On the interpretation of removable interactions: A survey of the field 33 years after Loftus

In a classic 1978 Memory &Cognition article, Geoff Loftus explained why noncrossover interactions are removable. These removable interactions are tied to the scale of measurement for the dependent variable and therefore do not allow unambiguous conclusions about latent psychological processes. In the present article, we present concrete examples of how this insight helps prevent experimental psychologists from drawing incorrect conclusions about the effects of forgetting and aging. In addition, we extend the Loftus classification scheme for interactions to include those on the cusp between removable and nonremovable. Finally, we use various methods (i.e., a study of citation histories, a questionnaire for psychology students and faculty members, an analysis of statistical textbooks, and a review of articles published in the 2008 issue of Psychology andAging) to show that experimental psychologists have remained generally unaware of the concept of removable interactions. We conclude that there is more to interactions in a 2 × 2 design than meets the eye

Assessing Theoretical Conclusions With Blinded Inference to Investigate a Potential Inference Crisis

Scientific advances across a range of disciplines hinge on the ability to make inferences about unobservable theoretical entities on the basis of empirical data patterns. Accurate inferences rely on both discovering valid, replicable data patterns and accurately interpreting those patterns in terms of their implications for theoretical constructs. The replication crisis in science has led to widespread efforts to improve the reliability of research findings, but comparatively little attention has been devoted to the validity of inferences based on those findings. Using an example from cognitive psychology, we demonstrate a blinded-inference paradigm for assessing the quality of theoretical inferences from data. Our results reveal substantial variability in experts’ judgments on the very same data, hinting at a possible inference crisis

The distribution of subjective memory strength: List strength and response bias

Criss, A.H. (2009). The distribution of subjective memory strength: List strength and response bias. Cognitive Psychology, 297-319

Data/Aggregation

Raw data; code to score; code to convert to aggregate data; and aggregate data

aggregated data

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Analysis

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The Effects of Word Frequency and Context Variability in Cued Recall

Criss, A.H., Aue, W., & Smith, L. (2011). The Effects of Word Frequency and Context Variability in Cued Recall. Journal of Memory and Language, 64, 119-132. doi: 10.1016/j.jml.2010.10.00