Mixed Model Analysis: Real Example

[josyc]

I love your energy and the way you explain things! Tysm :)))

[ToniSkit]

Please do that convergence video issues :)

[laurykost]

Hey! Cool video, thanks! but... have you ever considered doing a video to explain how to deal with some warnings? 
For example: "boundary (singular) fit: see ?isSingular".
It would be actually very useful.

[navjotsingh]

Love this video…and I think I also love you 😂 you are so cool and helpful.

[bpatriquin]

Do you have videos like this one that show your process of adjusting for confounding within a linear mixed model???

[thejll]

Nice videos! Do you have one where you explain why we should use mixed-effect modelling instead of doing separate regressions on data subsets?

[shrilekhab]

I need your suggestions for my data analysis using mixed models. Please let me know if you are available on zoom or teams at the earliest. It would be of great help.

[snuffleism]

How can I use multilevel modeling with a binary outcome variable? Any chance you can do a video example of that? I have an ordinal independent variable (3), ordinal moderator (3), and annual time waves (10).

[kennedygolfhead]

Oh my god this video is amazing... This really gives me the insight into how powerful the R is...

[gustavsloris]

Heyo, Dustin, thank you for your enthusiasm and effort in teaching! I've started using "flexplot" and am trying to utilize it for analysing GLMM (log-link, Gamma distr), and it doesn't compile any graphs...
when calling the 'visualize(model, plot="model")' R gives out this message Error in draw_axis(break_positions = guide$key[[aesthetic]], break_labels = guide$key$.label, :
lazy-load database is corrupt

my question is – is flexplot suitable for plotting, analysing (also for R-sq statistic) when used with GLMM (glmer) not just linear MM?

many thanks and keep it up! :)

[jamie]

Thanks for your videos, they are helpful for some modelling I'm attempting! QUICK QUESTION - Usually I see one of the random effects of model described as repeated measures/same people across multiple time points. I have data where I have multiple time points but slight differences in the groups of people (i.e. most are different people but some people show up across multiple time points). How would this type of data be handled in a mixed model? Would I ignore this as a random effects factor as most people are not present in the data across multiple time points?

[bpatriquin]

I cannot thank you enough! I realize all YouTube how-to vids use narration, but I relate SO MUCH to the way you think out loud at each point in the model building process 🔥

[leab]

Hi, thanks for the video! I did not really yet understand these two things: 1. why do we compare two possible models, does that have to do with controlling the interaction of the effects (trying to make sure that no things are interpreted as output effects that in reality are interactions that are only occuring due to the combination in the model)? And: How can I interpret a PB Test run by using the Modcomp function? This would be extremely helpful. Thanks for the video

[lauracarreno]

I couldn't install flexplot, it says it's not available for the latest version of R. Any chances there's a workaround for this? thank you!

[rayray]

I have a question on reporting LME models. When doing them in r, spss, or jamovi, you get the summary of the anova table and f values. What is the recommended way to report these models? F values like an anova framework or estimates like in regression. I see them reported both ways, so I wanted to get your thoughts on it. Should the anova table be paid any attention to, and instead, we jump right into the estimates? Thank you.