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Nicholas Jon Horton

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Nicholas Horton & Garrett Fitzmaurice, 2005. "Analysis of multiple source/multiple informant data in Stata," North American Stata Users' Group Meetings 2005 1, Stata Users Group.

    Cited by:

    1. Maria Paola Caria & Rino Bellocco & Maria Rosaria Galanti & Nicholas J. Horton, 2011. "The impact of different sources of body mass index assessment on smoking onset: An application of multiple-source information models," Stata Journal, StataCorp LP, vol. 11(3), pages 386-402, September.
    2. Xu Xu & Peter Z. G. Qian & Qing Liu, 2016. "Samurai Sudoku-Based Space-Filling Designs for Data Pooling," The American Statistician, Taylor & Francis Journals, vol. 70(1), pages 1-8, February.

  2. Nicholas Horton, 2001. "Fitting Generalized Estimating Equation (GEE) Regression Models in Stata," North American Stata Users' Group Meetings 2001 1.1, Stata Users Group.

    Cited by:

    1. Debasish Kumar Das & Champa Bati Dutta, 2013. "Global Financial Crisis And Foreign Development Assistance Shocks In Least Developing Countries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(2), pages 1-41, June.

Articles

  1. Nicholas Jon Horton, 2016. "Discussion: Making Progress in a Crowded Market," International Statistical Review, International Statistical Institute, vol. 84(2), pages 179-181, August.

    Cited by:

    1. Iddo Gal & Irena Ograjenšek, 2016. "Rejoinder: More on Enhancing Statistics Education with Qualitative Ideas," International Statistical Review, International Statistical Institute, vol. 84(2), pages 202-209, August.

  2. Nicholas J. Horton, 2015. "Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward," The American Statistician, Taylor & Francis Journals, vol. 69(2), pages 138-145, May.

    Cited by:

    1. Sitsofe Tsagbey & Miguel de Carvalho & Garritt L. Page, 2017. "All Data are Wrong, but Some are Useful? Advocating the Need for Data Auditing," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 231-235, July.
    2. Constance H. McLaren & Bruce J. McLaren, 2018. "SCOTS: The Searchable Collection of Time Series," INFORMS Transactions on Education, INFORMS, vol. 19(1), pages 12-22, September.
    3. Cimpoeru, Smaranda & Roman, Monica, 2018. "Statistical Literacy and Attitudes Towards Statistics of Romanian Undergraduate Students," MPRA Paper 90452, University Library of Munich, Germany, revised 31 Aug 2018.

  3. J. Hardin & R. Hoerl & Nicholas J. Horton & D. Nolan & B. Baumer & O. Hall-Holt & P. Murrell & R. Peng & P. Roback & D. Temple Lang & M. D. Ward, 2015. "Data Science in Statistics Curricula: Preparing Students to “Think with Data”," The American Statistician, Taylor & Francis Journals, vol. 69(4), pages 343-353, November.

    Cited by:

    1. Roger W. Hoerl & Ronald D. Snee, 2017. "Statistical Engineering: An Idea Whose Time Has Come?," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 209-219, July.
    2. Giani Ionel Gradinaru & Vasile Dinu & Catalin-Laurentiu Rotaru & Andreea Toma, 2024. "The Development of Educational Competences for Romanian Students in the Context of the Evolution of Data Science and Artificial Intelligence," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 26(65), pages 1-14, February.
    3. David Gil & Magnus Johnsson & Higinio Mora & Julian Szymański, 2019. "Review of the Complexity of Managing Big Data of the Internet of Things," Complexity, Hindawi, vol. 2019, pages 1-12, February.
    4. Hassani, Hossein & Beneki, Christina & Silva, Emmanuel Sirimal & Vandeput, Nicolas & Madsen, Dag Øivind, 2021. "The science of statistics versus data science: What is the future?," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    5. Simons, Andrew M., 2020. "Making Business Statistics Come Alive: Incorporating Field Trial Data from a Cookstove Study into the Classroom," Applied Economics Teaching Resources (AETR), Agricultural and Applied Economics Association, vol. 2(3), July.

  4. Nicholas J. Horton & Johanna S. Hardin, 2015. "Teaching the Next Generation of Statistics Students to “Think With Data”: Special Issue on Statistics and the Undergraduate Curriculum," The American Statistician, Taylor & Francis Journals, vol. 69(4), pages 259-265, November.

    Cited by:

    1. Roger W. Hoerl & Ronald D. Snee, 2017. "Statistical Engineering: An Idea Whose Time Has Come?," The American Statistician, Taylor & Francis Journals, vol. 71(3), pages 209-219, July.
    2. Alexander B. Sibley & Zhiguo Li & Yu Jiang & Yi-Ju Li & Cliburn Chan & Andrew Allen & Kouros Owzar, 2018. "Facilitating the Calculation of the Efficient Score Using Symbolic Computing," The American Statistician, Taylor & Francis Journals, vol. 72(2), pages 199-205, April.
    3. Nicholas Jon Horton, 2016. "Discussion: Making Progress in a Crowded Market," International Statistical Review, International Statistical Institute, vol. 84(2), pages 179-181, August.
    4. Constance H. McLaren & Bruce J. McLaren, 2018. "SCOTS: The Searchable Collection of Time Series," INFORMS Transactions on Education, INFORMS, vol. 19(1), pages 12-22, September.
    5. Amy L. Phelps & Kathryn A. Szabat, 2017. "The Current Landscape of Teaching Analytics to Business Students at Institutions of Higher Education: Who is Teaching What?," The American Statistician, Taylor & Francis Journals, vol. 71(2), pages 155-161, April.

  5. Mahnaz Mahdavi & Nicholas J. Horton, 2014. "Financial Knowledge among Educated Women: Room for Improvement," Journal of Consumer Affairs, Wiley Blackwell, vol. 48(2), pages 403-417, June.

    Cited by:

    1. Alfonso Arellano & Noelia Camara & David Tuesta, 2014. "El efecto de la autoconfianza en el conocimiento financiero," Working Papers 1427, BBVA Bank, Economic Research Department.
    2. Yoshihiko Kadoya & Naheed Rabbani & Mostafa Saidur Rahim Khan, 2022. "Insurance literacy among older people in Japan: The role of socio‐economic status," Journal of Consumer Affairs, Wiley Blackwell, vol. 56(2), pages 788-805, June.
    3. Tabea Bucher-Koenen & Annamaria Lusardi & Rob Alessie & Maarten van Rooij, 2017. "How Financially Literate Are Women? An Overview and New Insights," Journal of Consumer Affairs, Wiley Blackwell, vol. 51(2), pages 255-283, July.
    4. Alfonso Arellano & Noelia Camara & David Tuesta, 2015. "Explaining the Gender Gap in Financial Literacy: the Role of Non-Cognitive Skills," Working Papers 15/32, BBVA Bank, Economic Research Department.
    5. Paraboni, Ana Luiza & da Costa, Newton, 2021. "Improving the level of financial literacy and the influence of the cognitive ability in this process," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 90(C).
    6. Wandeda, Dickson Onyango & Were, Maureen, 2023. "Financial Decision-Making Dynamics Among Women and Financial Health in Kenya: Propensity Score Matching," African Journal of Economic Review, African Journal of Economic Review, vol. 11(5), December.
    7. Bucher-Koenen, Tabea & Alessie, Rob & Lusardi, Annamaria & van Rooij, Maarten, 2021. "Fearless Woman: Financial Literacy and Stock Market Participation," ZEW Discussion Papers 21-015, ZEW - Leibniz Centre for European Economic Research.
    8. José J. Cao‐Alvira & Amalia Novoa‐Hoyos & Alexander Núñez‐Torres, 2021. "On the financial literacy, indebtedness, and wealth of Colombian households," Review of Development Economics, Wiley Blackwell, vol. 25(2), pages 978-993, May.
    9. Laura Hospido & Sara Izquierdo & Margarita Machelett, 2021. "The gender gap in financial competences (556 KB)," Economic Bulletin, Banco de España, issue 1/2021.
    10. Antonia Grohmann & Annekathrin Schoofs, 2018. "Financial Literacy and Intra-Household Decision Making: Evidence from Rwanda," Discussion Papers of DIW Berlin 1720, DIW Berlin, German Institute for Economic Research.
    11. M. M. Naeser Seldal & Ellen K. Nyhus, 2022. "Financial Vulnerability, Financial Literacy, and the Use of Digital Payment Technologies," Journal of Consumer Policy, Springer, vol. 45(2), pages 281-306, June.
    12. Annamaria Lusardi & Olivia S. Mitchell, 2013. "The Economic Importance of Financial Literacy: Theory and Evidence," CeRP Working Papers 134, Center for Research on Pensions and Welfare Policies, Turin (Italy).
    13. Alfonso Arellano & Noelia Camara & David Tuesta, 2014. "The effect of self-confidence on financial literacy," Working Papers 1428, BBVA Bank, Economic Research Department.
    14. Davoli, Maddalena & Rodríguez-Planas, Núria, 2020. "Culture and Adult Financial Literacy: Evidence from the United States," IZA Discussion Papers 13349, Institute of Labor Economics (IZA).
    15. Davoli, Maddalena & Rodríguez-Planas, Núria, 2021. "Preferences, Financial Literacy, and Economic Development," IZA Discussion Papers 14759, Institute of Labor Economics (IZA).
    16. Zhou, Yang & Yang, Manfang & Gan, Xu, 2023. "Education and financial literacy: Evidence from compulsory schooling law in China," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 335-346.
    17. Tracey West & Michelle Cull, 2020. "Future Expectations and Financial Satisfaction," Economic Papers, The Economic Society of Australia, vol. 39(4), pages 318-335, December.
    18. Bahovec Vlasta & Barbić Dajana & Palić Irena, 2017. "The Regression Analysis of Individual Financial Performance: Evidence from Croatia," Business Systems Research, Sciendo, vol. 8(2), pages 1-13, September.
    19. Maddalena Davoli, 2023. "A, B, or C? Question Format and the Gender Gap in Financial Literacy," Economics of Education Working Paper Series 0206, University of Zurich, Department of Business Administration (IBW).
    20. Jake Anders & John Jerrim & Lindsey Macmillan, 2022. "Socio-economic inequality in young people's financial capabilities," CEPEO Working Paper Series 22-03, UCL Centre for Education Policy and Equalising Opportunities, revised Feb 2022.
    21. Antonia Grohmann & Olaf Hübler & Roy Kouwenberg & Lukas Menkhoff, 2016. "Financial Literacy: Thai Middle Class Women Do Not Lag behind," Discussion Papers of DIW Berlin 1615, DIW Berlin, German Institute for Economic Research.
    22. Marie-Hélène BROIHANNE, 2021. "Testing the gender gap in subjective financial literacy of spouses," Working Papers of LaRGE Research Center 2021-08, Laboratoire de Recherche en Gestion et Economie (LaRGE), Université de Strasbourg.

  6. Kathryn M. Aloisio & Sonja A. Swanson & Nadia Micali & Alison Field & Nicholas J. Horton, 2014. "Analysis of partially observed clustered data using generalized estimating equations and multiple imputation," Stata Journal, StataCorp LP, vol. 14(4), pages 863-883, December.

    Cited by:

    1. Jumah, Adusei & Somua-Wiafe, Ernest & Apom, Barnabas, 2021. "On the willingness to exit street hawking," IHS Working Paper Series 34, Institute for Advanced Studies.
    2. Liu, Li & Xiang, Liming, 2019. "Missing covariate data in generalized linear mixed models with distribution-free random effects," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 1-16.

  7. Nicholas J. Horton, 2013. "I Hear, I Forget. I Do, I Understand: A Modified Moore-Method Mathematical Statistics Course," The American Statistician, Taylor & Francis Journals, vol. 67(4), pages 219-228, November.

    Cited by:

    1. Nicholas J. Horton, 2015. "Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward," The American Statistician, Taylor & Francis Journals, vol. 69(2), pages 138-145, May.

  8. C. J. Wild & M. Pfannkuch & M. Regan & N. J. Horton, 2011. "Towards more accessible conceptions of statistical inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(2), pages 247-295, April.

    Cited by:

    1. Chris J. Wild & Maxine Pfannkuch & Matt Regan & Ross Parsonage, 2017. "Accessible Conceptions of Statistical Inference: Pulling Ourselves Up by the Bootstraps," International Statistical Review, International Statistical Institute, vol. 85(1), pages 84-107, April.
    2. Jim Ridgway, 2016. "Implications of the Data Revolution for Statistics Education," International Statistical Review, International Statistical Institute, vol. 84(3), pages 528-549, December.
    3. Xie, Yihui, 2013. "animation: An R Package for Creating Animations and Demonstrating Statistical Methods," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 53(i01).

  9. Nicholas J. Horton, 2008. "Review of Multilevel and Longitudinal Modeling Using Stata, Second Edition, by Sophia Rabe-Hesketh and Anders Skrondal," Stata Journal, StataCorp LP, vol. 8(4), pages 579-582, December.

    Cited by:

    1. Nicholas J. Horton, 2011. "Stata tip 95: Estimation of error covariances in a linear model," Stata Journal, StataCorp LP, vol. 11(1), pages 145-148, March.

  10. Horton, Nicholas J. & Kleinman, Ken P., 2007. "Much Ado About Nothing: A Comparison of Missing Data Methods and Software to Fit Incomplete Data Regression Models," The American Statistician, American Statistical Association, vol. 61, pages 79-90, February.

    Cited by:

    1. R Florez-Lopez, 2010. "Effects of missing data in credit risk scoring. A comparative analysis of methods to achieve robustness in the absence of sufficient data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 486-501, March.
    2. Celeste Combrinck & Vanessa Scherman & David Maree & Sarah Howie, 2018. "Multiple Imputation for Dichotomous MNAR Items Using Recursive Structural Equation Modeling With Rasch Measures as Predictors," SAGE Open, , vol. 8(1), pages 21582440187, February.
    3. Labohm, Katharina & Baaken, Dominik & Hess, Sebastian, 2021. "Mikromarktstrukturen der Rohmilchautomaten in Deutschland," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317053, German Association of Agricultural Economists (GEWISOLA).
    4. Jushan Bai & Serena Ng, 2021. "Matrix Completion, Counterfactuals, and Factor Analysis of Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(536), pages 1746-1763, October.
    5. Zachary D Rethorn & Alessandra N Garcia & Chad E Cook & Oren N Gottfried, 2020. "Quantifying the collective influence of social determinants of health using conditional and cluster modeling," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-18, November.
    6. Louis Anthony (Tony) Cox, Jr & Douglas A. Popken, 2008. "Overcoming Confirmation Bias in Causal Attribution: A Case Study of Antibiotic Resistance Risks," Risk Analysis, John Wiley & Sons, vol. 28(5), pages 1155-1172, October.
    7. David (David Patrick) Madden, 2012. "The relationship between low birthweight and socioeconomic status in Ireland," Working Papers 201214, School of Economics, University College Dublin.
    8. Cain Polidano & Ha Vu, 2012. "Labour market impacts from disability onset," ANU Working Papers in Economics and Econometrics 2012-583, Australian National University, College of Business and Economics, School of Economics.
    9. Gedikoglu, Haluk & Parcell, Joseph L., 2013. "Implications of Survey Sampling Design for Missing Data Imputation," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149679, Agricultural and Applied Economics Association.
    10. Hapfelmeier, A. & Ulm, K., 2014. "Variable selection by Random Forests using data with missing values," Computational Statistics & Data Analysis, Elsevier, vol. 80(C), pages 129-139.
    11. Margaret L McNairy & Deanna Jannat-Khah & Jean W Pape & Adias Marcelin & Patrice Joseph & Jean Edward Mathon & Serena Koenig & Martin Wells & Daniel W Fitzgerald & Arthur Evans, 2018. "Predicting death and lost to follow-up among adults initiating antiretroviral therapy in resource-limited settings: Derivation and external validation of a risk score in Haiti," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-16, August.
    12. Valentino Dardanoni & Salvatore Modica & Franco Peracchi, 2011. "Regression with imputed covariates: A generalized missing-indicator approach," Post-Print hal-00815561, HAL.
    13. Castellacci, Fulvio & Natera, Jose Miguel, 2011. "A new panel dataset for cross-country analyses of national systems, growth and development (CANA)," MPRA Paper 28376, University Library of Munich, Germany.
    14. Kristian Kleinke & Mark Stemmler & Jost Reinecke & Friedrich Lösel, 2011. "Efficient ways to impute incomplete panel data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 351-373, December.
    15. Yi-Sheng Chao & Hsing-Chien Wu & Chao-Jung Wu & Wei-Chih Chen, 2018. "Index or illusion: The case of frailty indices in the Health and Retirement Study," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-19, July.
    16. McDonough, Ian K. & Millimet, Daniel L., 2017. "Missing data, imputation, and endogeneity," Journal of Econometrics, Elsevier, vol. 199(2), pages 141-155.
    17. Brady T. West & Patricia Berglund & Steven G. Heeringa, 2008. "A closer examination of subpopulation analysis of complex-sample survey data," Stata Journal, StataCorp LP, vol. 8(4), pages 520-531, December.
    18. Rachel Griffith & Rodrigo Lluberas & Melanie Lührmann, 2016. "Gluttony And Sloth? Calories, Labor Market Activity And The Rise Of Obesity," Journal of the European Economic Association, European Economic Association, vol. 14(6), pages 1253-1286, December.
    19. Werber Borut & Baggia Alenka & Žnidaršič Anja, 2018. "Factors Affecting the Intentions to Use RFID Subcutaneous Microchip Implants for Healthcare Purposes," Organizacija, Sciendo, vol. 51(2), pages 121-133, May.
    20. Simon Trimborn & Wolfgang Karl Härdle, 2015. "CRIX or evaluating Blockchain based currencies," SFB 649 Discussion Papers SFB649DP2015-048, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    21. Trimborn, Simon & Härdle, Wolfgang Karl, 2018. "CRIX an Index for cryptocurrencies," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 107-122.
    22. Zhong, Hua & Hu, Wuyang, 2015. "Farmers’ Willingness to Engage in Best Management Practices: an Application of Multiple Imputation," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196962, Southern Agricultural Economics Association.
    23. Lena Walther & Lukas M. Fuchs & Jürgen Schupp & Christian von Scheve, 2019. "Living Conditions and the Mental Health and Well-being of Refugees: Evidence from a Representative German Panel Study," SOEPpapers on Multidisciplinary Panel Data Research 1029, DIW Berlin, The German Socio-Economic Panel (SOEP).
    24. Adriano Zanin Zambom & Gregory J. Matthews, 2021. "Sure independence screening in the presence of missing data," Statistical Papers, Springer, vol. 62(2), pages 817-845, April.
    25. Göran Kauermann & Mehboob Ali, 2021. "Semi-parametric regression when some (expensive) covariates are missing by design," Statistical Papers, Springer, vol. 62(4), pages 1675-1696, August.
    26. Valentino Dardanoni & Giuseppe De Luca & Salvatore Modica & Franco Peracchi, 2011. "A Generalized Missing-Indicator Approach to Regression with Imputed Covariates," EIEF Working Papers Series 1111, Einaudi Institute for Economics and Finance (EIEF), revised May 2011.
    27. Audronė Telešienė & Jelle Boeve-de Pauw & Daphne Goldman & Ralph Hansmann, 2021. "Evaluating an Educational Intervention Designed to Foster Environmental Citizenship among Undergraduate University Students," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
    28. Hapfelmeier, A. & Hothorn, T. & Ulm, K., 2012. "Recursive partitioning on incomplete data using surrogate decisions and multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1552-1565.
    29. Siddique, Juned & Harel, Ofer, 2009. "MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i09).
    30. Ke-Hai Yuan & Fan Yang-Wallentin & Peter M. Bentler, 2012. "ML Versus MI for Missing Data With Violation of Distribution Conditions," Sociological Methods & Research, , vol. 41(4), pages 598-629, November.
    31. Consentino, Fabrizio & Claeskens, Gerda, 2010. "Order selection tests with multiply imputed data," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2284-2295, October.
    32. Schomaker, Michael & Heumann, Christian, 2014. "Model selection and model averaging after multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 758-770.
    33. Ruiwen Zhou & Huiqiong Li & Jianguo Sun & Niansheng Tang, 2022. "A new approach to estimation of the proportional hazards model based on interval-censored data with missing covariates," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 28(3), pages 335-355, July.
    34. Präg, Patrick, 2018. "Nonresponse to Items on Self-Reported Delinquency. A Review and Evaluation of Missing Data Techniques," SocArXiv y9sv7, Center for Open Science.
    35. James Honaker & Gary King, 2010. "What to Do about Missing Values in Time‐Series Cross‐Section Data," American Journal of Political Science, John Wiley & Sons, vol. 54(2), pages 561-581, April.
    36. Lê, Félice & Diez Roux, Ana & Morgenstern, Hal, 2013. "Effects of child and adolescent health on educational progress," Social Science & Medicine, Elsevier, vol. 76(C), pages 57-66.
    37. Kontopantelis, Evangelos & Springate, David A & Parisi, Rosa & Reeves, David, 2016. "Simulation-Based Power Calculations for Mixed Effects Modeling: ipdpower in Stata," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i12).
    38. Fitzpatrick, Trevor & Mues, Christophe, 2016. "An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market," European Journal of Operational Research, Elsevier, vol. 249(2), pages 427-439.

  11. Cozier, Y.C. & Palmer, J.R. & Horton, N.J. & Fredman, L. & Wise, L.A. & Rosenberg, L., 2007. "Relation between neighborhood median housing value and hypertension risk among black women in the United States," American Journal of Public Health, American Public Health Association, vol. 97(4), pages 718-724.

    Cited by:

    1. Anh D. Ngo & Catherine Paquet & Natasha J. Howard & Neil T. Coffee & Anne W. Taylor & Robert J. Adams & Mark Daniel, 2014. "Area-Level Socioeconomic Characteristics, Prevalence and Trajectories of Cardiometabolic Risk," IJERPH, MDPI, vol. 11(1), pages 1-19, January.
    2. Lisa A. Matricciani & Catherine Paquet & Natasha J. Howard & Robert Adams & Neil T. Coffee & Anne W. Taylor & Mark Daniel, 2013. "Investigating Individual- and Area-Level Socioeconomic Gradients of Pulse Pressure among Normotensive and Hypertensive Participants," IJERPH, MDPI, vol. 10(2), pages 1-19, February.
    3. Arline T. Geronimus & John Bound & Annie Ro, 2014. "Residential Mobility Across Local Areas In The United States And The Geographic Distribution Of The Healthy Population," Working Papers 14-14, Center for Economic Studies, U.S. Census Bureau.
    4. Harrington, Daniel W. & Elliott, Susan J., 2009. "Weighing the importance of neighbourhood: A multilevel exploration of the determinants of overweight and obesity," Social Science & Medicine, Elsevier, vol. 68(4), pages 593-600, February.
    5. Bécares, Laia & Nazroo, James & Jackson, James & Heuvelman, Hein, 2012. "Ethnic density effects on health and experienced racism among Caribbean people in the US and England: A cross-national comparison," Social Science & Medicine, Elsevier, vol. 75(12), pages 2107-2115.

  12. Horton, Nicholas J., 2006. "Multilevel and Longitudinal Modeling Using Stata. Sophia Rabe-Hesketh and Anders Skrondal," The American Statistician, American Statistical Association, vol. 60, pages 293-294, August.

    Cited by:

    1. Xiaoming Lin & Ruodan Lu & Liang Guo & Bing Liu, 2019. "Social Capital and Mental Health in Rural and Urban China: A Composite Hypothesis Approach," IJERPH, MDPI, vol. 16(4), pages 1-16, February.

  13. Horton, Nicholas J. & Brown, Elizabeth R. & Qian, Linjuan, 2004. "Use of R as a Toolbox for Mathematical Statistics Exploration," The American Statistician, American Statistical Association, vol. 58, pages 343-357, November.

    Cited by:

    1. Nicholas J. Horton, 2015. "Challenges and Opportunities for Statistics and Statistical Education: Looking Back, Looking Forward," The American Statistician, Taylor & Francis Journals, vol. 69(2), pages 138-145, May.

  14. Horton N.J. & Lipsitz S.R. & Parzen M., 2003. "A Potential for Bias When Rounding in Multiple Imputation," The American Statistician, American Statistical Association, vol. 57, pages 229-232, November.

    Cited by:

    1. Yeh Jason Jia-Hsing, 2009. "Missing (Completely?) At Random: Lessons from Insurance Studies," Asia-Pacific Journal of Risk and Insurance, De Gruyter, vol. 3(2), pages 1-13, April.
    2. R Florez-Lopez, 2010. "Effects of missing data in credit risk scoring. A comparative analysis of methods to achieve robustness in the absence of sufficient data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 486-501, March.
    3. Celeste Combrinck & Vanessa Scherman & David Maree & Sarah Howie, 2018. "Multiple Imputation for Dichotomous MNAR Items Using Recursive Structural Equation Modeling With Rasch Measures as Predictors," SAGE Open, , vol. 8(1), pages 21582440187, February.
    4. Paul T. von Hippel, 2013. "Should a Normal Imputation Model be Modified to Impute Skewed Variables?," Sociological Methods & Research, , vol. 42(1), pages 105-138, February.
    5. Lahiri, Kajal & Pulungan, Zulkarnain, 2007. "Income-related health disparity and its determinants in New York state: racial/ethnic and geographical comparisons," MPRA Paper 21694, University Library of Munich, Germany.
    6. Kajal Lahiri & Zulkarnain Pulungan, 2006. "Health Inequality and Its Determinants in New York," Discussion Papers 06-03, University at Albany, SUNY, Department of Economics.
    7. Matthew Desmond & Tracey Shollenberger, 2015. "Forced Displacement From Rental Housing: Prevalence and Neighborhood Consequences," Demography, Springer;Population Association of America (PAA), vol. 52(5), pages 1751-1772, October.
    8. Carsten Kuchler & Martin Spiess, 2009. "The data quality concept of accuracy in the context of publicly shared data sets," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 3(1), pages 67-80, June.
    9. Razzak Humera & Heumann Christian, 2019. "Hybrid Multiple Imputation In A Large Scale Complex Survey," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 33-58, December.
    10. Darrick Yee & Andrew Ho, 2015. "Discreteness Causes Bias in Percentage-Based Comparisons: A Case Study From Educational Testing," The American Statistician, Taylor & Francis Journals, vol. 69(3), pages 174-181, August.
    11. Yajuan Si & Jerome P. Reiter, 2013. "Nonparametric Bayesian Multiple Imputation for Incomplete Categorical Variables in Large-Scale Assessment Surveys," Journal of Educational and Behavioral Statistics, , vol. 38(5), pages 499-521, October.
    12. Kristian Kleinke & Jost Reinecke & Cornelia Weins, 2021. "The development of delinquency during adolescence: a comparison of missing data techniques revisited," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(3), pages 877-895, June.
    13. Davide Vidotto & Jeroen K. Vermunt & Katrijn van Deun, 2018. "Bayesian Multilevel Latent Class Models for the Multiple Imputation of Nested Categorical Data," Journal of Educational and Behavioral Statistics, , vol. 43(5), pages 511-539, October.
    14. Xu, Wan & Khachatryan, Hayk, 2014. "Multiple Imputation in the Complex National Nursery Survey Data by Fully Conditional Specification," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170208, Agricultural and Applied Economics Association.
    15. Yan Xia & Yanyun Yang, 2016. "Bias Introduced by Rounding in Multiple Imputation for Ordered Categorical Variables," The American Statistician, Taylor & Francis Journals, vol. 70(4), pages 358-364, October.
    16. Stuart R. Lipsitz & Garrett M. Fitzmaurice & Roger D. Weiss, 2020. "Using Multiple Imputation with GEE with Non-monotone Missing Longitudinal Binary Outcomes," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 890-904, December.
    17. Danielle X. Morales & Sara E. Grineski & Timothy W. Collins, 2017. "Faculty Motivation to Mentor Students Through Undergraduate Research Programs: A Study of Enabling and Constraining Factors," Research in Higher Education, Springer;Association for Institutional Research, vol. 58(5), pages 520-544, August.
    18. Chae, David H. & Lincoln, Karen D. & Adler, Nancy E. & Syme, S. Leonard, 2010. "Do experiences of racial discrimination predict cardiovascular disease among African American men? The moderating role of internalized negative racial group attitudes," Social Science & Medicine, Elsevier, vol. 71(6), pages 1182-1188, September.

  15. Nicholas J. Horton & Garrett M. Fitzmaurice, 2002. "Maximum likelihood estimation of bivariate logistic models for incomplete responses with indicators of ignorable and non‐ignorable missingness," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(3), pages 281-295, July.

    Cited by:

    1. David Draper & Mark Gittoes, 2004. "Statistical analysis of performance indicators in UK higher education," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 167(3), pages 449-474, August.

  16. Nicholas J. Horton & Nan M. Laird, 2001. "Maximum Likelihood Analysis of Logistic Regression Models with Incomplete Covariate Data and Auxiliary Information," Biometrics, The International Biometric Society, vol. 57(1), pages 34-42, March.

    Cited by:

    1. Sinha, Sanjoy K. & Laird, Nan M. & Fitzmaurice, Garrett M., 2010. "Multivariate logistic regression with incomplete covariate and auxiliary information," Journal of Multivariate Analysis, Elsevier, vol. 101(10), pages 2389-2397, November.
    2. Liu, Li & Xiang, Liming, 2019. "Missing covariate data in generalized linear mixed models with distribution-free random effects," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 1-16.

  17. Joseph G. Ibrahim & Stuart R. Lipsitz & Nick Horton, 2001. "Using auxiliary data for parameter estimation with non‐ignorably missing outcomes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 50(3), pages 361-373.

    Cited by:

    1. Lei Wang & Wei Ma, 2021. "Improved empirical likelihood inference and variable selection for generalized linear models with longitudinal nonignorable dropouts," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 623-647, June.
    2. Liang, Hua, 2008. "Generalized partially linear models with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 880-895, May.
    3. Wang Miao & Eric J. Tchetgen Tchetgen, 2016. "On varieties of doubly robust estimators under missingness not at random with a shadow variable," Biometrika, Biometrika Trust, vol. 103(2), pages 475-482.
    4. Liang, Hua & Su, Haiyan & Zou, Guohua, 2008. "Confidence intervals for a common mean with missing data with applications in an AIDS study," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 546-553, December.
    5. Yoshiharu Takagi & Yutaka Kano, 2019. "Bias reduction using surrogate endpoints as auxiliary variables," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(4), pages 837-852, August.
    6. Bindele, Huybrechts F. & Nguelifack, Brice M., 2019. "Generalized signed-rank estimation for regression models with non-ignorable missing responses," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 14-33.
    7. Dan Jackson & Ian R. White & Morven Leese, 2010. "How much can we learn about missing data?: an exploration of a clinical trial in psychiatry," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(3), pages 593-612, July.
    8. Baojiang Chen & Xiao-Hua Zhou, 2011. "Doubly Robust Estimates for Binary Longitudinal Data Analysis with Missing Response and Missing Covariates," Biometrics, The International Biometric Society, vol. 67(3), pages 830-842, September.
    9. Shonosuke Sugasawa & Kosuke Morikawa & Keisuke Takahata, 2022. "Bayesian semiparametric modeling of response mechanism for nonignorable missing data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(1), pages 101-117, March.

  18. Horton N. J. & Lipsitz S. R., 2001. "Multiple Imputation in Practice: Comparison of Software Packages for Regression Models With Missing Variables," The American Statistician, American Statistical Association, vol. 55, pages 244-254, August.

    Cited by:

    1. Hildegard Seidl & Matthias Hunger & Reiner Leidl & Christa Meisinger & Rupert Wende & Bernhard Kuch & Rolf Holle, 2015. "Cost-effectiveness of nurse-based case management versus usual care for elderly patients with myocardial infarction: results from the KORINNA study," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(6), pages 671-681, July.
    2. Ronald B. Mincy & Elia De la Cruz Toledo, 2014. "Unemployment and Child Support Compliance Through the Great Recession," Working Papers 14-01-ff, Princeton University, School of Public and International Affairs, Center for Research on Child Wellbeing..
    3. Patrick Royston & John B. Carlin & Ian R. White, 2009. "Multiple imputation of missing values: New features for mim," Stata Journal, StataCorp LP, vol. 9(2), pages 252-264, June.
    4. Christian Seiler, 2013. "Nonresponse in Business Tendency Surveys: Theoretical Discourse and Empirical Evidence," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 52.
    5. Giorgio Calzolari & Laura Neri, 2010. "The Method of Simulated Scores for Estimating Multinormal Regression Models with Missing Values," Econometrics Working Papers Archive wp2010_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    6. Paredes-Gazquez, Juan Diego & Rodriguez-Fernandez, José Miguel & de la Cuesta-Gonzalez, Marta, 2016. "Measuring corporate social responsibility using composite indices: Mission impossible? The case of the electricity utility industry," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 19(1), pages 142-153.
    7. Hua Yun Chen & Hui Xie & Yi Qian, 2011. "Multiple Imputation for Missing Values through Conditional Semiparametric Odds Ratio Models," Biometrics, The International Biometric Society, vol. 67(3), pages 799-809, September.
    8. Youngwon Nam & Cäzilia Loibl, 2021. "Financial Capability and Financial Planning at the Verge of Retirement Age," Journal of Family and Economic Issues, Springer, vol. 42(1), pages 133-150, March.
    9. Grimalda, Gianluca & Farina, Francesco & Conte, Anna & Schmidt, Ulrich, 2023. "Why do preferences for redistribution differ across countries? An experimental analysis," Kiel Working Papers 2230, Kiel Institute for the World Economy (IfW Kiel), revised 2023.
    10. Ahmad R. Alsaber & Jiazhu Pan & Adeeba Al-Hurban, 2021. "Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018)," IJERPH, MDPI, vol. 18(3), pages 1-25, February.
    11. Andrew Briggs & Taane Clark & Jane Wolstenholme & Philip Clarke, 2003. "Missing.... presumed at random: cost‐analysis of incomplete data," Health Economics, John Wiley & Sons, Ltd., vol. 12(5), pages 377-392, May.
    12. Susanne Rässler & Regina Riphahn, 2006. "Survey item nonresponse and its treatment," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 217-232, March.
    13. Kristian Kleinke & Mark Stemmler & Jost Reinecke & Friedrich Lösel, 2011. "Efficient ways to impute incomplete panel data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 351-373, December.
    14. Chaurasia, Ashok, 2023. "Combining rules for F- and Beta-statistics from multiply-imputed data," Econometrics and Statistics, Elsevier, vol. 25(C), pages 51-65.
    15. Geronimi, J. & Saporta, G., 2017. "Variable selection for multiply-imputed data with penalized generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 103-114.
    16. Ben F M Wijnen & Karin Pos & Eva Velthorst & Frederike Schirmbeck & Hoi Yau Chan & Lieuwe de Haan & Mark van der Gaag & Silvia M A A Evers & Filip Smit, 2018. "Economic evaluation of brief cognitive behavioural therapy for social activation in recent-onset psychosis," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-16, November.
    17. Hamid Heidarian Miri & Jafar Hassanzadeh & Abdolreza Rajaeefard & Majid Mirmohammadkhani & Kambiz Ahmadi Angali, 2016. "Multiple Imputation to Correct for Nonresponse Bias: Application in Non-communicable Disease Risk Factors Survey," Global Journal of Health Science, Canadian Center of Science and Education, vol. 8(1), pages 133-133, January.
    18. Yijie Zhou & Francesca Dominici & Thomas A. Louis, 2010. "Racial disparities in risks of mortality in a sample of the US Medicare population," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(2), pages 319-339, March.
    19. Joyance Meechai & Manel Wijesinha, 2022. "Household energy expenditure and consumption patterns in the United States," Computational Statistics, Springer, vol. 37(5), pages 2095-2127, November.
    20. Robert Rieg, 2019. "Selbstständigkeit von Bilanzbuchhaltern und Controllern: Eine empirische Untersuchung zu Einkommen und Determinanten," ZfKE – Zeitschrift für KMU und Entrepreneurship, Duncker & Humblot, Berlin, vol. 67(1), pages 35-66.
    21. Nengsih Titin Agustin & Bertrand Frédéric & Maumy-Bertrand Myriam & Meyer Nicolas, 2019. "Determining the number of components in PLS regression on incomplete data set," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 18(6), pages 1-28, December.
    22. Jing Dai & Stefan Sperlich & Walter Zucchini, 2016. "A Simple Method for Predicting Distributions by Means of Covariates with Examples from Poverty and Health Economics," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 152(I), pages 49-80, March.
    23. Eneko Echaniz & Chinh Ho & Andres Rodriguez & Luigi dell’Olio, 2020. "Modelling user satisfaction in public transport systems considering missing information," Transportation, Springer, vol. 47(6), pages 2903-2921, December.
    24. Jing Dai & Stefan Sperlich & Walter Zucchini, 2011. "Estimating and Predicting Household Expenditures and Income Distributions," MAGKS Papers on Economics 201147, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    25. Młodak Andrzej, 2021. "An application of a complex measure to model–based imputation in business statistics," Statistics in Transition New Series, Polish Statistical Association, vol. 22(1), pages 1-28, March.
    26. Sarah Mustillo, 2012. "The Effects of Auxiliary Variables on Coefficient Bias and Efficiency in Multiple Imputation," Sociological Methods & Research, , vol. 41(2), pages 335-361, May.
    27. Paul Zhang, 2005. "Multiple imputation of missing data with ante-dependence covariance structure," Journal of Applied Statistics, Taylor & Francis Journals, vol. 32(2), pages 141-155.
    28. Janet MacNeil Vroomen & Iris Eekhout & Marcel G. Dijkgraaf & Hein van Hout & Sophia E. de Rooij & Martijn W. Heymans & Judith E. Bosmans, 2016. "Multiple imputation strategies for zero-inflated cost data in economic evaluations: which method works best?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 939-950, November.
    29. Víctor Amor-Esteban & Mª-Purificación Galindo-Villardón & Isabel-María García-Sánchez, 2019. "A Multivariate Proposal for a National Corporate Social Responsibility Practices Index (NCSRPI) for International Settings," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(2), pages 525-560, June.
    30. Ulrich Rendtel, 2006. "The 2005 Plenary Meeting on ‘‘Missing Data and Measurement Error’’," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(4), pages 493-499, December.
    31. Gabriele Beissel Durrant, 2009. "Imputation Methods for Handling Item-Nonresponse in the Social Sciences: A Methodological Review," Working Papers id:2007, eSocialSciences.
    32. David K. Blough & Scott Ramsey & Sean D. Sullivan & Roger Yusen, 2009. "The impact of using different imputation methods for missing quality of life scores on the estimation of the cost‐effectiveness of lung‐volume‐reduction surgery," Health Economics, John Wiley & Sons, Ltd., vol. 18(1), pages 91-101, January.
    33. Li, Daniel H. & Wang, Liqun, 2016. "A weighted simulation-based estimator for incomplete longitudinal data models," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 16-22.
    34. Dardas, Anastassios Z. & Williams, Allison & Scott, Darren, 2020. "Carer-employees’ travel behaviour: Assisted-transport in time and space," Journal of Transport Geography, Elsevier, vol. 82(C).
    35. Adnan Efendic & Tomasz Marek Mickiewicz & Anna Rebmann, 2013. "Growth Aspirations and Social Capital: Young Firms in a Post-Conflict Environment," UCL SSEES Economics and Business working paper series 122, UCL School of Slavonic and East European Studies (SSEES).
    36. Stuart R. Lipsitz & Garrett M. Fitzmaurice & Roger D. Weiss, 2020. "Using Multiple Imputation with GEE with Non-monotone Missing Longitudinal Binary Outcomes," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 890-904, December.
    37. Kristian Kleinke & Jost Reinecke, 2013. "Multiple imputation of incomplete zero-inflated count data," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 67(3), pages 311-336, August.
    38. Atanu Bhattacharjee, 2020. "Estimation of Treatment Effect with Missing Observations for Three Arms and Three Periods Crossover Clinical Trials," Annals of Data Science, Springer, vol. 7(3), pages 447-460, September.
    39. Opoku-Agyemang, Kweku A., 2017. "A Human-Computer Interaction Approach for Integrity in Economics," SocArXiv ra3cs, Center for Open Science.
    40. Consentino, Fabrizio & Claeskens, Gerda, 2010. "Order selection tests with multiply imputed data," Computational Statistics & Data Analysis, Elsevier, vol. 54(10), pages 2284-2295, October.
    41. Aderiana Mutheu Mbandi & Jan R. Böhnke & Dietrich Schwela & Harry Vallack & Mike R. Ashmore & Lisa Emberson, 2019. "Estimating On-Road Vehicle Fuel Economy in Africa: A Case Study Based on an Urban Transport Survey in Nairobi, Kenya," Energies, MDPI, vol. 12(6), pages 1-28, March.
    42. Shu Yang & Jae Kwang Kim, 2020. "Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 839-861, September.
    43. Ringle, Jay L. & Huefner, Jonathan C. & James, Sigrid & Pick, Robert & Thompson, Ronald W., 2012. "12-month follow-up outcomes for youth departing an integrated residential continuum of care," Children and Youth Services Review, Elsevier, vol. 34(4), pages 675-679.
    44. Landau, E.R. & Raniti, M.B. & Blake, M. & Waloszek, J.M. & Blake, L. & Simmons, J.G. & Schwartz, O. & Murray, G. & Trinder, J. & Allen, N.B. & Byrne, M.L., 2021. "The ratio of morning cortisol to CRP prospectively predicts first-onset depression in at-risk adolescents," Social Science & Medicine, Elsevier, vol. 281(C).

Chapters

  1. J. M. Henle & N. J. Horton & S. J. Jakus, 2008. "Modelling Inequality with a Single Parameter," Economic Studies in Inequality, Social Exclusion, and Well-Being, in: Duangkamon Chotikapanich (ed.), Modeling Income Distributions and Lorenz Curves, chapter 14, pages 255-269, Springer.

    Cited by:

    1. A. Il’inskii I. & Z. Mierzwa & А. Ильинский И. & З. Межва, 2019. "Распределение богатства в экосистеме биткоин // Wealth Distribution in the Bitcoin Ecosystem," Финансы: теория и практика/Finance: Theory and Practice // Finance: Theory and Practice, ФГОБУВО Финансовый университет при Правительстве Российской Федерации // Financial University under The Government of Russian Federation, vol. 23(2), pages 6-16.

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