A5043964505- Survey Methodology and Nonresponse
- Survey Sampling and Estimation Techniques
- Statistical Methods and Bayesian Inference
- Census and Population Estimation
- Data-Driven Disease Surveillance
- Urban, Neighborhood, and Segregation Studies
- Healthcare Policy and Management
- Advanced Statistical Methods and Models
- Statistical Methods and Inference
- Economic and Environmental Valuation
- Technology and Data Analysis
- Data Quality and Management
- Health disparities and outcomes
- Big Data Technologies and Applications
- Bayesian Methods and Mixture Models
- Child Abuse and Trauma
- Fault Detection and Control Systems
- Water Quality and Resources Studies
- Adolescent Sexual and Reproductive Health
- Spatial and Panel Data Analysis
- Electoral Systems and Political Participation
- Scientific Measurement and Uncertainty Evaluation
- Forecasting Techniques and Applications
- Child Welfare and Adoption
- Data Analysis with R
RTI International
2013-2023
University of North Carolina at Chapel Hill
2009-2021
Naval Dockyards Society
1999-2020
Research Triangle Park Foundation
2004
New Mexico State University
1989-1993
United States Census Bureau
1985
Statistical Research (United States)
1985
Preface. Chapter 1. The Evolution of Survey Process Quality. 1.1 Concept a Survey. 1.2 Types Surveys. 1.3 Brief History Methodology. 1.4 Quality Revolution. 1.5 Definitions and in Statistical Organizations. 1.6 Measuring 1.7 Improving 1.8 Nutshell. 2. Data 2.1 Overview the Process. 2.2 Total Error. 2.3 Decomposing Nonsampling Error into Its Component Parts. 2.4 Gauging Magnitude 2.5 Mean Squared 2.6 An Illustration Concepts. 3. Coverage Nonresponse 3.1 3.2 Measures Bias. 3.3 Reducing 3.4...
Partial table of contents: THE QUESTIONNAIRE. The Current Status Questionnaire Design (N. Bradburn & S. Sudman). Context Effects in the General Social Survey (T. Smith). RESPONDENTS AND RESPONSES. Recall Error: Sources and Bias Reduction Techniques (D. Eisenhower, et al.). Toward a Response Model Establishment Surveys (W. Edwards D. Cantor). INTERVIEWERS OTHER MEANS OF DATA COLLECTION. Analysis Reinterview: An Overview (G. Forsman I. Schreiner). Expenditure Diary Their Associated Errors (A....
Partial table of contents: QUESTIONNAIRE DESIGN. From Theoretical Concept to Survey Question (J. Hox). Designing Rating Scales for Effective Measurement in Surveys Krosnick & L. Fabrigar). DATA COLLECTION. Developing a Speech Recognition Application Research (B. Blyth). Children as Respondents: Methods Improving Data Quality Scott). POST SURVEY PROCESSING AND OPERATIONS. Integrated Control Systems Processing Bethlehem). QUALITY ASSESSMENT CONTROL. Continuous Improvement Statistical Agencies...
The total survey error (TSE) paradigm provides a theoretical framework for optimizing surveys by maximizing data quality within budgetary constraints. In this article, the TSE is viewed as part of much larger design strategy that seeks to optimize quality; i.e., more broadly defined include user-specified dimensions quality. Survey methodology, framework, alters our perspectives on design, implementation, and evaluation. As an example, although major objective maximize accuracy subject costs...
Recent years have seen an increase in the amount of statistics describing different phenomena based on “Big Data.” This term includes data characterized not only by their large volume, but also variety and velocity, organic way which they are created, new types processes needed to analyze them make inference from them. The change nature data, availability, collected disseminated is fundamental. constitutes a paradigm shift for survey research. There great potential Big Data, there some...
Abstract While Big Data offers a potentially less expensive, burdensome, and more timely alternative to survey data for producing variety of statistics, it is not without error. The AAPOR Task Force on others have called researchers evaluate the quality using an approach similar total error (TSE) framework. However, differences in construction of, access to, overall structure between make application TSE difficult. In this article, we seek develop Total Error Framework (TEF), extension...
Journal Article Using Geocoded Census Data for Nonresponse Bias Correction: An Assessment Get access Paul Biemer, Biemer * *Address all correspondence to RTI International, P.O. Box 12194, Research Triangle Park, NC 27709, USA; E-mail: ppb@rti.org. Search other works by this author on: Oxford Academic Google Scholar Andy Peytchev of Survey Statistics and Methodology, Volume 1, Issue May 2013, Pages 24–44, https://doi.org/10.1093/jssam/smt003 Published: 01 2013
Summary The paper considers the use of level-of-effort (LOE) paradata to model non-response mechanism in surveys and adjust for bias, particularly bias that is missing not at random or non-ignorable. Our approach based on an unconditional maximum likelihood estimation (call-back) adapts extends prior work handle complexities are encountered large-scale field surveys. A test ‘missingness random’ assumption also proposed can be applied essentially any survey when LOE data available. adjustment...
Journal Article Using Bonus Monetary Incentives to Encourage Web Response in Mixed-Mode Household Surveys Get access Paul P Biemer, Biemer Address correspondence P. RTI International P.O. Box 12194 Research Triangle Park, NC 27709-2194; E-mail: ppb@rti.org. Search for other works by this author on: Oxford Academic Google Scholar Joe Murphy, Murphy Stephanie Zimmer, Zimmer Chip Berry, Berry Grace Deng, Deng Katie Lewis of Survey Statistics and Methodology, Volume 6, Issue 2, June 2018, Pages...
Abstract This article describes a general framework for improving the quality of statistical programs in organizations that provide continual flow products to users and stakeholders. The work stems from 2011 mandate Statistics Sweden issued by Swedish Ministry Finance develop system indicators tracking developments changes product achieving improvements survey across diverse set key products. We describe this system, apply it number at Sweden, summarize results lessons learned. implications...
Summary Latent class analysis (LCA) is a statistical tool for evaluating the error in categorical data when two or more repeated measurements of same survey variable are available. This paper illustrates an application LCA self-reports drug use using from 1994, 1995 and 1996 implementations US National Household Survey on Drug Abuse. In our application, approach used estimating classification errors which turn leads to identifying problems with questionnaire adjusting estimates prevalence...
Abstract Aim To identify factors associated with lower urinary tract symptoms (LUTS) among female elementary school teachers in Taipei. Methods This study is a cross‐sectional, descriptive study. A total of 520 surveys were distributed to 26 schools Logistic regression was used possible related individual LUTS. Results Study results based on the information provided by 445 participants. Of teachers, 293 (65.8%) experienced at least one type Factors incontinence body mass index (BMI), vaginal...