I have a question. I want to conduct a binairy logistic regression analysis, with a dependent categorical variable of "20 or higher score on an addiction severity questionnaire" and predictors. But, i want to understand the following that I have included as an image as well in this posting. 1) when i include 4 predictor variables, i do understand that i get different data and exp (b) per predictor than when I use 6 predictors. But, what i do not understand is, when i use extra predictors, that a predictor that earlier revealed a lower predictive value, somehow shows a higher predictor value suddenly. And 2) in the picture you can see the "Drinker + me association score using all blocks", which shows a strange exp (b) value when I use it in the analysis with 6 predictors. >>>>>>>> i would like to understand how this is possible, what i am doing wrong, and if i can prevent this from occurring or solve it.
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Topic gesloten.
to be concrete, taken out of the document that i attached:
*of one potential predictor variable (drinker & me association all blocks), in the regression analysis with 4 predictors the data are:B= .875, SE=.683, wald-1.645, df=1, sig=.20, exp (b)= 2.40. in the analysis with 6 predictors, the data for this SAME variable are:B= 15.69, SE= 6.53, wald=5.777, df=1, sig.=.02, Exp (B)= 6509112.599. Any idea what is happening here?
