Regression with Count Data: Poisson and Negative Binomial

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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

Matthew E. Clapham

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This clip alone gave me more information than I ever imagined. Thanks.

youngzproduction

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!

dtox

This is super useful to understand and apply the poisson regression analysis. one of the best tutorial I have ever watched. Many thanks!

Sefa-Safa

Hi ! Thank you for explaining theses models. Is it possible to provide the R code you 've been using to compute the
graphics ?

ibrahimkassoumhabibou

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

pabos

OMG, thank you so much for this very informative video, it really helped me a lot!

estefaniavillanueva

can you provide the code for the mean vs varaince plot for quasi poisson and negative binomial glm....that will be very helpful

kaustavchakrabarty

Thank you so much! Excellent explanation!

francoisdaudelin

Amazing video! Excellent explanation and very useful!

RqueErre

Thank you very much! This helped me quite a lot!!

HashanDananjaya

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 !

tonycardinal

Great ! Please keep posting more such videos

pranilbasu

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.

thejll

Thank you so much for posting this video!

cathrineb

Do fish counts from a bay over time disqualify this kind of data for a Poisson distribution because it's a time series dataset?

brazilfootball

So... How to get the confidence interval of y after fitting the model?

abcpsc

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