Fixed Effect vs. Random Effects Models - Common Mistakes in Meta-Analysis and How To Avoid Them

Common mistakes and how to avoid them - fixed-effect vs. random-effects models. Examples and specific concerns for each.
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[@axisgraf]

This presentation is pure gold! Thank you for sharing it with the rest of us unfortunate to have not attended this session

[@MetaAnalysisCMA]

Glad you enjoyed it!

[@ahmedehsanurrahman4185]

This is the best explanation of RE models and FE model in meta-analysis that I have ever heard.

[@calebdanny1485]

you probably dont give a shit but does anyone know a way to get back into an Instagram account..?
I stupidly lost my login password. I appreciate any tips you can offer me.

[@archertheo6898]

@Caleb Danny instablaster :)

[@LegoEddy]

Finally understood it! Thanks a lot for sharing this, and for the reference to your paper for the mathematical differences.

[@thankyou6555]

What an absolutely outstanding presentation! Wonderful! Thank you for sharing this.

[@fnssupply]

Thank you for taking the time to make this helpful video!

[@timot6901]

Thank you very much! I found the paper you referred to before watching this video. After watching it I understand most of it.

[@amywilderson85]

Now I can see what exactly are fixed-effect and random-effects models. Thank you!!

[@MetaAnalysisCMA]

You're welcome!

[@veralicebruin4478]

Enjoyable and clarifying!! Thank you!!

[@saadalhumaid3959]

Fantastic tute as usual. Thanks alot Michael

[@daahmandaahman7977]

Brilliantly clear presentation. I will be sure to use the word 'universe' in my study!

[@indigolight22]

Your insight is profound. Thank you.

[@tchinzowu]

Beautiful explanation. I'm going to sort the paper I am working on right away.

[@ceciliasamame8216]

Thank you, Dr. Borenstein. Excellent video!!

[@yinghe_dbw]

这个视频不断的让我想到了某国的大部分教授们，总是在不断地强调结果是不是显著，怎么巧妙的处理就可以让结果看着更好看……这种模式下学了很多甚至变得“很厉害”成为了“大佬”一头雾水的开始分享怎么做一篇“优秀”文章的经验，sucks。Anyway，这真的是一篇perfect lecture，highest respect for this vedio and the professor！

[@elizabethblears2919]

Thank you so much! Very helpful!

[@myihienew]

Thank you for your lecture. very easy to understand

[@babakkhoshnood1811]

Thank you so much. Very clear and concise. Look forward to reading the book / using the software. Best Regards, Babak Khoshnood

[@babaymben9850]

We owe a lot to Dr.Borenstein. Thanks doctor, i wish all the best to you.

[@MrSpotgold]

I applaud this explanation! Thank you dr. Borenstein. Random effects models rule. The fixed effect model is simple, clear, and wrong.

[@dc33333]

good speaker. so clear.

[@mauriciomolinahn]

Great Lecture Dr. Borensterin!!!

[@MetaAnalysisCMA]

Glad you enjoyed it!

[@tiajin248]

Thankss a lot for sharing this amazing lecture, I learned a lot from this lecture.

[@PantherBakua]

great video. thank you very much

[@kayak0000]

As an MD and clinical researcher for 5 years, i observed that some MDs/physicians really have no/little idea on how to run statistical tests for research (which is understandable since statistics is really not part of the MD curriculum) so they are wholly/partially dependent on their statisticians. There are times also when the statisticians have the right idea / executed the tests correctly but the clinician interpreted the methods and/or results differently. 😅😅😅

[@lisas.3530]

Thank you so much!!!!!!!!!!

[@alfredoalarconyanez4896]

Thank you, your video is very informative

[@yousafkhankhalil8726]

Thank you for your lecture

[@KingCrocoduck]

Let me add three more to the list: eyeballing funnel plots to determine whether they're asymmetric, treating Egger's test as though it detected publication bias, using trim/fill or PET PEESE on highly heterogeneous studies

[@mohammadkashem3375]

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?

[@Doodoodoomanamana]

he mentioned he'd been talking about giving an appropriate weight to each study in another module, does anyone know which module it is?

[@BigBossHuntelaar]

You should mension the method of Peto and the Fixed EffectS model sooner in the video! As a disclaimer.
Now I've watched the entire video (and learned a lot!) and only found out at the end that the study I am interested in actually uses the fixed effectS model and Peto OR's.

[@zqtang3481]

Should fixed effect model instead of random effects model be used at 23:21? Is that right?

[@venugopal-ir7hq]

Sir, can you please share the relevant reference for the above

[@drnaziashuaib7238]

thanks sir

[@tesfahun_taddege]

Good

[@bodrulalomk1257]

nice

[@georgepalaio3745]

So it’s wrong to chose a fixed effect model based on heterogeneity less than 50

[@archisarker2920]

❤

[@LijiaLinPHD]

It seems that the narrator is reading a written script, because I can hear he's turning the pages. This makes the flow a little fast. I really need 100% focus.

[@AndruideAtario]

Fake and Fabricated! Bad presentation, and wrong and way off any reasonable analysis. Sad, I was excited