Study: Smokers in clinical studies who say they’ve quit often haven’t

A great example of differential misclassification bias that was a criticism of the secondhand smoke epidemiology — i.e., smokers pretending they were nonsmokers. Here’s a quantification of the effect.

Continue reading Study: Smokers in clinical studies who say they’ve quit often haven’t

Claim: BP oil spill did $17.2 billion in damage to natural resources, scientists find

Ridiculous. The real number is much closer to, if not zero. Reminds me of the first environmental project I ever worked on.

Continue reading Claim: BP oil spill did $17.2 billion in damage to natural resources, scientists find

Studies of scientific bias targeting the right problems, Stanford-led study finds

Stanford researchers close in on realities JunkScience.com exposed decades ago. But there is one important note to make here.

Continue reading Studies of scientific bias targeting the right problems, Stanford-led study finds

Double Standard: Financial ties between researchers and drug industry linked to positive trial results

So where is a similar report for climate, EPA-funded and other government-funded ‘researchers’?

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How Natural Variations Became Environmental Crises: The Numbers Racket

“It is bad enough that EPA and ATSDR intentionally and cynically manipulate the value their official, “safe” exposure levels for the express purpose of deceiving the general public and keeping the fear alive. Continue reading How Natural Variations Became Environmental Crises: The Numbers Racket

Misleading p-values showing up more often in biomedical journal articles, Stanford study finds

From the great John Ioannidis. Continue reading Misleading p-values showing up more often in biomedical journal articles, Stanford study finds

American Statistical Association releases statement on statistical significance and p-values

“Provides principles to improve the conduct and interpretation of quantitative science.” Continue reading American Statistical Association releases statement on statistical significance and p-values