Welcome to the Analytix Thinking blog! The blog that is intended to help people think rightly about data and deciding what is true. First, the intended audience is those who are analytically/quantitatively minded, but the exposition is also meant to be consumable by those who are curious about such matters, but without formal mathematical, statistical … Continue reading No. 1: Introduction – Welcome to Analytix Thinking
No. 11: Some Beliefs in Priors
The probability that the null hypothesis is true is 0.50. How should we interpret that and then write it down mathematically?
No. 10 – Always do Subgroup IDENTIFICATION
You may have heard, “Always do subgroup analysis, but never believe them.” Don't believe this.
No. 9: Case Study – Genetic Subgroups and CV Disease
The over-reliance on p-values can lead to misinterpretation of data and a $150 million bet on a subgroup with scant evidence.
No. 8: Let’s Get Real – Bayes and Biomarkers
How do we know when an observed effect is real or spurious?
No. 7: What does p<0.05 mean anyway?
Some people say, "A p-value=0.05 is not very much evidence against the null hypothesis." Well then, how much evidence is it?
No. 6: Détente – The Peaceful Co-Existence of Significance Levels and Bayes
pr(B|A) ≠ 1 – pr(A|B). Why do we act like it ?!
No. 5: pr(You’re Bayesian) > 0.50
For too long statisticians have been peddling pr(data|hypothesis) when scientists [indeed all of us] want pr(hypothesis|data).
