Hi everyone,
Currently I'm writing my thesis on the effects of divorce on children. It's a complex design so I guess I'll be posting more questions here
My dependent variable is whether or not the respondent has ever been in a relationship. My independents are 2 dichotomous variables : Gender and parental marital status (0 = together 1 = divorced). I found dat the marital status of the parents has an effect, gender of the respondent has not. Now i want to check if the interaction between gender and parental marital status has an effect. --> Y = b1Maritalstatus + b2Gender + b3MaritalstatusxGender
Both gender as marital status correlate highly with the interaction term. I solved this by first recoding the variables (0 to -0,5 and 1 to 0,5) and then centering these and making the interaction with the two centered variabled. No longer high correlations, so I guess I solved this. However, some people say it's not okay to center categorical data, so is my solution wrong? Is there a better solution?
Second question, still the same dependent. I want to see if the age at the time of parental divorce (continuous) interacts with gender. Again the multicollinearity issue, so I center the age-variable. This reduces the correlation between gender and the interaction term, but not the correlation between age and the interaction term. How can this be? What did I do wrong?
Thanks in advance for your help!
Currently I'm writing my thesis on the effects of divorce on children. It's a complex design so I guess I'll be posting more questions here
My dependent variable is whether or not the respondent has ever been in a relationship. My independents are 2 dichotomous variables : Gender and parental marital status (0 = together 1 = divorced). I found dat the marital status of the parents has an effect, gender of the respondent has not. Now i want to check if the interaction between gender and parental marital status has an effect. --> Y = b1Maritalstatus + b2Gender + b3MaritalstatusxGender
Both gender as marital status correlate highly with the interaction term. I solved this by first recoding the variables (0 to -0,5 and 1 to 0,5) and then centering these and making the interaction with the two centered variabled. No longer high correlations, so I guess I solved this. However, some people say it's not okay to center categorical data, so is my solution wrong? Is there a better solution?
Second question, still the same dependent. I want to see if the age at the time of parental divorce (continuous) interacts with gender. Again the multicollinearity issue, so I center the age-variable. This reduces the correlation between gender and the interaction term, but not the correlation between age and the interaction term. How can this be? What did I do wrong?
Thanks in advance for your help!