Big Data for Finite Population Inference: Applying Quasi-Random Approaches to Naturalistic Driving Data Using Bayesian Additive Regression Trees
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[1] Til Stürmer,et al. The role of the c‐statistic in variable selection for propensity score models , 2011, Pharmacoepidemiology and drug safety.
[2] Jennifer Hill,et al. Assessing Methods for Generalizing Experimental Impact Estimates to Target Populations , 2016, Journal of research on educational effectiveness.
[3] Tom W. Smith,et al. Big Data and Survey Research: Supplement or Substitute? , 2017 .
[4] Xiao-Li Meng,et al. Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election , 2018, The Annals of Applied Statistics.
[5] K Jung,et al. Comparing methods for estimation of heterogeneous treatment effects using observational data from health care databases , 2018, Statistics in medicine.
[6] Elizabeth A. Stuart,et al. Measuring model misspecification: Application to propensity score methods with complex survey data , 2018, Comput. Stat. Data Anal..
[7] Roderick J. A. Little,et al. Projecting From Advance Data Using Propensity Modeling: An Application to Income and Tax Statistics , 1992 .
[8] Michael R Elliott,et al. Appropriate analysis of CIREN data: using NASS-CDS to reduce bias in estimation of injury risk factors in passenger vehicle crashes. , 2010, Accident; analysis and prevention.
[9] Bruce D. Meyer,et al. Household Surveys in Crisis , 2015 .
[10] Isabel Molina,et al. Small Area Estimation: Rao/Small Area Estimation , 2005 .
[11] Richard Valliant,et al. Estimating Propensity Adjustments for Volunteer Web Surveys , 2011 .
[12] Wei-Yin Loh,et al. Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..
[13] Carol A C Flannagan,et al. Development of a real-time prediction model of driver behavior at intersections using kinematic time series data. , 2017, Accident; analysis and prevention.
[14] Sunghee Lee,et al. Estimation for Volunteer Panel Web Surveys Using Propensity Score Adjustment and Calibration Adjustment , 2009 .
[15] S. Ferrari,et al. Beta Regression for Modelling Rates and Proportions , 2004 .
[16] D. Binder. On the variances of asymptotically normal estimators from complex surveys , 1983 .
[17] D. Horvitz,et al. A Generalization of Sampling Without Replacement from a Finite Universe , 1952 .
[18] J. Neyman. On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and the Method of Purposive Selection , 1934 .
[19] E. Hargittai. Is Bigger Always Better? Potential Biases of Big Data Derived from Social Network Sites , 2015 .
[20] M. Couper. Is the sky falling? new technology, changing media, and the future of surveys , 2013 .
[21] Sharon L. Lohr,et al. Combining Survey Data with Other Data Sources , 2017 .
[22] Siva R K Narla,et al. The Evolution of Connected Vehicle Technology: From Smart Drivers to Smart Cars to....Self-Driving Cars. , 2013 .
[23] R. Little,et al. Model-Based Alternatives to Trimming Survey Weights , 2000 .
[24] Roger Tourangeau,et al. Summary Report of the AAPOR Task Force on Non-probability Sampling , 2013 .
[25] D. Rubin,et al. The central role of the propensity score in observational studies for causal effects , 1983 .
[26] H. Chipman,et al. BART: Bayesian Additive Regression Trees , 2008, 0806.3286.
[27] Danna L. Moore,et al. Characteristics of Cell Phone Only, Listed, and Unlisted Telephone Households , 2009 .
[28] Michael R. Elliott,et al. Obtaining cancer risk factor prevalence estimates in small areas: combining data from two surveys , 2005 .
[29] Mingnan Liu,et al. Effect of a pre-paid incentive on response rates to an Address-Based Sampling (ABS) Web-Mail survey , 2016 .
[30] James R. Gattiker,et al. Parallel Bayesian Additive Regression Trees , 2013, 1309.1906.
[31] Carl-Erik Särndal,et al. Model Assisted Survey Sampling , 1997 .
[32] Christopher Weiss,et al. Challenges With Propensity Score Strategies in a High-Dimensional Setting and a Potential Alternative , 2011, Multivariate behavioral research.
[33] Sharon-Lise T Normand,et al. Bayesian propensity scores for high‐dimensional causal inference: A comparison of drug‐eluting to bare‐metal coronary stents , 2017, Biometrical journal. Biometrische Zeitschrift.
[34] Henrik Toft Sørensen,et al. Comment on "Perils and potentials of self-selected entry to epidemiological studies and surveys" , 2016 .
[35] W. Fuller,et al. Sample survey theory and methods: Past, present, and future directions , 2017 .
[36] Roderick J. A. Little,et al. Approaches to Improving Survey-Weighted Estimates , 2017 .
[37] P. Squire,et al. WHY THE 1936 LITERARY DIGEST POLL FAILED , 1988 .
[38] Daniel Almirall,et al. Chasing Balance and Other Recommendations for Improving Nonparametric Propensity Score Models , 2017, Journal of causal inference.
[39] Michael R. Elliott,et al. Combining Data from Probability and Non- Probability Samples Using Pseudo-Weights , 2009 .
[40] R. Groves. Three Eras of Survey Research , 2011 .
[41] R. Valliant,et al. General Regression Estimation Adjusted for Undercoverage and Estimated Control Totals , 2016 .
[42] Edward I. George,et al. Bayesian Ensemble Learning , 2006, NIPS.
[43] S. M. Tam,et al. Big Data, Official Statistics and Some Initiatives by the Australian Bureau of Statistics , 2015 .
[44] Elizabeth A. Stuart,et al. Theory and practice in non-probability surveys : parallels between causal inference and survey inference , 2017 .
[45] R. Little,et al. Does Weighting for Nonresponse Increase the Variance of Survey Means? (Conference Paper) , 2004 .
[46] Michael R. Elliott,et al. Inference for Nonprobability Samples , 2017 .
[47] Piyushimita Thakuriah,et al. Seeing Cities Through Big Data: Research, Methods and Applications in Urban Informatics , 2016 .
[48] Richard Valliant,et al. Internet Surveys: Can Statistical Adjustments Eliminate Coverage Bias? , 2008 .
[49] T. Louis,et al. Web-Based Enrollment and Other Types of Self-Selection in Surveys and Studies: Consequences for Generalizability , 2018 .
[50] D. Rubin. Multiple imputation for nonresponse in surveys , 1989 .
[51] Trent D. Buskirk,et al. Apples to Oranges or Gala versus Golden Delicious?Comparing Data Quality of Nonprobability Internet Samples to Low Response Rate Probability Samples , 2017 .
[52] Sunghee Lee. Propensity score adjustment as a weighting scheme for volunteer panel web surveys , 2006 .
[53] Paul J. Lavrakas,et al. Trends in Telephone Outcomes, 2008 - 2015 , 2016 .
[54] Piet Daas,et al. Selectivity of Big data , 2014 .
[55] Elizabeth A Stuart,et al. Generalizability of Randomized Trial Results to Target Populations , 2018, Research on social work practice.
[56] J. Rao. Small Area Estimation , 2003 .
[57] Kevin L. McKinney,et al. Earnings Inequality and Mobility Trends in the United States: Nationally Representative Estimates from Longitudinally Linked Employer-Employee Data , 2017, Journal of Labor Economics.
[58] C. Owsley,et al. Distracted Driving and Risk of Crash or Near-Crash Involvement Among Older Drivers Using Naturalistic Driving Data With a Case-Crossover Study Design , 2019, The journals of gerontology. Series A, Biological sciences and medical sciences.
[59] Thomas A. Louis,et al. Perils and potentials of self‐selected entry to epidemiological studies and surveys , 2016 .