Beyond P-Value-Obsession: When are Statistical Hypothesis Tests Required and Appropriate? - Anne Margarian (German Journal of Agricultural Economics (GJAE), 2022)
Complementing more specific "p-value discussions", this paper presents fundamental arguments for when null hypothesis statistical significance tests (NHST) are required and appropriate. The arguments, which are paradigmatic rather than technical, are operationalised and broken down to the extent that their logic can be mapped into a decision tree for the use of NHST. We derive a perspective that does not ban p-values but proposes to minimize their use. P-values will become rather rare in (agricultural) economics if they are not applied in any cases, where the conditions for their proper use are violated or where their use is not appropriate or required in order to answer the questions asked of the data. The accompanying shift from prioritising inferential statistics to recognising the value of descriptive statistics requires not only a change in entrenched habits of thought. This shift also has the potential to trigger changes in the research processes and in the evaluation of new approaches within the disciplines.
Keywords: 330; p-value discussion; statistical inference; null hypothesis statistical significance tests; descriptive statistics; causal inference