ArticleBehavior research methods2023
Rating norms should be calculated from cumulative link mixed effects models.
Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 1 of them a synthesis that pooled it.
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Who cites it
38 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- When the meaningless make sense: Wordlikeness and affective norms for 4,800 pseudowords and 1,200 Spanish words.Behavior research methods · 2026Article
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- Elderspeak from the perspective of hospitalised geriatric patients-insights from a cross-sectional study using a mixed-methods design.Frontiers in medicine · 2026Article
- SocioLex-CZ: Normative estimates for socio-semantic dimensions of meaning for 2,999 words and 1,000 images.Behavior research methods · 2025Article
- Under my umbrella: Rating scales obscure statistical power and effect size heterogeneity.Behavior research methods · 2025Article
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4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Studies which provide norms of Likert ratings typically report per-item summary statistics. Traditionally, these summary statistics comprise the mean and the standard deviation (SD) of the ratings, and the number of observations. Such summary statistics can preserve the rank order of items, but provide distorted estimates of the relative distances between items because of the ordinal nature of Likert ratings. Inter-item relations in such ordinal scales can be more appropriately modelled by cumulative link mixed effects models (CLMMs). In a series of simulations, and with a reanalysis of an existing rating norms dataset, we show that CLMMs can be used to more accurately norm items, and can provide summary statistics analogous to the traditionally reported means and SDs, but which are disentangled from participants' response biases. CLMMs can be applied to solve important statistical issues that exist for more traditional analyses of rating norms.
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