“How not to collaborate with a biostatistician. This is what happens when two people are speaking different research languages! My current workplace is nothing like this, but I think most biostatisticians have had some kind of similar experiences like this in the past!”
YouTube: Biostatistics vs. Lab Research by JavaMama926
This site has reporting guidelines for all types of studies. These are checklists for writing all parts of a paper on these various study types.
CONSORT is for clinical trials and STROBE is for observational studies.
Equator Network: Reporting guidelines for main study types
Covariance and correlation are two statistical concepts that are closely related, both conceptually and by their name. The excerpts below are from a concise article that differentiates them.
“Correlation is a special case of covariance which can be obtained when the data is standardised. Now, when it comes to making a choice, which is a better measure of the relationship between two variables, correlation is preferred over covariance, because it remains unaffected by the change in location and scale, and can also be used to make a comparison between two pairs of variables.”
“The following points are noteworthy so far as the difference between covariance and correlation is concerned:
Learn about a piece of epidemiological history: one of the earliest examples of population-level clinical studies influencing medical practice. This podcast tells the story of how French physician Pierre Charles Alexandre Louis studied a group of patients and ended up discovering quantitative evidence on the detriment of bloodletting. Learning the history helps place these tools in a broader context, which isn’t crucial, but interesting nonetheless.
The first population study in history was born out of a dramatic debate involving leeches, “medical vampires,” professional rivalries, murder accusations, and, of course, bloodletting, all in the backdrop of the French Revolution. The second of a multipart series on the development of population medicine, this episode contextualizes Pierre Louis’ “numerical method,” his famous trial on bloodletting, and the birth of a new way for doctors to “know”.
Ronald Bayer, Ph.D., and Sandro Galea, M.D., Dr.P.H.
“The NIH’s most recent Estimates of Funding for Various Research, Condition, and Disease Categories report (www.report.nih.gov/categorical_spending.aspx) shows, for example, that total support in fiscal year 2014 for research areas including the words ‘gene,’ ‘genome,’ or ‘genetic’ was about 50% greater than funding for areas including the word ‘prevention.’…The proportion of NIH-funded projects with the words ‘public’ or ‘population’ in their title, for example, has dropped by 90% over the past 10 years, according to the NIH Reporter.”
“Without minimizing the possible gains to clinical care from greater realization of precision medicine’s promise, we worry that an unstinting focus on precision medicine by trusted spokespeople for health is a mistake — and a distraction from the goal of producing a healthier population.”
NEJM: Public Health in the Precision-Medicine Era by Ronald Bayer, Ph.D., and Sandro Galea, M.D., Dr.P.H.
“The fall of a prominent behavioral scientist tells of a system where research is judged not on merit, but on the attention it gets.”
“…remember that science is about asking questions, not pursuing answers.”
-James Hamblin, MD
The Atlantic: A Credibility Crisis in Food Science
“Earthlings is a 2005 American documentary film about humankind’s total dependence on animals for economic purposes. Presented in five chapters (pets, food, clothing, entertainment and scientific research) the film is narrated by Joaquin Phoenix, featuring music by Moby, and was written, produced and directed by Shaun Monson.”
How Not to Die describes the numerous health benefits of eating a plant-based diet. After reading through half the book, I watched Earthlings to see arguments from the animal rights activists for eliminating animal products from the dinner table. Personal health has always been my primary interest for minimizing meat consumption. But the message in this documentary is just as difficult to ignore as it is to watch.
There are some valid counter arguments to abandoning meat, which are listed in this reddit thread. The most compelling was that from an Indian man who argues he will not stop eating meat nor stop providing it for his family because he has genuine concern that his children my not survive due to malnutrition. Perhaps citizens of the more developed nations are the primary audience for this documentary.
I have watched a handful of anti-meat documentaries, and often they appeal to emotions such as shame, guilt, or anger. Earthlings takes a more objective role, showing film of industrial animal manufacturing in the United States. It was refreshing to be treated as a neutral observer, instead of being reprimanded. There are definite appeals to emotion, but the dialogue in the documentary is more calm than any I’ve seen before.
Earthlings has made me reconsider my current relationship with meat and animal products. I imagine I have grown up with more livestock experience than many of my neighbors. I learned from my family to slaughter fish, chickens, turkeys, and rabbits for food. I attempted a pescatarian diet for several years in my twenties, but only for personal health reasons. This is the most cognizant I have been of my indirect participation in the massive consumption of animals, and what that actually means.
Attributed to German Philosopher Arthur Schopenhauer (1788–1860)
“As much as 30% of the entire world’s stored data is generated in the health care industry. A single patient typically generates close to 80 megabytes each year in imaging and electronic medical record (EMR) data. This trove of data has obvious clinical, financial, and operational value for the health care industry, and the new value pathways that such data could enable have been estimated by McKinsey to be worth more than $300 billion annually in reduced costs alone…Read More”
NEJM Catalyst: Using It or Losing It? The Case for Data Scientists Inside Health Care by Marco D. Huesch, MBBS, PhD & Timothy J. Mosher, MD
