Detecting time-specific differences between temporal nonlinear curves: Analyzing data from the visual world paradigm

Jacob J Oleson; Joseph E Cavanaugh; Bob McMurray; Grant Brown

doi:10.1177/0962280215607411

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Detecting time-specific differences between temporal nonlinear curves: Analyzing data from the visual world paradigm

Journal article

Peer reviewed

Detecting time-specific differences between temporal nonlinear curves: Analyzing data from the visual world paradigm

Jacob J Oleson, Joseph E Cavanaugh, Bob McMurray and Grant Brown

Statistical methods in medical research, Vol.26(6), pp.2708-2725

12/2017

DOI: 10.1177/0962280215607411

PMCID: PMC4805515

PMID: 26400088

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https://www.ncbi.nlm.nih.gov/pmc/articles/4805515View

Open Access

Abstract

In multiple fields of study, time series measured at high frequencies are used to estimate population curves that describe the temporal evolution of some characteristic of interest. These curves are typically nonlinear, and the deviations of each series from the corresponding curve are highly autocorrelated. In this scenario, we propose a procedure to compare the response curves for different groups at specific points in time. The method involves fitting the curves, performing potentially hundreds of serially correlated tests, and appropriately adjusting the overall alpha level of the tests. Our motivating application comes from psycholinguistics and the visual world paradigm. We describe how the proposed technique can be adapted to compare fixation curves within subjects as well as between groups. Our results lead to conclusions beyond the scope of previous analyses.

Acoustic Stimulation

Humans

Logistic Models

Models, Statistical

Psycholinguistics - statistics & numerical data

Normal Distribution

Algorithms

Language

Time Factors

Biostatistics - methods

Computer Simulation

Cochlear Implants

Nonlinear Dynamics

Details

Title: Subtitle: Detecting time-specific differences between temporal nonlinear curves: Analyzing data from the visual world paradigm
Creators: Jacob J Oleson - 1 Department of Biostatistics, The University of Iowa, Iowa City, Iowa, USA
Joseph E Cavanaugh - 1 Department of Biostatistics, The University of Iowa, Iowa City, Iowa, USA
Bob McMurray - 2 Department of Psychology, The University of Iowa, Iowa City, Iowa, USA
Grant Brown - 1 Department of Biostatistics, The University of Iowa, Iowa City, Iowa, USA
Resource Type: Journal article
Publication Details: Statistical methods in medical research, Vol.26(6), pp.2708-2725
DOI: 10.1177/0962280215607411
PMID: 26400088
PMCID: PMC4805515
NLM abbreviation: Stat Methods Med Res
ISSN: 0962-2802
eISSN: 1477-0334
Publisher: England
Grant note: R01 DC008089 / NIDCD NIH HHS M01 RR000059 / NCRR NIH HHS P50 DC000242 / NIDCD NIH HHS
Language: English
Date published: 12/2017
Academic Unit: Statistics and Actuarial Science; Communication Sciences and Disorders; Linguistics; Psychological and Brain Sciences; Iowa Neuroscience Institute; Biostatistics; Injury Prevention Research Center; Otolaryngology
Record Identifier: 9983985971402771

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