jamovi

Hello,

I know how to perform an ordinary binomial logistic regression with two outcomes and several potential predictor variables. But my setup is a bit more complex.

There are two treatment groups in the experiment. For each treatment group, there is a binary outcome based on a response variable assessing the effectiveness of the treatment: treatment effective - yes or no.
In addition, there are two follow-up time points for each treatment: after 2 weeks and after 4 weeks.

So, in the end, there is:

• treatment A after 2 weeks: effective yes or no

• treatment A after 4 weeks: effective yes or no

• treatment B after 2 weeks: effective yes or no

• treatment B after 4 weeks: effective yes or no

How would I handle such an experimental setup with logistic regression in jamovi in order to analyze for the potential predictor variables?

You can use generalized mixed models, selecting a logistic model.

Hi, thanks for the answer. What would I select in jamovi for that? I assumed I would have to choose a type of "Regression" analysis, for example "Logistic Regression - N Outcomes/Multinomial". But how would I define or code the 8 different outcomes?

Or would I find the appropriate analysis type under "ANOVA"? But I could not find an option for selecting a logistic model there.

I think this publication here does a similar type of analysis as I would like to do one (in the statistical sense).

"Mixed effects logistic regression analysis of blood pressure among Ghanaians and associated risk factors"
https://www.nature.com/articles/s41598-023-34478-0

The response variable (blood pressure) is binary (high or normal). The response variable was determined across three measurement periods (in my case I only have two). Here, they, wanted to identify risk factors for high blood pressure and for that they used a mixed effects logistic regression model.

How can I do this mixed effects logistic regression model in jamovi?

You need to install GAMLj3 module. There you find generalized mixed models

Thank you. I noticed that the GAMLj3 is only available in the library with the most current version of jamovi and not the so-called solid version, which I had installed until now.

Current version is pretty ok, just go for it.

Alright, good to know.

Would it be wrong to analyze the two different treatments as two independent experiments and hence perform two separate logistic regression analyses?

Because what I want to know is which of the several potential predictor variables provide(s) a strong and statistically significant prediction of the response variable (treatment effective or not) after 2 weeks and/or 4 weeks. I am not interested in comparing treatment A and treatment B.

The research question is - more simply expressed: What predicts an effective response to the treatment at time point 1 and at time point 2, respectively?

If you're not interested in comparing treatment group A to treatment group B (and if you think your audience won't be interested in that comparison either), then you could simply code the data so that there's no distinction between A and B, and do just one analysis. (Doing two separate analysis halves the N and thus tends to drastically reduce the statistical power.)