To Aid Statistical Inference, Emphasize Unconditional Descriptions of Statistics

09/18/2019
by   Sander Greenland, et al.
0

We have elsewhere reviewed proposals to reform terminology and improve interpretations of conventional statistics by emphasizing logical and information concepts over probability concepts. We here give detailed reasons and methods for reinterpreting statistics (including but not limited to) P-values and interval estimates in unconditional terms, which describe compatibility of observations with an entire set of analysis assumptions, rather than just a narrow target hypothesis. Such reinterpretations help avoid overconfident inferences whenever there is uncertainty about the assumptions used to derive and compute the statistical results. Examples of such assumptions include not only standard statistical modeling assumptions, but also assumptions about absence of systematic errors, protocol violations, and data corruption. Unconditional descriptions introduce uncertainty about such assumptions directly into statistical presentations of results, rather than leaving that only to the informal discussion that ensues. We thus view unconditional description as a vital component of good statistical training and presentation.

READ FULL TEXT
research
09/18/2019

Semantic and Cognitive Tools to Aid Statistical Inference: Replace Confidence and Significance by Compatibility and Surprise

Researchers often misinterpret and misrepresent statistical outputs. Thi...
research
04/03/2023

Connecting Simple and Precise P-values to Complex and Ambiguous Realities

Mathematics is a limited component of solutions to real-world problems, ...
research
01/18/2021

The Violating Assumptions Series: Simulated demonstrations to illustrate how assumptions can affect statistical estimates

When teaching and discussing statistical assumptions, our focus is often...
research
03/22/2018

Calibrating Model-Based Inferences and Decisions

As the frontiers of applied statistics progress through increasingly com...
research
09/23/2019

A reckless guide to P-values: local evidence, global errors

This chapter demystifies P-values, hypothesis tests and significance tes...
research
03/27/2013

Probabilistic Interpretations for MYCIN's Certainty Factors

This paper examines the quantities used by MYCIN to reason with uncertai...
research
09/17/2018

Contribution to the discussion of "When should meta-analysis avoid making hidden normality assumptions?": A Bayesian perspective

Contribution to the discussion of "When should meta-analysis avoid makin...

Please sign up or login with your details

Forgot password? Click here to reset