Abstract
Most theories and hypotheses in psychology are verbal in nature, yet their evaluation overwhelmingly relies on inferential statistical procedures. The validity of the move from qualitative to quantitative analysis depends on the verbal and statistical expressions of a hypothesis being closely aligned - that is, that the two must refer to roughly the same set of hypothetical observations. Here, I argue that many applications of statistical inference in psychology fail to meet this basic condition. Focusing on the most widely used class of model in psychology - the linear mixed model - I explore the consequences of failing to statistically operationalize verbal hypotheses in a way that respects researchers'…
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Authors
1- TYTal YarkoniCorresponding
The University of Texas at Austin
Topics & keywords
Topics
Keywords
- Generalizability theory
- Operationalization
- Generalization
- Statistical inference
- Set (abstract data type)
- Psychological research
- Inference
- Statistical model
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