Bayesian panel quantile regression for binary outcomes with correlated random effects: an application on crime recidivism in Canada
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[1] Roberta A. de A. Fagundes,et al. Interval quantile regression models based on swarm intelligence , 2018, Appl. Soft Comput..
[2] Breaking Bad: Mechanisms of Social Influence and the Path to Criminality in Juvenile Jails , 2017 .
[3] J. McCrary,et al. Criminal Deterrence: A Review of the Literature , 2017 .
[4] Colin Chen. A Finite Smoothing Algorithm for Quantile Regression , 2007 .
[5] Carlos Lamarche,et al. Penalized Quantile Regression with Semiparametric Correlated Effects: Applications with Heterogeneous Preferences , 2017, SSRN Electronic Journal.
[6] R. Koenker. Quantile regression for longitudinal data , 2004 .
[7] Mohammad Arshad Rahman,et al. Bayesian Quantile Regression for Ordinal Models , 2016, 2209.14700.
[8] G. Yin,et al. Bayesian Quantile Regression for Longitudinal Studies with Nonignorable Missing Data , 2010, Biometrics.
[9] Jerry A. Hausman,et al. Panel Data and Unobservable Individual Effects , 1981 .
[10] J. Geweke,et al. Contemporary Bayesian Econometrics and Statistics , 2005 .
[11] Y. Mundlak. On the Pooling of Time Series and Cross Section Data , 1978 .
[12] John Geweke,et al. Efficient Simulation from the Multivariate Normal and Student-t Distributions Subject to Linear Constraints and the Evaluation of Constraint Probabilities , 1991 .
[13] J H Albert,et al. Sequential Ordinal Modeling with Applications to Survival Data , 2001, Biometrics.
[14] John Geweke,et al. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments , 1991 .
[15] Ivan Jeliazkov,et al. FITTING AND COMPARISON OF MODELS FOR MULTIVARIATE ORDINAL OUTCOMES , 2008 .
[16] Stéphane Bonhomme,et al. Nonlinear Panel Data Estimation via Quantile Regressions , 2015 .
[17] George B. Dantzig,et al. Linear programming and extensions , 1965 .
[18] Gordon B. Dahl,et al. Incarceration, Recidivism, and Employment , 2016, Journal of Political Economy.
[19] C. Dahl,et al. Headlights on tobacco road to low birthweight outcomes , 2013 .
[20] Christopher Cornwell,et al. Estimating the Economic Model of Crime with Panel Data , 1994 .
[21] H. Kozumi,et al. Gibbs sampling methods for Bayesian quantile regression , 2011 .
[22] Kengo Kato,et al. Quantile Regression Methods for Longitudinal Data , 2017 .
[23] W. Newey,et al. Average and Quantile Effects in Nonseparable Panel Models , 2009, 0904.1990.
[24] L. Mark Berliner,et al. Subsampling the Gibbs Sampler , 1994 .
[25] J. Powell,et al. A quantile correlated random coefficients panel data model , 2016, Journal of Econometrics.
[26] M. Bottai,et al. Quantile regression for longitudinal data using the asymmetric Laplace distribution. , 2007, Biostatistics.
[27] M. A. Rahman. Quantile regression using metaheuristic algorithms , 2013 .
[28] Jeffrey M. Wooldridge,et al. Solutions Manual and Supplementary Materials for Econometric Analysis of Cross Section and Panel Data , 2003 .
[29] Naomi S. Altman,et al. Quantile regression , 2019, Nature Methods.
[30] M. Votruba,et al. Job displacement and crime: Evidence from Norwegian register data , 2019 .
[31] Sanjay Mehrotra,et al. On the Implementation of a Primal-Dual Interior Point Method , 1992, SIAM J. Optim..
[32] T. Lancaster,et al. Bayesian Quantile Regression , 2005 .
[33] Taban Baghfalaki,et al. Bayesian quantile regression for joint modeling of longitudinal mixed ordinal and continuous data , 2018, Commun. Stat. Simul. Comput..
[34] D. Griffel. Linear programming 2: Theory and extensions , by G. B. Dantzig and M. N. Thapa. Pp. 408. £50.00. 2003 ISBN 0 387 00834 9 (Springer). , 2004, The Mathematical Gazette.
[35] C. S. Davis. Semi-parametric and non-parametric methods for the analysis of repeated measurements with applications to clinical trials. , 1991, Statistics in medicine.
[36] Gary Chamberlain,et al. Analysis of Covariance with Qualitative Data , 1979 .
[37] Mohammad Arshad Rahman,et al. Flexible Bayesian Quantile Regression in Ordinal Models , 2016, Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B.
[38] Genya Kobayashi,et al. Bayesian analysis of quantile regression for censored dynamic panel data , 2012, Comput. Stat..
[39] C. Dahl,et al. CREATES Research Paper 2008-20 Headlights on tobacco road to low birthweight outcomes Evidence from a battery of quantile regression estimators and a heterogeneous panel , 2011 .
[40] Dirk Van den Poel,et al. Binary quantile regression: a Bayesian approach based on the asymmetric Laplace distribution , 2012 .
[41] Dongmei Liu,et al. Likelihood Estimation of Conjugacy Relationships in Linear Models with Applications to High-Throughput Genomics , 2009, The international journal of biostatistics.
[42] Matthew Harding,et al. PANEL PROBIT WITH FLEXIBLE CORRELATED EFFECTS: QUANTIFYING TECHNOLOGY SPILLOVERS IN THE PRESENCE OF LATENT HETEROGENEITY , 2012 .
[43] Garima Siwach. Unemployment shocks for individuals on the margin: Exploring recidivism effects , 2018, Labour Economics.
[44] H. Lian,et al. Bayesian quantile regression for longitudinal data models , 2012 .
[45] Carlos Lamarche,et al. Robust penalized quantile regression estimation for panel data , 2010 .
[46] B. Baltagi. Estimating an economic model of crime using panel data from North Carolina , 2006 .
[47] R. Koenker,et al. Computing regression quantiles , 1987 .
[48] Mohammad Arshad Rahman,et al. Binary and Ordinal Data Analysis in Economics: Modeling and Estimation , 2013 .
[49] Rahim Alhamzawi,et al. Bayesian quantile regression for ordinal longitudinal data , 2016, 1603.00297.
[50] Narendra Karmarkar,et al. A new polynomial-time algorithm for linear programming , 1984, Comb..
[51] Donald Hedeker,et al. Application of Random-Effects Probit Regression Models , 1994 .
[52] Stanislav Volgushev,et al. Panel data quantile regression with grouped fixed effects , 2018, Journal of Econometrics.
[53] Carlos Lamarche,et al. Estimation of Censored Quantile Regression for Panel Data With Fixed Effects , 2013 .
[54] William A. Link,et al. On thinning of chains in MCMC , 2012 .
[55] G. Chamberlain. Multivariate regression models for panel data , 1982 .
[56] S. Haberman. Analysis of qualitative data , 1978 .
[57] Luc Devroye,et al. Random variate generation for the generalized inverse Gaussian distribution , 2012, Statistics and Computing.
[58] M. Arellano,et al. On the testing of correlated effects with panel data , 1993 .
[59] Marco Geraci,et al. Linear quantile mixed models , 2013, Statistics and Computing.
[60] Robust Linear Static Panel Data Models Using Ε-Contamination , 2017 .
[61] Gregory Kordas. Smoothed binary regression quantiles , 2006 .
[62] Ivan Jeliazkov,et al. The impact of estimation uncertainty on covariate effects in nonlinear models , 2018 .
[63] Kaj Madsen,et al. A Finite Smoothing Algorithm for Linear l1 Estimation , 1993, SIAM J. Optim..
[64] R. Koenker. Quantile Regression: Name Index , 2005 .
[65] B. Baltagi,et al. Robust Linear Static Panel Data Models Using Ε-Contamination , 2017, SSRN Electronic Journal.
[66] Siddhartha Chib,et al. Inference in Semiparametric Dynamic Models for Binary Longitudinal Data , 2006 .
[67] I. Barrodale,et al. An Improved Algorithm for Discrete $l_1 $ Linear Approximation , 1973 .
[68] Toshi H. Arimura,et al. Same concerns, same responses? A Bayesian quantile regression analysis of the determinants for supporting nuclear power generation in Japan , 2015 .
[69] Markku Rahiala,et al. Panel Data , 2011, International Encyclopedia of Statistical Science.
[70] Badi H. Baltagi,et al. Fixed effects, random effects or Hausman–Taylor?: A pretest estimator , 2003 .
[71] Rahim Alhamzawi,et al. Bayesian single-index quantile regression for ordinal data , 2018, Commun. Stat. Simul. Comput..
[72] T. Baghfalaki,et al. Bayesian quantile regression for analyzing ordinal longitudinal responses in the presence of non-ignorable missingness , 2018 .
[73] Art B. Owen,et al. Statistically Efficient Thinning of a Markov Chain Sampler , 2015, ArXiv.
[74] Jing Wang,et al. Bayesian quantile regression for parametric nonlinear mixed effects models , 2012, Stat. Methods Appl..
[75] Rahim Alhamzawi,et al. Bayesian model selection in ordinal quantile regression , 2016, Comput. Stat. Data Anal..
[76] W. Greene. Panel Data Models for Discrete Choice , 2015 .
[77] John Geweke,et al. Contemporary Bayesian Econometrics and Statistics: Geweke/Contemporary Bayesian Econometrics and Statistics , 2005 .
[78] S. Chib,et al. Bayesian analysis of binary and polychotomous response data , 1993 .
[79] Cristina Davino,et al. Quantile Regression: Theory and Applications , 2013 .
[80] R. Koenker,et al. Regression Quantiles , 2007 .
[81] C. Geyer. Markov Chain Monte Carlo Maximum Likelihood , 1991 .
[82] D. Hedeker,et al. Application of random-effects probit regression models. , 1994, Journal of consulting and clinical psychology.
[83] Ivan A. Canay. A Simple Approach to Quantile Regression for Panel Data , 2011 .
[84] J. Hausman. Specification tests in econometrics , 1978 .
[85] A. Cameron,et al. Microeconometrics: Methods and Applications , 2005 .
[86] Gary Chamberlain,et al. Chapter 22 Panel data , 1984 .
[87] M. Bottai,et al. Mixed-Effects Models for Conditional Quantiles with Longitudinal Data , 2009, The international journal of biostatistics.
[88] Michael Wooldridge,et al. Econometric Analysis of Cross Section and Panel Data, 2nd Edition , 2001 .
[89] Mohammad Arshad Rahman,et al. Estimation and Applications of Quantile Regression for Binary Longitudinal Data , 2019, Topics in Identification, Limited Dependent Variables, Partial Observability, Experimentation, and Flexible Modeling: Part B.
[90] Jason Abrevaya,et al. The Effects of Birth Inputs on Birthweight , 2008 .
[91] B. Baltagi,et al. Econometric Analysis of Panel Data , 2020, Springer Texts in Business and Economics.
[92] Jason Abrevaya,et al. The effects of birth inputs on birthweight : evidence from quantile estimation on panel data by , 2007 .
[93] J. Wooldridge,et al. Correlated Random Effects Models with Endogenous Explanatory Variables and Unbalanced Panels , 2019, Annals of Economics and Statistics.
[94] George B. Dantzig,et al. Linear Programming 1: Introduction , 1997 .
[95] John M. Olin. On MCMC sampling in hierarchical longitudinal models , 1999 .