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  • Search: subject:"non-ignorable missing"
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Year of publication
Subject
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Non-ignorable missing data 2 Anreiz 1 Bayesian method 1 Befragung 1 Bias 1 Data collection method 1 Erhebungstechnik 1 Growth mixture models 1 HIV 1 Incentives 1 Interview 1 Leistungsanreiz 1 Longitudinal 1 Markov chain Monte Carlo methods 1 Model selecting criteria 1 Participation incentives 1 Performance incentive 1 Robust methods 1 Sampling 1 Selection bias 1 Selection models 1 Stichprobenerhebung 1 Survey design 1 Systematischer Fehler 1 Theorie 1 Theory 1 jointing modeling 1 non-ignorable missing 1 non-ignorable missing values 1 pattern-mixture 1 pseudo-imputation 1 single-bounded dichotomous choice contingent valuation studies 1
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Online availability
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Free 2 Undetermined 2
Type of publication
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Article 2 Book / Working Paper 1 Other 1
Type of publication (narrower categories)
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Article in journal 1 Aufsatz in Zeitschrift 1
Language
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English 2 Undetermined 2
Author
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Bärnighausen, Till 1 Canning, David 1 Lu, Zhenqiu 1 Mavromaras, Kostas 1 McGovern, Mark E. 1 Odejar, Maria Ana 1 Ryan, Mandy 1 Subhashis Ghosal 1 Sujit Ghosh 1 Zhang, Zhiyong 1 Zhu, Liansheng 1
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Institution
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Econometric Society 1
Published in...
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Computational Statistics & Data Analysis 1 Econometric Society 2004 North American Summer Meetings 1 Economics letters 1
Source
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RePEc 2 BASE 1 ECONIS (ZBW) 1
Showing 1 - 4 of 4
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Accounting for non-response bias using participation incentives and survey design : an application using gift vouchers
McGovern, Mark E.; Canning, David; Bärnighausen, Till - In: Economics letters 171 (2018), pp. 239-244
Persistent link: https://www.econbiz.de/10012021795
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Robust growth mixture models with non-ignorable missingness: Models, estimation, selection, and application
Lu, Zhenqiu; Zhang, Zhiyong - In: Computational Statistics & Data Analysis 71 (2014) C, pp. 220-240
Challenges in the analyses of growth mixture models include missing data, outliers, estimation, and model selection. Four non-ignorable missingness models to recover the information due to missing data, and three robust models to reduce the effect of non-normality are proposed. A full Bayesian...
Persistent link: https://www.econbiz.de/10010719680
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Analyzing Longitudinal Data with Non-ignorable Missing
Zhu, Liansheng - 2006
missingness is informative and hence not ignorable, it is generally difficult to analyze non-ignorable missing (NIM) data since …
Persistent link: https://www.econbiz.de/10009431266
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Messy Data Modelling in Health Care Contingent Valuation Studies
Odejar, Maria Ana; Mavromaras, Kostas; Ryan, Mandy - Econometric Society - 2004
This study addresses the complexity in modeling contingent valuation surveys with true zeros and non-ignorable missing …
Persistent link: https://www.econbiz.de/10005063706
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