Regression with Count Data: Poisson and Negative Binomial
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- čas přidán 28. 06. 2024
- Poisson, quasi-Poisson, and negative binomial regression - when to do them and how you should choose the method. What are overdispersion and underdispersion, and why are they problems? How to deal with too many zero counts (zero-inflation) or when zero counts are impossible (zero-truncation).
0:00 Background
2:26 Poisson Regression: What and Why
7:05 Overdispersion: Quasi-Poisson or Negative Binomial
13:25 Zero-Inflation and Zero-Truncation
18:37 Summary Table - Věda a technologie
This clip alone gave me more information than I ever imagined. Thanks.
Best video on the internet on this topic in my opinion. Covers the why, the what, the when and the how.. perfect! Liked and subbed. Thanks!
I agree, really really good educational video, much appreciated
This is super useful to understand and apply the poisson regression analysis. one of the best tutorial I have ever watched. Many thanks!
Amazing video! Excellent explanation and very useful!
Nice ! Thanks for the timestamps !
Thank you so much for posting this video!
super helpful, thank you Matthew!
Great ! Please keep posting more such videos
Congratulations! Excellent Video. It would help a lot if you provided the code for the variance vs mean plot and the corresponding lines predicted by the quasi-Poisson and negative binomial model. Thanks
Very excellent video! Thanks!
Hi ! Thank you for explaining theses models. Is it possible to provide the R code you 've been using to compute the
graphics ?
Very nice video. Thank you!
Thank you very much! This helped me quite a lot!!
can you provide the code for the mean vs varaince plot for quasi poisson and negative binomial glm....that will be very helpful
OMG, thank you so much for this very informative video, it really helped me a lot!
Thank you so much! Excellent explanation!
Quick question: Can I use multivariate zero truncated Poisson regression to compare the effects of two IVs on a DV? I'm mostly wondering if the size of the coefficients lose their meaning because of the zero truncation
great vid, cheers
Great explanations
Excellent video. Thank you ! Quick ques: When you say that the mean must equal the variance, do you mean that the mean of all the Y values of the observed data points must equal the variance of all the observed Y values of the dots of the scatter plot? thanks !
great.. thanks sir
this is an awesome video
So... How to get the confidence interval of y after fitting the model?
Just thank youi!
THANK YOUUUUUU
Do fish counts from a bay over time disqualify this kind of data for a Poisson distribution because it's a time series dataset?
When you talk about y being Poisson distributed, do you mean ‘the errors on y’? I have data where y is a combination of things only some of which carry counting-statistics uncertainties.
Holy fuck is this video good