Eq5Dmap: A Command for Mapping between EQ-5D-3L and EQ-5D-5L

In this article, we describe a new command, eq5dmap, for conditional prediction of the utility values of EQ-5D-5L (EQ-5D-3L) from observed or specified values of EQ-5D-3L (EQ-5D-5L) conditional on age and gender. Predictions can be made either from the five-item health descriptions or from the (exact or approximate) utility score. The prediction process is based on a joint statistical model of the two variants of EQ-5D that have been fit to alternative reference datasets (the National Data Bank for Rheumatic Diseases and a EuroQol Group coordinated data-collection study). The underlying model is a system of ordinal regressions with a flexible residual distribution specified as Gaussian or as a copula mixture. Use of the command is illustrated with an application that includes an investigation of the sensitivity of the mapping outcomes to the choice of reference dataset.

CONDITIONAL PREDICTION MARKETS AS CORPORATE DECISION SUPPORT SYSTEMS – AN EXPERIMENTAL COMPARISON WITH GROUP DELIBERATIONS

Predicting the future is an integral part of effective corporate decision making. Most firms face the critical challenge of aggregating information dispersed among its agents. These agents and thus the aggregation process are prone to judgmental biases. The primary research question we address is whether markets correct these biases better than group deliberations. Using an experimental setting, we find that information markets provide more accurate and less volatile forecasts than group deliberations. We also describe different sources of the behavioral biases we observe. For example, while a deliberating group can be led astray by an influential group member, traders tend to overweight personal preferences. Our results indicate that conditional prediction markets provide a more effective medium for aggregating information than group deliberations.