how to present multilevel model results in a visual and understandable way for non-experts

[Nothome1975]

Hi everyone,
I am doing a multilevel analysis with educational survey data and would like to present the results to a research team that includes members without a statistical background.
I would like to ask: Are there any visual and effective ways to interpret the results from a multilevel model (e.g. coefficients at each level, variances, etc.) for non-experts? If anyone has an example to illustrate (especially through graphs), I would love to learn more.
Thanks!

[Nothome1975]

Has anyone encountered this situation?

[Tishaunn]

You could use simple bar charts or dot plots to show fixed effects (coefficients) with confidence intervals, and variance components can be illustrated using variance partitioning pie charts. A slopes-as-outcomes plot can also help show variability between groups. Clear labeling and minimizing statistical jargon are key.

[DavidAlexander]

You could use simple bar charts or dot plots to show fixed effects (repo) with confidence intervals, and variance components can be illustrated using variance partitioning pie charts. A slopes-as-outcomes plot can also help show variability between groups. Clear labeling and minimizing statistical jargon are key.

Good idea tho, you can even highlight “Key takeaways” directly under each plot, this helps non-statistical team members engage meaningfully.