
