MONTHLY MEMORY LANE: 3 years ago: February 2012. I am to mark in red three posts (or units) that seem most apt for general background on key issues in this blog. Given our Fisher reblogs, we’ve already seen many this month. So, I’m marking in red (1) The Triad, and (2) the Unit on Spanos’ misspecification tests. Plase see those posts for their discussion. The two posts from 2/8 are apt if you are interested in a famous case involving statistics at the Supreme Court. Beyond that it’s just my funny theatre of the absurd piece with Barnard. (Gelman’s is just a link to his blog.)
- (2/3) Senn Again (Gelman)
- (2/7) When Can Risk-Factor Epidemiology Provide Reliable Tests?
- (2/8) Guest Blogger: Interstitial Doubts About the Matrixx (Schachtman)
- (2/8) Distortions in the Court? (PhilStat/PhilStock) **Cobb on Zilizk & McCloskey
- (2/11) R.A. Fisher: Statistical Methods and Scientific Inference
- (2/11) JERZY NEYMAN: Note on an Article by Sir Ronald Fisher
- (2/12) E.S. Pearson: Statistical Concepts in Their Relation to Reality
REBLOGGED LAST WEEK
- (2/12) Guest Blogger. STEPHEN SENN: Fisher’s alternative to the alternative
- (2/15) Guest Blogger. Aris Spanos: The Enduring Legacy of R.A. Fisher
- (2/17) Two New Properties of Mathematical Likelihood
- (2/20) Statistical Theater of the Absurd: “Stat on a Hot Tin Roof”? (Rejected Post Feb 20)
M-S TESTING UNIT
- (2/22) Intro to Misspecification Testing: Ordering From A Full Diagnostic Menu (part 1)
- (2/23) Misspecification Testing: (part 2) A Fallacy of Error “Fixing”
- (2/27) Misspecification Testing: (part 3) Subtracting-out effects “on paper”
- (2/28) Misspecification Tests: (part 4) and brief concluding remarks
This new, once-a-month, feature began at the blog’s 3-year anniversary in Sept, 2014.
Previous 3 YEAR MEMORY LANES:
I’m continually amazed that with all the handwringing about p-values these days that people almost never talk about how ruinous to error probabilities failed assumptions are. My colleague, Aris Spanos, has shown glaring flaws in the statistical models being used in economics, and on which crucial policy decisions are based. Ioannidis seems also to have overlooked this glaring source of unreliability in his focus on poor predictions from research findings that are based on a single .05 p-value coupled with all manner of selection biases.