Thoughts: A heated debate and condemnation of NB by @noah_greifer. Seems term confusion is also an issue in the field.
#poisson #regression #negativebinomial #countdata #overdispersion
stats.stackexchange.com/questions/65...
Thoughts: A heated debate and condemnation of NB by @noah_greifer. Seems term confusion is also an issue in the field.
#poisson #regression #negativebinomial #countdata #overdispersion
stats.stackexchange.com/questions/65...
Thoughts: A simple overview, but can be a starting point for IRRs in count models.
#irr #regression #stats #poisson #negativebinomial #effectsize
www.statology.org/incidence-ra...
Thoughts: A simple overview, but can be a starting point for IRRs in count models.
#irr #regression #stats #poisson #negativebinomial #effectsize
www.statology.org/incidence-ra...
Thoughts: Comprehensive #r tutorial for binary and count analysis with #brms
#logisticregression #count #poisson #negativebinomial #rstats #guide #tutorial #bayes #bayesian
bayesf22-notebook.classes.andrewheiss.com/bayes-rules/...
Thoughts: Comprehensive #r tutorial for binary and count analysis with #brms
#logisticregression #count #poisson #negativebinomial #rstats #guide #tutorial #bayes #bayesian
bayesf22-notebook.classes.andrewheiss.com/bayes-rules/...
Thoughts: Lots of cool work with new distributions for specific data/scenarios. Let's move beyond Normal.
#negativebinomial #weibull #distributions #MLE
link.springer.com/article/10.1...
Thoughts: Lots of cool work with new distributions for specific data/scenarios. Let's move beyond Normal.
#negativebinomial #weibull #distributions #MLE
link.springer.com/article/10.1...
Thoughts: A fairly comprehensive frequentist tutorial. Covers some edge cases, but doesn't explain them well.
#count #poisson #negativebinomial #IRR #tutorial #education
doi.org/10.1002/ijop...
Thoughts: A fairly comprehensive frequentist tutorial. Covers some edge cases, but doesn't explain them well.
#count #poisson #negativebinomial #IRR #tutorial #education
doi.org/10.1002/ijop...
Pat sells boxes of matches door to door, with a probability p = 0.4 of selling a box at each house. What's the chance she will exhaust all 30 houses in the village before selling the 5th box?
#NegativeBinomial #HCAndersen
Pat sells boxes of matches door to door, with a probability p = 0.4 of selling a box at each house. What's the chance she will exhaust all 30 houses in the village before selling the 5th box?
#NegativeBinomial #HCAndersen