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Comparing Functional Trend and Learning among Groups in Intensive Binary Longitudinal Eye-Tracking Data using By-Variable Smooth Functions of GAMM.

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第一作者： Sun-Joo,Cho

第一单位： Vanderbilt University, Nashville, USA. sj.cho@vanderbilt.edu.

作者： Sun-Joo,Cho ^[1] ; Sarah,Brown-Schmidt ^[2] ; Sharice,Clough ^[3] ; Melissa C,Duff ^[4]

作者单位： Vanderbilt University, Nashville, USA. sj.cho@vanderbilt.edu. ^[1] Vanderbilt University, Nashville, USA. ^[2] Vanderbilt University Medical Center, Nashville, USA.;The Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands. ^[3] Vanderbilt University Medical Center, Nashville, USA. ^[4]

关键词 by-variable smooth function eye-tracking data generalized additive mixed model group comparisons intensive binary longitudinal data

DOI 10.1007/s11336-024-09986-1

PMID 39014288

发布时间 2025-11-19

基金项目

NIDCD grant R01 NIH DC017926/NR/NINR NIH HHS/United States

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Comparing Functional Trend and Learning among Groups in Intensive Binary Longitudinal Eye-Tracking Data using By-Variable Smooth Functions of GAMM.

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Comparing Functional Trend and Learning among Groups in Intensive Binary Longitudinal Eye-Tracking Data using By-Variable Smooth Functions of GAMM.

Psychometrika

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Psychometrika

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