Null Hypothesis Testing ≠ Scientific Inference: A Critique of the Shaky Premise at the Heart of the Science and Values Debate, and a Defense of Value-Neutral Risk Assessment.
Risk Anal
; 39(7): 1520-1532, 2019 07.
Article
en En
| MEDLINE
| ID: mdl-30742707
Many philosophers and statisticians argue that risk assessors are morally obligated to evaluate the probabilities and consequences of methodological error, and to base their decisions of whether to adopt a given parameter value, model, or hypothesis on those considerations. This argument is couched within the rubric of null hypothesis testing, which I suggest is a poor descriptive and normative model for risk assessment. Risk regulation is not primarily concerned with evaluating the probability of data conditional upon the null hypothesis, but rather with measuring risks, estimating the consequences of available courses of action and inaction, formally characterizing uncertainty, and deciding what to do based upon explicit values and decision criteria. In turn, I defend an ideal of value-neutrality, whereby the core inferential tasks of risk assessment-such as weighing evidence, estimating parameters, and model selection-should be guided by the aim of correspondence to reality. This is not to say that value judgments be damned, but rather that they should be accounted for within a structured approach to decision analysis, rather than embedded within risk assessment in an informal manner.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Proyectos de Investigación
/
Ciencia
/
Técnicas de Apoyo para la Decisión
/
Medición de Riesgo
/
Toma de Decisiones
Tipo de estudio:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Aspecto:
Equity_inequality
Límite:
Humans
Idioma:
En
Revista:
Risk Anal
Año:
2019
Tipo del documento:
Article
Pais de publicación:
Estados Unidos