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Multiple Imputation of Industry and Occupation Codes in Census Public-use Samples Using Bayesian Logistic Regression
TL;DR: In this article, the authors describe methods used to create a new Census data base that can be used to study comparability of industry and occupation classification systems, and show how modifications of maximum likelihood methods were made for the modeling and imputation phases of the project.
Journal ArticleDOI
Mental health disparities within the LGBT population: A comparison between transgender and nontransgender individuals
Dejun Su,Jay A. Irwin,Christopher M. Fisher,Athena K. Ramos,Megan S. Kelley,Diana Ariss Rogel Mendoza,Jason D. Coleman +6 more
TL;DR: Compared to nontransgender LGB individuals, transgender individuals were more likely to report discrimination, depression symptoms, and attempted suicides and lack of self-acceptance of LGBT identity was associated with depression symptoms among transgender individuals.
Journal ArticleDOI
Bias reduction in exponential family nonlinear models
Ioannis Kosmidis,David Firth +1 more
TL;DR: In this article, a more general family of bias-reducing adjustments is developed for a broad class of univariate and multivariate generalized nonlinear models, and a necessary and sufficient condition is given for the existence of a penalized likelihood interpretation of the method.
Journal ArticleDOI
Morphology as a Predictor of Flower Choice by Bumble Bees
TL;DR: Morphological differences between bees were associated with use of different plant species; however, the role of bee morphology in flower choice was most evident when preferred plant species bloomed abundantly.
Journal ArticleDOI
A mixture model for the regression analysis of competing risks data
Martin G. Larson,Gregg E. Dinse +1 more
TL;DR: In this paper, a parametric mixture model is proposed to analyze failure-time data that are subject to censoring and multiple modes of failure, and the hazard rate for each conditional distribution of time to failure, given type of failure is modelled as the product of a piecewise exponential function of time and a loglinear function of the covariates.