Hi. I am running a logistic regression with a binary dependent variable and 5 class independent variables. The used code is: proc logistic data=train; class var1 var2 var3 var4 var5 / param=GLM; model pred12 (event='2')= var1 var2 var3 var4 var5 / RSQ; run; And the partial output is: Effect DF Wald Pr > ChiSq Chi-Square Var1 1 150,7266 <.0001 Var2 3 119,5550 <.0001 Var3 8 157,9586 <.0001 Var4 6 1553,0700 <.0001 Var5 4 15975,6288 <.0001 Analysis of Maximum Likelihood Estimates Parameter DF Estimate Standard Wald Pr > ChiSq Error Chi-Square Intercept 1 5,0054 0,2974 283,3322 <,0001 .-------- .---- .------ .-------- .-------- .-------- .-------- .-------- .---- .------ .-------- .-------- .-------- .-------- Var4 1 1 -1,9443 0,2969 42,8854 <,0001 Var4 2 1 -1,6971 0,296 32,8692 <,0001 Var4 3 1 -0,9009 0,2951 9,3197 0,0023 Var4 4 1 -1,0116 0,2957 11,7065 0,0006 Var4 5 1 -0,4524 0,2963 2,3319 0,1267 Var4 6 1 0,0255 0,3039 0,0071 0,933 Var4 999 0 0 . . . Var5 1 1 -1,2442 0,0445 782,4054 <,0001 Var5 2 1 -1,5483 0,0364 1811,5691 <,0001 Var5 3 1 -2,108 0,0304 4793,1049 <,0001 Var5 4 1 -3,1394 0,0259 14693,0821 <,0001 Var5 999 0 0 . . . My question is concerning the wald chi-square. How can I interpret the fact that for var5 the value of the wald chi-square is so much higher than the values of the remaining variables? And what is the consequence to the regression quality. Thanks in advance for the help.
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