ArticleLearning & behavior2021
Mixed effects modeling of Morris water maze data revisited: Bayesian censored regression.
Article in Learning & behavior, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Sex-specific effects of the atypical antipsychotic risperidone on performance in a risky decision-making task.Behavioural brain research · 2027Article
- Protocol for the standardized design of Morris water maze experiments and statistical analysis using SPSS.STAR protocols · 2026Article
- Understanding Individual Subject Differences through Large Behavioral Datasets: Analytical and Statistical Considerations.Perspectives on behavior science · 2024Article
- Statistical power and false positive rates for interdependent outcomes are strongly influenced by test type: Implications for behavioral neuroscience.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Young, Clark, Goffus, and Hoane (Learning and Motivation, 40(2), 160-177, 2009) documented significant advantages of linear and nonlinear mixed-effects modeling in the analysis of Morris water maze data. However, they also noted a caution regarding the impact of the common practice of ending a trial when the rat had not reached the platform by a preestablished deadline. The present study revisits their conclusions by considering a new approach that involves multilevel (i.e., mixed effects) censored generalized linear regression using Bayesian analysis. A censored regression explicitly models the censoring created by prematurely ending a trial, and the use of generalized linear regression incorporates the skewed distribution of latency data as well as the nonlinear relationships this can produce. This approach is contrasted with a standard multilevel linear and nonlinear regression using two case studies. The censored generalized linear regression better models the observed relationships, but the linear regression created mixed results and clearly resulted in model misspecification.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.