In the mid-19th century, Bernhard Riemann conceived of a new way to think about mathematical spaces, providing the foundation for modern geometry and physics.

Robustness is better assessed with a few thoughtful models than with billions of regressions

Synthese - The aim of the paper is to explore how people understand the concepts of health and disease, including the factors that influence their judgments about whether a condition is a disease...

This is an educational resource, with content at the cutting edge of scientific knowledge. It aims to improve future research, by improving researchers knowledge in the statistical inferences made, pl...

This is an educational resource, with content at the cutting edge of scientific knowledge. It aims to improve future research, by improving researchers knowledge in the statistical inferences made, pl...

Psychometric network models have become increasingly popular in psychology and the social sciences. Huth et al. show that a large proportion of reported network findings are based on weak or inconclusive evidence inviting caution when interpreting results.

Anthropic research on data-poisoning attacks in large language models

Interval scales are frequently assumed in educational and psychological research involving latent variables, but are rarely verified. This paper outlines methods for investigating the interval scale assumption when fitting the Rasch model to item response data. We study a Bayesian method for evaluating an item response dataset’s adherence to the cancellation axioms of additive conjoint measurement under the Rasch model, and compare the extent to which the axiom of double cancellation holds in the data at sample sizes of 250 and 1000 with varying test lengths, difficulty spreads, and levels of adherence to the Rasch model in the data-generating process. Because the statistic produced by the procedure is not directly interpretable as an indicator of whether an interval scale can be established, we develop and evaluate procedures for bootstrapping a null distribution of violation rates against which to compare results. At a sample size of 250, the method under investigation is not well powered to detect the violations of interval scaling that we simulate, but the procedure works quite consistently at N = 1000. That is, at moderate but achievable sample sizes, empirical tests for interval scaling are indeed possible.

Social scientists are now using large language models to create "silicon samples" - synthetic datasets intended to stand in for human respondents, aimed at revolutionising human subjects research. How...