Publication

A generalized measurement model to quantify health: The multi-attribute preference response model

Krabbe, P. F. M., 21-Nov-2013, In : PLoS ONE. 8, 11, 12 p., e79494.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Krabbe, P. F. M. (2013). A generalized measurement model to quantify health: The multi-attribute preference response model. PLoS ONE, 8(11), [e79494]. https://doi.org/10.1371/journal.pone.0079494

Author

Krabbe, Paul F M. / A generalized measurement model to quantify health : The multi-attribute preference response model. In: PLoS ONE. 2013 ; Vol. 8, No. 11.

Harvard

Krabbe, PFM 2013, 'A generalized measurement model to quantify health: The multi-attribute preference response model', PLoS ONE, vol. 8, no. 11, e79494. https://doi.org/10.1371/journal.pone.0079494

Standard

A generalized measurement model to quantify health : The multi-attribute preference response model. / Krabbe, Paul F M.

In: PLoS ONE, Vol. 8, No. 11, e79494, 21.11.2013.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Krabbe PFM. A generalized measurement model to quantify health: The multi-attribute preference response model. PLoS ONE. 2013 Nov 21;8(11). e79494. https://doi.org/10.1371/journal.pone.0079494


BibTeX

@article{70382210d6274698a9b6ba7db704494e,
title = "A generalized measurement model to quantify health: The multi-attribute preference response model",
abstract = "After 40 years of deriving metric values for health status or health-related quality of life, the effective quantification of subjective health outcomes is still a challenge. Here, two of the best measurement tools, the discrete choice and the Rasch model, are combined to create a new model for deriving health values. First, existing techniques to value health states are briefly discussed followed by a reflection on the recent revival of interest in patients' experience with regard to their possible role in health measurement. Subsequently, three basic principles for valid health measurement are reviewed, namely unidimensionality, interval level, and invariance. In the main section, the basic operation of measurement is then discussed in the framework of probabilistic discrete choice analysis (random utility model) and the psychometric Rasch model. It is then shown how combining the main features of these two models yields an integrated measurement model, called the multi-attribute preference response (MAPR) model, which is introduced here. This new model transforms subjective individual rank data into a metric scale using responses from patients who have experienced certain health states. Its measurement mechanism largely prevents biases such as adaptation and coping. Several extensions of the MAPR model are presented. The MAPR model can be applied to a wide range of research problems. If extended with the self-selection of relevant health domains for the individual patient, this model will be more valid than existing valuation techniques.",
keywords = "QUALITY-OF-LIFE, CHOICE EXPERIMENTS, COMPARATIVE JUDGMENT, PATIENT PREFERENCES, UTILITY-MODELS, RASCH MODEL, VALUATION, STATES, QALYS, QUANTIFICATION",
author = "Krabbe, {Paul F M}",
year = "2013",
month = "11",
day = "21",
doi = "10.1371/journal.pone.0079494",
language = "English",
volume = "8",
journal = "PLOS-One",
issn = "1932-6203",
publisher = "PUBLIC LIBRARY SCIENCE",
number = "11",

}

RIS

TY - JOUR

T1 - A generalized measurement model to quantify health

T2 - The multi-attribute preference response model

AU - Krabbe, Paul F M

PY - 2013/11/21

Y1 - 2013/11/21

N2 - After 40 years of deriving metric values for health status or health-related quality of life, the effective quantification of subjective health outcomes is still a challenge. Here, two of the best measurement tools, the discrete choice and the Rasch model, are combined to create a new model for deriving health values. First, existing techniques to value health states are briefly discussed followed by a reflection on the recent revival of interest in patients' experience with regard to their possible role in health measurement. Subsequently, three basic principles for valid health measurement are reviewed, namely unidimensionality, interval level, and invariance. In the main section, the basic operation of measurement is then discussed in the framework of probabilistic discrete choice analysis (random utility model) and the psychometric Rasch model. It is then shown how combining the main features of these two models yields an integrated measurement model, called the multi-attribute preference response (MAPR) model, which is introduced here. This new model transforms subjective individual rank data into a metric scale using responses from patients who have experienced certain health states. Its measurement mechanism largely prevents biases such as adaptation and coping. Several extensions of the MAPR model are presented. The MAPR model can be applied to a wide range of research problems. If extended with the self-selection of relevant health domains for the individual patient, this model will be more valid than existing valuation techniques.

AB - After 40 years of deriving metric values for health status or health-related quality of life, the effective quantification of subjective health outcomes is still a challenge. Here, two of the best measurement tools, the discrete choice and the Rasch model, are combined to create a new model for deriving health values. First, existing techniques to value health states are briefly discussed followed by a reflection on the recent revival of interest in patients' experience with regard to their possible role in health measurement. Subsequently, three basic principles for valid health measurement are reviewed, namely unidimensionality, interval level, and invariance. In the main section, the basic operation of measurement is then discussed in the framework of probabilistic discrete choice analysis (random utility model) and the psychometric Rasch model. It is then shown how combining the main features of these two models yields an integrated measurement model, called the multi-attribute preference response (MAPR) model, which is introduced here. This new model transforms subjective individual rank data into a metric scale using responses from patients who have experienced certain health states. Its measurement mechanism largely prevents biases such as adaptation and coping. Several extensions of the MAPR model are presented. The MAPR model can be applied to a wide range of research problems. If extended with the self-selection of relevant health domains for the individual patient, this model will be more valid than existing valuation techniques.

KW - QUALITY-OF-LIFE

KW - CHOICE EXPERIMENTS

KW - COMPARATIVE JUDGMENT

KW - PATIENT PREFERENCES

KW - UTILITY-MODELS

KW - RASCH MODEL

KW - VALUATION

KW - STATES

KW - QALYS

KW - QUANTIFICATION

U2 - 10.1371/journal.pone.0079494

DO - 10.1371/journal.pone.0079494

M3 - Article

VL - 8

JO - PLOS-One

JF - PLOS-One

SN - 1932-6203

IS - 11

M1 - e79494

ER -

ID: 5997761