Hello everyone,
I am currently working on a project where I have a data set with measurements taken place at two time points (longitudinal). I got two variables, lets call them a and b, both being continuous scaled, and i got four more variables, lets call them 1,2,3,4 also all continuous scaled. I am interested in gender effects, so now I I want to check if there is a difference for a & b for gender (male/female). Then I want to check if there is a difference for 1,2,3,4 for gender. In the end, I would like to see if gender is influencing a &b, which in turn is influencing 1,2,3,4.
What I am thinking is, I could do structural equation modeling, including all the variables and then do two groups, one for each gender and compare those two. However I am unsure if that is valid. Moreover, I am super new to SEM so not even sure if its the right approach.
I am thankful for any hints or advice
I am currently working on a project where I have a data set with measurements taken place at two time points (longitudinal). I got two variables, lets call them a and b, both being continuous scaled, and i got four more variables, lets call them 1,2,3,4 also all continuous scaled. I am interested in gender effects, so now I I want to check if there is a difference for a & b for gender (male/female). Then I want to check if there is a difference for 1,2,3,4 for gender. In the end, I would like to see if gender is influencing a &b, which in turn is influencing 1,2,3,4.
What I am thinking is, I could do structural equation modeling, including all the variables and then do two groups, one for each gender and compare those two. However I am unsure if that is valid. Moreover, I am super new to SEM so not even sure if its the right approach.
I am thankful for any hints or advice