Poisson Regression Part II: How to interpret the Poisson regression output, what are the assumptions of Poisson regression model, issues with Poisson regression and Survival analysis.
Intro to Statistics Course: (https://bit.ly/2SQOxDH) ; More Statistics and R Programming Tutorials: (https://bit.ly/2Fhu9XU)
In this video tutorial we will
• Go over interpretation of Poisson regression output
– Calculate the log-rate, rate, expected count, RR
• Explain the assumptions of the Poisson Model
• Talk about common issues with Poisson
– Over dispersion
– Zero inflation
• and Introduce survival analysis
►► Watch More:
► Intro to Statistics Course: https://bit.ly/2SQOxDH
►R Tutorials for Data Science https://bit.ly/1A1Pixc
►Getting Started with R (Series 1): https://bit.ly/2PkTneg
►Graphs and Descriptive Statistics in R (Series 2): https://bit.ly/2PkTneg
►Probability distributions in R (Series 3): https://bit.ly/2AT3wpI
►Bivariate analysis in R (Series 4): https://bit.ly/2SXvcRi
►Linear Regression in R (Series 5): https://bit.ly/1iytAtm
►ANOVA Concept and with R https://bit.ly/2zBwjgL
Content Creator and Producer: Mary Clare Kennedy (M.A.), Research Associate at UBC
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This statistics video tutorial is prepared to support SPPH 500: Analytic Methods in Applied Epidemiology course offered in the School of Population and Public Health at the University of British Columbia (UBC). These videos are created as part of #marinstatslectures video tutorial series to support some courses at UBC (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free.
Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!