Combining growth curves when a longitudinal study switches measurement tools

Jacob J Oleson; Joseph E Cavanaugh; J Bruce Tomblin; Elizabeth Walker; Camille Dunn

doi:10.1177/0962280214534588

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Combining growth curves when a longitudinal study switches measurement tools

Journal article

Peer reviewed

Combining growth curves when a longitudinal study switches measurement tools

Jacob J Oleson, Joseph E Cavanaugh, J Bruce Tomblin, Elizabeth Walker and Camille Dunn

Statistical methods in medical research, Vol.25(6), pp.2925-2938

12/2016

DOI: 10.1177/0962280214534588

PMCID: PMC4227964

PMID: 24821002

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Abstract

When longitudinal studies are performed to investigate the growth of traits in children, the measurement tool being used to quantify the trait may need to change as the subjects' age throughout the study. Changing the measurement tool at some point in the longitudinal study makes the analysis of that growth challenging which, in turn, makes it difficult to determine what other factors influence the growth rate. We developed a Bayesian hierarchical modeling framework that relates the growth curves per individual for each of the different measurement tools and allows for covariates to influence the shapes of the curves by borrowing strength across curves. The method is motivated by and demonstrated by speech perception outcome measurements of children who were implanted with cochlear implants. Researchers are interested in assessing the impact of age at implantation and comparing the growth rates of children who are implanted under the age of two versus those implanted between the ages of two and four.

Age Factors

Humans

Child, Preschool

Deafness - physiopathology

Infant

Speech Perception - physiology

Growth - physiology

Young Adult

Cochlear Implantation

Adolescent

Bayes Theorem

Deafness - surgery

Child

Longitudinal Studies

Details

Title: Subtitle: Combining growth curves when a longitudinal study switches measurement tools
Creators: Jacob J Oleson - Department of Biostatistics, The University of Iowa, Iowa City, USA jacob-oleson@uiowa.edu
Joseph E Cavanaugh - Department of Biostatistics, The University of Iowa, Iowa City, USA
J Bruce Tomblin - Department of Otolaryngology - Head and Neck Surgery, Department of Communication Sciences and Disorders, The University of Iowa, Iowa City, USA
Elizabeth Walker - Department of Otolaryngology - Head and Neck Surgery, Department of Communication Sciences and Disorders, The University of Iowa, Iowa City, USA
Camille Dunn - Department of Otolaryngology - Head and Neck Surgery, Department of Communication Sciences and Disorders, The University of Iowa, Iowa City, USA
Resource Type: Journal article
Publication Details: Statistical methods in medical research, Vol.25(6), pp.2925-2938
DOI: 10.1177/0962280214534588
PMID: 24821002
PMCID: PMC4227964
NLM abbreviation: Stat Methods Med Res
ISSN: 0962-2802
eISSN: 1477-0334
Publisher: England
Grant note: M01 RR000059 / NCRR NIH HHS P50 DC000242 / NIDCD NIH HHS
Language: English
Date published: 12/2016
Academic Unit: Statistics and Actuarial Science; Communication Sciences and Disorders; Iowa Neuroscience Institute; Biostatistics; Injury Prevention Research Center; Otolaryngology
Record Identifier: 9983985892702771

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