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 language | English |
|---|---|
| Pages (from-to) | 169-177 |
| Number of pages | 9 |
| Journal | Psychosomatic Medicine |
| Volume | 74 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 1 2012 |
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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 journal › Article
}
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
C2 - 22286856
AN - SCOPUS:84857063513
VL - 74
SP - 169
EP - 177
JO - Psychosomatic Medicine
JF - Psychosomatic Medicine
SN - 0033-3174
IS - 2
ER -