Describing the difference between fixed and random effects in statistical models.
Пікірлер: 55
@misterabuse3 жыл бұрын
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!
@rodrigogutierrezdiaz5483 Жыл бұрын
love him too
@zelim98632 жыл бұрын
Excellent explanation of effects in statistical models! Huge thanks Tom, you are the best!
@ElNick093 жыл бұрын
This is brilliantly done. Wonderful presentation!
@MannISNOR4 жыл бұрын
This is really well done! Great job Tom Reader!
@lawrnc2 жыл бұрын
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
@DoctorNahanni5 ай бұрын
This was fabulous! I really enjoy your style of presenting. It is clear, challenging, and well-crafted.
@seanleeduncan3 жыл бұрын
No! We need the mixed effect model video. This is the clearest explanation I've heard.
@radelgrumpf3 жыл бұрын
Extremely good video, Mr. Reader. Thank you so much.
@anamikabhowmick63222 жыл бұрын
Such a great explanation and I finally understood this importing thing
@abdulbouraa45292 жыл бұрын
Hi, I'm From Comoros. Thanks for the video, it was crystal clear !!!
@_Randa_ Жыл бұрын
Such a clear explanation! Very helpful.
@AmIsupposedToBeAlone2 жыл бұрын
Really clear explanation! Thank you!
@avishkaravishkar14513 жыл бұрын
Excellent video and crystal clear explanation
@tarikutesfaye44715 күн бұрын
I loved the video. Thank you Tom!
@THIAGOVIZINE4 жыл бұрын
Great Video! Please upload the Mixed Effects one
@BlowAway113 жыл бұрын
That was very clear. Thanks a lot!
@afraidofmoths65472 жыл бұрын
What an awesome video! Thank you!
@rameshwariar673 Жыл бұрын
Thank you for this clear explanation!
@djjoeyb2873 Жыл бұрын
Big up the top g Tom, shelling stats like it's Mario Kart. GG
@chandlerw882 жыл бұрын
Thanks Tom. Great explanation
@WanyShamsuddin2 жыл бұрын
Very clear explanation . Thankyou !
@ollie-d2 жыл бұрын
Very clearly explained, cheers
@zolper11898 ай бұрын
Thank you for the explanation, this video was very easy to understand!
@sofiaalfonso98833 жыл бұрын
What an excelent video, thank you very much
@NERMIENKH5 ай бұрын
Thank you so much for simplyfing such topic.
@dywu123 жыл бұрын
Thx Tom, great explaination :) and well pronounced btw!
@stanislaviakhno23283 жыл бұрын
Great video! Well explained, thank you. I wonder if at 6:00 it is going about the random effects and not bias measurement? Thanks!
@md.masumbillah82222 жыл бұрын
great presentation!
@karakesteven66173 жыл бұрын
Hello!! can one use a fixed effect regression on a cross-sectional dataset, if yes how?
@jacobalbright87172 жыл бұрын
Fantastic! Thank you!
@molloarden89383 жыл бұрын
Superb , lucid presentation on an all too often neglected topic in stats.
@johnorosz7477 Жыл бұрын
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.
@margaridacabral35023 жыл бұрын
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...
@uniofnottingham3 жыл бұрын
We found these other videos with Tom Reader kzbin.info/www/bejne/sGWYfYifpZuFmas and kzbin.info/www/bejne/hqqxq5V6l8-mZ7s if they help at all.
@wiltonpt12 жыл бұрын
Great Lectures. Many thanks. Is there a sequel into explaining more about Mixed models
@crazychocgingerbread70993 жыл бұрын
Thank you so much!
@chungbui78924 жыл бұрын
Thank you, sir
@riesenpurzel2 жыл бұрын
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.
@haeyoungkim5093 Жыл бұрын
Its a major limitation of the peer review process...
@riabhabu76410 ай бұрын
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?
@ThuHuongHaThi3 жыл бұрын
Thank you very much, sir
@preciousumeha29734 жыл бұрын
Thank you sir
@timokvamme Жыл бұрын
very well explained
@durgasthan3 жыл бұрын
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
@abdullahahmadzai63654 жыл бұрын
great
@mohammadkashem3375 Жыл бұрын
Hi Sir, if Hausman test indicates that fixed model is more appropriate than random effect model, and if in that case, in data time period (T) > cross section units (N), which FEM is to be chosen: time (T) FEM or Cross section (N) FEM?
@betrugerzbovorni24432 жыл бұрын
very good
@VictorOrdu2 жыл бұрын
Great theoretical background
@esthertaheri22807 ай бұрын
Hope there was a link to the next video for the mixed model
@rumeeranisavapandit19653 жыл бұрын
Sir, please give the lectures in written form also
@Y45HV1N Жыл бұрын
can "nurse" be treated as a random effects if there are only 2 nurses?
@mubarekeshetiehussen3989 Жыл бұрын
Firstly, i would like to thanks for you interesting study, my data have two land uses(exclosure and non exclosure) with three site in each land use how to arrange my data and make analysis using liner mixed effect model
@chrislloyd5415 Жыл бұрын
You talk about dependence within individuals. Why can you not include a dummy variable for each individual and, if desired, an interaction of this dummy variable with the covariate? This is a FE model. What is the value in pretending that the individual parameters follow a normal distribution (when they might not)?
@BluePenguin18123 ай бұрын
Hi Chris, the approach you describe only works if "sphericity" is satisfied, for which you need equal variation on the dependent variable for each cluster (each individual in this case). While Mauchly's test tries to identify whether sphericity is violated, a mixed model assigning a random effect to the clustering variable avoids this requirement