Longitudinal Multilevel Modeling in R Studio (PART 3)

[@cavanbonner1676]

Thank you so so much for putting this videos together. This series has been a huge help while I try to finish a senior thesis alone at home without being able to meet in person with any of my faculty like I normally would.

[@faustinorubioperez4584]

Thank you so much! This videos help me a lot, this kind of models are hard to understand in a conceptual level, but step by step I'm starting to understanding it.

[@ericcui7193]

These are great tutorials!

[@wasafisafi612]

Thank you so much for the video

[@haoduong6565]

If you have examples of binary outcome, please share link. Thank you!

[@SouravPadhee]

Can I get the dataset?

[@kristiapamungkas697]

Thanks a lot for the videos! I'd like to know how missing data affect the results generally (e.g., participants with only 1 day input)

[@peterkidd9829]

Great series of videos, very clear and informative and easy to follow! Just have one follow up question which I'm curious about. What would entering ID as a predictor into the full model show (with ID also remaining as a random intercept)?

[@monika8638]

Dear Jon, thank you very much for the super helpful videos! Do you have a recommendation on how to report the results - in a traditional regression table? Thanks again!

[@jonbstatsandpsych6340]

Hi Monika. Thanks for watching and for the comment. Here is a link to a website showing various examples of articles that have published different types of multilevel models: www.bristol.ac.uk/cmm/gallery Just select the options that best match your own analysis and hopefully it will show some papers that can help you write up your own results.

[@shivanithakur8938]

Is it possible to apply Multilevel models when data set consists of 3 IVs of categorical nature and 1 or more continuous DVs ?.......... My data set consists of 3 categorical IVs (1st IV consists of 2 categories, Second IV also consists of 2 Categories and 3rd IV consists of 3 categories).