Hi,
I'm experiencing difficulties with understanding my results despite active googling, and i'd be really grateful, if someone could help me.
I have a data set of around 1000 cases. The outcome i'm interested in (yes, no) occurs in around 35 %. In order to identify independent predictors for this outcome, i tried to construct a logistic regression analysis. In the logistic regression model, a dichotomous variable had a negative B coefficient value against my expectations (in crosstabulation, the variable seemed to be significantly associated with outcome occurring, p <0.001). The variable's CI for the OR was below 1 and p<0.001. Also, the SE was 0.2. After doing some reading, i assumed the problem of the wrong sign would be related to correlation between that another independent variable, so i began eliminating them in different combinations with no effect on the sign of the B coefficient. Moreover, no significant correlation between the variables seemed to exist (VIF 2 at most). In the end,i tried a model that included only that one variable, and still the negative b coefficient persisted. I also ran a linear regression (same y and x) but this yielded a positive b coefficient.
I'm really having trouble figuring this out and would very much appreciate any help!
K
I'm experiencing difficulties with understanding my results despite active googling, and i'd be really grateful, if someone could help me.
I have a data set of around 1000 cases. The outcome i'm interested in (yes, no) occurs in around 35 %. In order to identify independent predictors for this outcome, i tried to construct a logistic regression analysis. In the logistic regression model, a dichotomous variable had a negative B coefficient value against my expectations (in crosstabulation, the variable seemed to be significantly associated with outcome occurring, p <0.001). The variable's CI for the OR was below 1 and p<0.001. Also, the SE was 0.2. After doing some reading, i assumed the problem of the wrong sign would be related to correlation between that another independent variable, so i began eliminating them in different combinations with no effect on the sign of the B coefficient. Moreover, no significant correlation between the variables seemed to exist (VIF 2 at most). In the end,i tried a model that included only that one variable, and still the negative b coefficient persisted. I also ran a linear regression (same y and x) but this yielded a positive b coefficient.
I'm really having trouble figuring this out and would very much appreciate any help!
K
