Dear reader of this post,
I'm conducting research where I have 8 mental health care teams and three dependent variables: victimization, discrimination and social functioning. My research question is whether the socioeconomic status (SES) has influence on my three dependent variables.
My supervisor advised a multi-level model for each of my dependent variables. This is not within my comfort level, so bear with me.
So what happened is I fitted three models for the data I have. First, the Type III test of fixed effects does not generate a significant effect for my dependent variables. So does further fitting even make sense? But I keep getting a warning for problems with my "final Hessian matrix" So I'm left with basically just a linear regression.
So my friend who is a statistician (but lives in an other country) told me I have a problem with convergence. He solved this with "generalised Inverse" in SAS, but I can't seem to find such an option in SPSS, is there a solution?
Any tips or advice would be welcome!
Thanks in advance,
Anouk
I'm conducting research where I have 8 mental health care teams and three dependent variables: victimization, discrimination and social functioning. My research question is whether the socioeconomic status (SES) has influence on my three dependent variables.
My supervisor advised a multi-level model for each of my dependent variables. This is not within my comfort level, so bear with me.
So what happened is I fitted three models for the data I have. First, the Type III test of fixed effects does not generate a significant effect for my dependent variables. So does further fitting even make sense? But I keep getting a warning for problems with my "final Hessian matrix" So I'm left with basically just a linear regression.
So my friend who is a statistician (but lives in an other country) told me I have a problem with convergence. He solved this with "generalised Inverse" in SAS, but I can't seem to find such an option in SPSS, is there a solution?
Any tips or advice would be welcome!
Thanks in advance,
Anouk