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The episodic random utility model unifies time trade-off and discrete choice approaches in health state valuation.

Craig BM, Busschbach JJ - Popul Health Metr (2009)

Bottom Line: Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results.The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses.In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single estimator.

View Article: PubMed Central - HTML - PubMed

Affiliation: Health Outcomes & Behavior Program, Moffitt Cancer Center, 12902 Magnolia Drive, MRC-CANCONT, Tampa, Florida 33612-9416, USA. benjamin.craig@moffitt.org.

ABSTRACT

Background: To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation.

Methods: First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common instant RUM. For the interpretation of time trade-off (TTO) responses, we show that the episodic model implies a coefficient estimator, and the instant model implies a mean slope estimator. Secondly, we demonstrate these estimators and the differences between the estimates for 42 health states using TTO responses from the seminal Measurement and Valuation in Health (MVH) study conducted in the United Kingdom. Mean slopes are estimates with and without Dolan's transformation of worse-than-death (WTD) responses. Finally, we demonstrate an exploded probit estimator, an extension of the coefficient estimator for discrete choice data that accommodates both TTO and rank responses.

Results: By construction, mean slopes are less than or equal to coefficients, because slopes are fractions and, therefore, magnify downward errors in WTD responses. The Dolan transformation of WTD responses causes mean slopes to increase in similarity to coefficient estimates, yet they are not equivalent (i.e., absolute mean difference = 0.179). Unlike mean slopes, coefficient estimates demonstrate strong concordance with rank-based predictions (Lin's rho = 0.91). Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results.

Conclusion: The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses. In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single estimator.

No MeSH data available.


Related in: MedlinePlus

Comparison of Episodic RUM Estimates using Single and Both Responses for 42 EQ-5D Health States.
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Figure 3: Comparison of Episodic RUM Estimates using Single and Both Responses for 42 EQ-5D Health States.

Mentions: Figure 3 illustrates the relationship between episodic predictions. Compared to the rank-based predictions, coefficient estimates are slightly higher for mild health states and lower for states near death, which suggests the potential for duration dependence in health state valuation [15,16]. Future analysis may parameterize the duration effect and estimate the extent of adaptation. Overall, the pattern between episodic predictions suggests strong concordance.


The episodic random utility model unifies time trade-off and discrete choice approaches in health state valuation.

Craig BM, Busschbach JJ - Popul Health Metr (2009)

Comparison of Episodic RUM Estimates using Single and Both Responses for 42 EQ-5D Health States.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2667164&req=5

Figure 3: Comparison of Episodic RUM Estimates using Single and Both Responses for 42 EQ-5D Health States.
Mentions: Figure 3 illustrates the relationship between episodic predictions. Compared to the rank-based predictions, coefficient estimates are slightly higher for mild health states and lower for states near death, which suggests the potential for duration dependence in health state valuation [15,16]. Future analysis may parameterize the duration effect and estimate the extent of adaptation. Overall, the pattern between episodic predictions suggests strong concordance.

Bottom Line: Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results.The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses.In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single estimator.

View Article: PubMed Central - HTML - PubMed

Affiliation: Health Outcomes & Behavior Program, Moffitt Cancer Center, 12902 Magnolia Drive, MRC-CANCONT, Tampa, Florida 33612-9416, USA. benjamin.craig@moffitt.org.

ABSTRACT

Background: To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation.

Methods: First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common instant RUM. For the interpretation of time trade-off (TTO) responses, we show that the episodic model implies a coefficient estimator, and the instant model implies a mean slope estimator. Secondly, we demonstrate these estimators and the differences between the estimates for 42 health states using TTO responses from the seminal Measurement and Valuation in Health (MVH) study conducted in the United Kingdom. Mean slopes are estimates with and without Dolan's transformation of worse-than-death (WTD) responses. Finally, we demonstrate an exploded probit estimator, an extension of the coefficient estimator for discrete choice data that accommodates both TTO and rank responses.

Results: By construction, mean slopes are less than or equal to coefficients, because slopes are fractions and, therefore, magnify downward errors in WTD responses. The Dolan transformation of WTD responses causes mean slopes to increase in similarity to coefficient estimates, yet they are not equivalent (i.e., absolute mean difference = 0.179). Unlike mean slopes, coefficient estimates demonstrate strong concordance with rank-based predictions (Lin's rho = 0.91). Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results.

Conclusion: The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses. In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single estimator.

No MeSH data available.


Related in: MedlinePlus