Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework

Caitlin Ward; Jacob Oleson; J. Bruce Tomblin; Elizabeth Walker

doi:10.1080/02664763.2020.1817346

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Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework

Journal article

Open access

Peer reviewed

Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework

Caitlin Ward, Jacob Oleson, J. Bruce Tomblin and Elizabeth Walker

Journal of applied statistics, Vol.49(2), pp.449-465

02/2022

DOI: 10.1080/02664763.2020.1817346

PMCID: PMC8992014

PMID: 35400783

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8992014View

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Abstract

Psychometric growth curve modeling techniques are used to describe a person's latent ability and how that ability changes over time based on a specific measurement instrument. However, the same instrument cannot always be used over a period of time to measure that latent ability. This is often the case when measuring traits longitudinally in children. Reasons may be that over time some measurement tools that were difficult for young children become too easy as they age resulting in floor effects or ceiling effects or both. We propose a Bayesian hierarchical model for such a scenario. Within the Bayesian model we combine information from multiple instruments used at different age ranges and having different scoring schemes to examine growth in latent ability over time. The model includes between-subject variance and within-subject variance and does not require linking item specific difficulty between the measurement tools. The model's utility is demonstrated on a study of language ability in children from ages one to ten who are hard of hearing where measurement tool specific growth and subject-specific growth are shown in addition to a group level latent growth curve comparing the hard of hearing children to children with normal hearing.

growth curve modeling

longitudinal analysis

Bayesian hierarchical models

psychometric modeling

language ability

Details

Title: Subtitle: Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework
Creators: Caitlin Ward - Department of Biostatistics, The University of Iowa
Jacob Oleson - Department of Biostatistics, The University of Iowa
J. Bruce Tomblin - Department of Communication Sciences and Disorders, The University of Iowa
Elizabeth Walker - Department of Communication Sciences and Disorders, The University of Iowa
Resource Type: Journal article
Publication Details: Journal of applied statistics, Vol.49(2), pp.449-465
DOI: 10.1080/02664763.2020.1817346
PMID: 35400783
PMCID: PMC8992014
NLM abbreviation: J Appl Stat
ISSN: 0266-4763
eISSN: 1360-0532
Publisher: Taylor & Francis
Grant note: DOI: 10.13039/100000055, name: NIH/National Institute on Deafness and Other Communication Disorders; DOI: 10.13039/100000030, name: Centers for Disease Control and Prevention; DOI: 10.13039/100000016, name: Department of Health and Human Services
Language: English
Electronic publication date: 09/05/2020
Date published: 02/2022
Academic Unit: Communication Sciences and Disorders; Iowa Neuroscience Institute; Biostatistics; Nursing; Otolaryngology
Record Identifier: 9984070260402771

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