Hi Loki,
The number of people who have died from Covid 19 has become a political issue. Also, it can sometimes be difficult to pinpoint someone's cause of death. An alternative is to use death certificate data to perform an excess all-cause death analysis. Moreover, one can perform an excess pneumonia death analysis; pneumonia is a common comorbidity of covid-19. A colleague and I performed such an analysis, the preprint is on
medrxiv. The data is available in CDC's website. Excess deaths analysis are useful during emergencies in general, not just pandemics. Principles of Managerial Statistics and Data Science shows some (simple) applications to estimate the excess deaths that occurred in Puerto Rico after Hurricane Maria. The technical aspects of two methods - which made adjustments for large population displacement - are available in this
article and the code is in
GitHub.
Kind regards,
Rob
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Roberto Rivera
Professor
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Original Message:
Sent: 08-05-2020 10:58
From: Loki Natarajan
Subject: Racial disparities in police stops in US cities
Thank you Dr. Rivera. These are fantastic datasets and materials.
If you (or anyone) has similar projects suitable for biostatistics PhD students, I would appreciate hearing about them.
Thank you.
Loki
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Loki Natarajan
Professor
UCSD
Original Message:
Sent: 08-04-2020 10:39
From: Roberto Rivera
Subject: Racial disparities in police stops in US cities
Of course! R codes and presentation slides in the companion website should help put into context many of the examples and case studies. Some additional ideas can also be found here
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Roberto Rivera
Professor
Original Message:
Sent: 08-04-2020 10:07
From: Leszek Gawarecki
Subject: Racial disparities in police stops in US cities
Thank you for your message. Would it be possible to make your examples and data sets available without adopting the book?
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Leszek Gawarecki
Original Message:
Sent: 08-03-2020 14:27
From: Roberto Rivera
Subject: Racial disparities in police stops in US cities
Our article "Racial disparities in police stops in US cities" was published in
Significance 17 (4).
The theme is a hot topic so instructors may want to discuss the article with their students. The article includes a link to the R code used for the analysis. To encourage student discussion it is best (if possible) to apply the analysis to regional data. Alternatively, consider using data sets from
"Principles of Managerial Statistics and Data Science", a book that applies data science and concepts in statistics on over 100 open data sets throughout the world. Interesting applications include:
- Assessing racial profiling during police traffic stops in San Diego (based on over 100,000 police stops),
- Modeling taxi fares in Chicago based on 133 million taxi rides,
- Creating an animated visualization of Baltimore housing data,
- Analyzing Canada tourism employment,
- Studying harassment of members of the LGBT community in the EU, and
- Estimating the Puerto Rican death toll due to the Hurricane Maria emergency, are just a small fraction of examples.
For many case studies and examples, R code is made available so that instructors or students can either reproduce the results or use the code as a starting point for a different analysis. You can find codes (and data sets) in the companion website.
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Roberto Rivera
Professor
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