Revisiting measurement models in psychosomatic medicine research

A latent variable approach

Maria Llabre, Stephanie L. Fitzpatrick

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In this article, we describe how a latent variable modeling approach to the specification of measurement error unifies and benefits traditional methods of examining reliability in psychology and medicine. The models presented include classical reliability and generalizability theory to account for measurement error, latent class analysis to assess sensitivity and specificity, and item response theory to improve questionnaire development. We also illustrate how working with latent variables, in addition to addressing measurement error, may help deal with some instances of missing data. Throughout the article, analyses and results from examples and published articles are presented to illustrate the advantage of working with latent variables.

Original languageEnglish
Pages (from-to)169-177
Number of pages9
JournalPsychosomatic Medicine
Volume74
Issue number2
DOIs
StatePublished - Feb 1 2012

Fingerprint

Psychosomatic Medicine
Medicine
Psychology
Sensitivity and Specificity
Research
Surveys and Questionnaires
Measurement Error

Keywords

  • latent variables
  • measurement error
  • reliability
  • validity

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Applied Psychology
  • Arts and Humanities (miscellaneous)
  • Developmental and Educational Psychology

Cite this

Revisiting measurement models in psychosomatic medicine research : A latent variable approach. / Llabre, Maria; Fitzpatrick, Stephanie L.

In: Psychosomatic Medicine, Vol. 74, No. 2, 01.02.2012, p. 169-177.

Research output: Contribution to journalArticle

@article{915b443254f6429b829ac2afaa6880b4,
title = "Revisiting measurement models in psychosomatic medicine research: A latent variable approach",
abstract = "In this article, we describe how a latent variable modeling approach to the specification of measurement error unifies and benefits traditional methods of examining reliability in psychology and medicine. The models presented include classical reliability and generalizability theory to account for measurement error, latent class analysis to assess sensitivity and specificity, and item response theory to improve questionnaire development. We also illustrate how working with latent variables, in addition to addressing measurement error, may help deal with some instances of missing data. Throughout the article, analyses and results from examples and published articles are presented to illustrate the advantage of working with latent variables.",
keywords = "latent variables, measurement error, reliability, validity",
author = "Maria Llabre and Fitzpatrick, {Stephanie L.}",
year = "2012",
month = "2",
day = "1",
doi = "10.1097/PSY.0b013e3182433a30",
language = "English",
volume = "74",
pages = "169--177",
journal = "Psychosomatic Medicine",
issn = "0033-3174",
publisher = "Lippincott Williams and Wilkins",
number = "2",

}

TY - JOUR

T1 - Revisiting measurement models in psychosomatic medicine research

T2 - A latent variable approach

AU - Llabre, Maria

AU - Fitzpatrick, Stephanie L.

PY - 2012/2/1

Y1 - 2012/2/1

N2 - In this article, we describe how a latent variable modeling approach to the specification of measurement error unifies and benefits traditional methods of examining reliability in psychology and medicine. The models presented include classical reliability and generalizability theory to account for measurement error, latent class analysis to assess sensitivity and specificity, and item response theory to improve questionnaire development. We also illustrate how working with latent variables, in addition to addressing measurement error, may help deal with some instances of missing data. Throughout the article, analyses and results from examples and published articles are presented to illustrate the advantage of working with latent variables.

AB - In this article, we describe how a latent variable modeling approach to the specification of measurement error unifies and benefits traditional methods of examining reliability in psychology and medicine. The models presented include classical reliability and generalizability theory to account for measurement error, latent class analysis to assess sensitivity and specificity, and item response theory to improve questionnaire development. We also illustrate how working with latent variables, in addition to addressing measurement error, may help deal with some instances of missing data. Throughout the article, analyses and results from examples and published articles are presented to illustrate the advantage of working with latent variables.

KW - latent variables

KW - measurement error

KW - reliability

KW - validity

UR - http://www.scopus.com/inward/record.url?scp=84857063513&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84857063513&partnerID=8YFLogxK

U2 - 10.1097/PSY.0b013e3182433a30

DO - 10.1097/PSY.0b013e3182433a30

M3 - Article

VL - 74

SP - 169

EP - 177

JO - Psychosomatic Medicine

JF - Psychosomatic Medicine

SN - 0033-3174

IS - 2

ER -