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- W320644471 abstract "A companion paper proposed a new Generalized Heterogeneous Data Model (GHDM) to jointly model mixed types of dependent variables, including multiple nominal outcomes, multiple ordinal variables, and multiple count variables, as well as multiple continuous variables, and estimate the model using the maximum approximate composite marginal likelihood (MACML) method. This paper undertakes a simulation experiment within the virtual context of integrating residential location choice and travel behavior to evaluate the ability of the MACML approach to recover parameters. The simulation results show that the MACML approach effectively recovers underlying parameters, and also that ignoring the multi-dimensional nature of the relationship among mixed types of dependent variables can lead not only to inconsistent parameter estimation, but also have important implications for policy analysis." @default.
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- W320644471 date "2015-01-01" @default.
- W320644471 modified "2023-09-23" @default.
- W320644471 title "A Simulation Evaluation of the Maximum Approximate Composite Marginal Likelihood (MACML) Estimator for the Generalized Heterogeneous Data Model (GHMD)" @default.
- W320644471 hasPublicationYear "2015" @default.
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