Hi.
I'm running a multinomial logistic regression.
My independent variable isei is a continuous measure of social class, and my dependent variable is answer to the question: "How many people with whom you can discuss intimate and personal matters" with the following possibilities to answer: "none", "1", "2", "3", "4-6", "7-9" or "10 or more".
I run the following code: svy: mlogit inprdsc c.isei $control
Below you see a snapshot of my output. The mlogit regression gives me relative log odds. I'd like to supplement with a visualization of the probability answering for example "None" across different levels of social class (the isei variable). I've been trying to use the following command "marginscontplot isei", and I can make it work for the first response option "None" (see the second screenshot below). What do I add to the command in order to get the same plot for the second response option, which is "1", the third which is "2" etc.?
Thank you for your help! Please let me know, if anything elaborated, clarified etc.
Kind regards
Mads
__________________________________________________ __
I'm running a multinomial logistic regression.
My independent variable isei is a continuous measure of social class, and my dependent variable is answer to the question: "How many people with whom you can discuss intimate and personal matters" with the following possibilities to answer: "none", "1", "2", "3", "4-6", "7-9" or "10 or more".
I run the following code: svy: mlogit inprdsc c.isei $control
Below you see a snapshot of my output. The mlogit regression gives me relative log odds. I'd like to supplement with a visualization of the probability answering for example "None" across different levels of social class (the isei variable). I've been trying to use the following command "marginscontplot isei", and I can make it work for the first response option "None" (see the second screenshot below). What do I add to the command in order to get the same plot for the second response option, which is "1", the third which is "2" etc.?
Thank you for your help! Please let me know, if anything elaborated, clarified etc.
Kind regards
Mads
__________________________________________________ __
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