Fixed and random effects with Tom Reader

Describing the difference between fixed and random effects in statistical models.

[misterabuse]

I love you Tom, you managed to explain this incredibly important point to me in such an eloquent manner that I finally understand its significance!

[DoctorNahanni]

This was fabulous! I really enjoy your style of presenting. It is clear, challenging, and well-crafted.

[seanleeduncan]

No! We need the mixed effect model video. This is the clearest explanation I've heard.

[zelim]

Excellent explanation of effects in statistical models! Huge thanks Tom, you are the best!

[johnorosz]

Good data allows organizations to establish baselines, benchmarks, and goals to keep moving forward. Because data allows you to measure, you will be able to establish baselines, find benchmarks and set performance goals. A baseline is what a certain area looks like before a particular solution is implemented.

[lawrnc]

Great explanation! I find interesting that in this explanation it may be implied that random effects models (aka multilevel or mixed effects models) may be favoured to fixed effect ones, which instead through a lot of information away. Some researchers especially in econometrics instead would make the distinction between FE and RE models (rather than random and fixed effects) and favour fixed effects

[abdulbouraa]

Hi, I'm From Comoros. Thanks for the video, it was crystal clear !!!

[ElNick]

This is brilliantly done. Wonderful presentation!

[THIAGOVIZINE]

Great Video! Please upload the Mixed Effects one

[riesenpurzel]

sad truth is that I did mixed models once for a publication and one of the reviewers said the statistics section is hard to understand and not common, so i should use anova instead... cheers to the standards of nowadays science
edit: After submitting to a journal in another field where I knew from a colleague that the standards in statistics are a little higher, I had no problems anymore.

[riabhabu]

Hey! thank you so much for this explanation it was truly helpful. I was wondering if you could answer a question I had about the topic. What if you wrongly assume a factor to be of random effect how would that affect your results if at all?

[margaridacabral]

Amazing explanation! I wonder if the video about mixed models is already out? I could not find it under the youtube page of Univ. of Nottingham...

[djjoeyb]

Big up the top g Tom, shelling stats like it's Mario Kart. GG

[zolper]

Thank you for the explanation, this video was very easy to understand!

[durgasthan]

That is why we have many independent variables to capture the random effect.. but what i was expecting how these fixed vs random effecting impacting the model.. where we already tried using many independent variables

[wiltonpt]

Great Lectures. Many thanks. Is there a sequel into explaining more about Mixed models

[karakesteven]

Hello!! can one use a fixed effect regression on a cross-sectional dataset, if yes how?

[stanislaviakhno]

Great video! Well explained, thank you. I wonder if at 6:00 it is going about the random effects and not bias measurement? Thanks!

[MannISNOR]

This is really well done! Great job Tom Reader!

[NERMIENKH]

Thank you so much for simplyfing such topic.