2021 · 15 citations · 53 references
Social SciencesAnimal SciencesPsychologyAnimal BehaviorExperimental PsychologySocial CognitionAnimal CognitionAnimal StudiesExperimental Analysis Of BehaviorEye ContactHuman-animal InteractionsPerception In AnimalsBreed Differences In BehaviorCanine CognitionCollaborative NetworksCommunicative Gesture AnalysisLaboratory ReplicationMixed Methods Research DesignReplication Study DesignRepresentative Samples
To promote collaboration across canine science, address reproducibility issues, and advance open science practices within animal cognition, we have launched the ManyDogs consortium, modeled on similar ManyX projects in other fields. We aimed to create a collaborative network that (a) uses large, diverse samples to investigate and replicate findings, (b) promotes open science practices of preregistering hypotheses, methods, and analysis plans, (c) investigates the influence of differences across populations and breeds, and (d) examines how different research methods and testing environments influence the robustness of results. Our first study combines a phenomenon that appears to be highly robust—dogs’ ability to follow human pointing—with a question that remains controversial: do dogs interpret pointing as a social communicative gesture or as a simple associative cue? We collected preliminary data (N = 61) from a single laboratory on two conditions of a 2-alternative object choice task: (1) Ostensive (experimenter pointed to a baited cup after making eye-contact and saying the dog’s name); (2) Non-ostensive (experimenter pointed to a baited cup without making eye-contact or saying the dog’s name). Dogs followed the ostensive point, but not the non-ostensive point, significantly more often than expected by chance. Preliminary results also provided suggestive evidence for variability in point-following across dog breeds. The next phase is the global participation stage of the project. We propose to replicate this protocol in a large and diverse sample of research sites, simultaneously assessing replicability between labs and further investigating the question of dogs’ point-following comprehension.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
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Fitting Linear Mixed-Effects Models Using <b>lme4</b>
Douglas M. Bates, Martin Mächler, Benjamin M. Bolker et al. · Journal of Statistical Software · 2015 · 85.6K citations · Full text
Loo‐See Beh · Intellectum (Universidad de La Sabana) · 2010 · 16.1K citations · Full text
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