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Kanyange
Fluorite | Level 6


Hi All,

I have  built a Logistic Regression Model and I get the results below...The variables with a high Chi-Square below (Var1 and Var6)..Should they be removed from the model?

Thank You

Analysisof MaximumLikelihoodEstimates
ParameterDFEstimateStandard ErrorWald Chi-SquarePrPr> ChiSqStandardized EstimateExp(Est)
Intercept1-2.81450.004495,784.70 <.0001 0.06
Var 110.07580.00035745,168.02 <.00010.26611.079
Var 210.36460.007532,345.72 <.00010.04031.44
Var 31-0.09120.001862,407.66 <.0001-0.0520.913
Var 410.78910.008099,506.31 <.00010.09812.201
Var 510.10890.003341,060.29 <.00010.03391.115
Var 611.0980.00339104,610.00 <.00010.70952.998
Var 710.1530.002394,092.80 <.00010.0621.165
1 REPLY 1
user24feb
Barite | Level 11

I think a statistically right way would be, if you run the regression again - without var1 & var6 - and compare the likelihood functions. If they don't differ much, you don't need the 2 variables. (Likelihood-Ratio-Test: Subtract lambda=2*(likelihood with var1&var6 - likelihood without var1&var6) -> get value of the chi-squared distribution with 2 degrees of freedom -> if the result is almost zero (e.g. <0.01) the 2 variables should not be excluded.)

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