DOI: 10.21007/etd.cghs.2011.0355
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Evaluating Consumer Preferences for Medicare Part D Using Conjoint Analysis

Abstract: The establishment of an outpatient prescription drug benefit in Medicare, Medicare Part D, was one of the more significant events in United States healthcare reform history. Many seniors have chosen to enroll in the plan as the program has an enrollment of over 27 million. One central premise of Medicare Part D was that the plan would be administered entirely through private insurance plans. Because many plans would be competing against one another for potential beneficiaries, it was expected that companies wo… Show more

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Cited by 2 publications
(3 citation statements)
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References 53 publications
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“…This distribution answers predictive queries about unseen data using expectations. Each possible configuration of the weights, weighted according to the posterior distribution, makes a prediction about the unknown label given the test data item x [63].…”
Section: Theoretical Frameworkmentioning
confidence: 99%
“…This distribution answers predictive queries about unseen data using expectations. Each possible configuration of the weights, weighted according to the posterior distribution, makes a prediction about the unknown label given the test data item x [63].…”
Section: Theoretical Frameworkmentioning
confidence: 99%
“…This becomes relevant since, due to the lack of research on mobile application characteristics in a tourism setting, there is no "a priori" knowledge regarding preferences. A significant difference between attributes only exists if the upper confidence interval (CI) for one attribute is greater than the lower CI for another attribute (Manalo, 1990;Wingate, 2011). This means that any attribute comparison with overlapping values in their CI will be considered not statistically different.…”
Section: H5: the Part-worths Are Significantly Different Between Firsmentioning
confidence: 99%
“…H2 is designed to infer whether the levels of a particular attribute are statistically significant. The zero-centered part-worth estimates are examined at the 2.5 percentile and the 97.5 percentile to obtain a 95 per cent CI and determine whether they were statistically significantly different from zero (Wingate, 2011). If the CI values for a specific level cross zero, then they are not assumed to be significant.…”
mentioning
confidence: 99%