Statistical Methodology for the Analysis of Repeated Duration Data in Behavioral Studies

Autor: Anne Vilain, Coriandre Vilain, Frédérique Letué, Marie-José Martinez, Adeline Samson
Přispěvatelé: Statistique pour le Vivant et l’Homme (SVH), Laboratoire Jean Kuntzmann (LJK ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), GIPSA - Perception, Contrôle, Multimodalité et Dynamiques de la parole (GIPSA-PCMD), Département Parole et Cognition (GIPSA-DPC), Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Grenoble Images Parole Signal Automatique (GIPSA-lab ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), GIPSA-Services (GIPSA-Services), ANR-11-LABX-0025,PERSYVAL-lab,Systemes et Algorithmes Pervasifs au confluent des mondes physique et numérique(2011), ANR-15-IDEX-0002,UGA,IDEX UGA(2015)
Rok vydání: 2017
Předmět:
Mixed model
Linguistics and Language
Time Factors
Computer science
computer.software_genre
050105 experimental psychology
Language and Linguistics
03 medical and health sciences
Speech and Hearing
Nonverbal communication
0302 clinical medicine
Text mining
Goodness of fit
Humans
Speech
0501 psychology and cognitive sciences
Duration data
[SHS.LANGUE]Humanities and Social Sciences/Linguistics
[STAT.AP]Statistics [stat]/Applications [stat.AP]
[SHS.STAT]Humanities and Social Sciences/Methods and statistics
Models
Statistical
Repetition (rhetorical device)
Gestures
business.industry
Multimethodology
05 social sciences
Data Interpretation
Statistical
Compulsive Behavior
Artificial intelligence
business
computer
[STAT.ME]Statistics [stat]/Methodology [stat.ME]
030217 neurology & neurosurgery
Natural language processing
Software
Gesture
Behavioral Research
Zdroj: Journal of Speech, Language, and Hearing Research
Journal of Speech, Language, and Hearing Research, 2018, 61 (3), pp.561-582. ⟨10.1044/2017_JSLHR-S-17-0135⟩
Journal of Speech, Language, and Hearing Research, American Speech-Language-Hearing Association, 2018, 61 (3), pp.561-582. ⟨10.1044/2017_JSLHR-S-17-0135⟩
ISSN: 1558-9102
1092-4388
DOI: 10.1044/2017_JSLHR-S-17-0135⟩
Popis: Purpose Repeated duration data are frequently used in behavioral studies. Classical linear or log-linear mixed models are often inadequate to analyze such data, because they usually consist of nonnegative and skew-distributed variables. Therefore, we recommend use of a statistical methodology specific to duration data. Method We propose a methodology based on Cox mixed models and written under the R language. This semiparametric model is indeed flexible enough to fit duration data. To compare log-linear and Cox mixed models in terms of goodness-of-fit on real data sets, we also provide a procedure based on simulations and quantile–quantile plots. Results We present two examples from a data set of speech and gesture interactions, which illustrate the limitations of linear and log-linear mixed models, as compared to Cox models. The linear models are not validated on our data, whereas Cox models are. Moreover, in the second example, the Cox model exhibits a significant effect that the linear model does not. Conclusions We provide methods to select the best-fitting models for repeated duration data and to compare statistical methodologies. In this study, we show that Cox models are best suited to the analysis of our data set.
Databáze: OpenAIRE
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