Authors@R: c(person("Paul M.", "Hargarten", email = "hargartenp@alumni.vcu.edu", role = c("aut", "cre")),
person("David C.", "Wheeler", email = "david.wheeler@vcuhealth.org", role = c("aut","rev","ths")) )
Description: The miWQS package handles the uncertainty due to below the detection limit in a correlated component mixture problem.  Researchers want to determine if a set/mixture of continuous and correlated components/chemicals is associated with an outcome and if so, which components are important in that mixture. These components share a common outcome but are interval-censored between zero and low thresholds, or detection limits, that may be different across the components. This package applies the multiple imputation (MI) procedure to the weighted quantile sum regression (WQS) methodology for continuous, binary, or count outcomes (Hargarten & Wheeler (2020) <doi:10.1016/j.envres.2020.109466>). The imputation models are: bootstrapping imputation (Lubin et.al (2004) <doi:10.1289/ehp.7199>), univariate Bayesian imputation (Hargarten & Wheeler (2020) <doi:10.1016/j.envres.2020.109466>), and multivariate Bayesian regression imputation.

Title: Individual data sets for micro-econometrics
Suggests: car, systemfit, sem, lmtest, sandwich, Ecdat
Description: These data sets come mainly from the Journal of Applied Econometrics' and the Journal of Business and Economic Statistics' data archives.
Packaged: Fri Oct 21 15:51:35 2005; yves

Description: Tools for microeconomic analysis and microeconomic modelling
Packaged: Mon Feb 21 11:19:38 2005; suapm095

Packaged: Mon May  9 14:16:40 2005; suapm095

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Packaged: Tue Feb  7 11:31:43 2006; suapm095

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Packaged: Sat Sep 30 23:22:47 2006; suapm095

Packaged: Fri May 11 16:09:52 2007; suapm095

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Packaged: Sun Aug 12 12:59:27 2007; suapm095

Packaged: Tue Sep 11 08:22:56 2007; suapm095