Paul P Biemer
Dados Biográficos
| ID | 281008 |
|---|---|
| NOME | Paul P Biemer |
| PRENOMES | Paul P |
| SOBRENOME | Biemer |
| ASSINATURA | BIEMER P P |
| AFILIAÇÕES | RTI International |
| ORCID | 0000-0003-2214-2707 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 19 |
| TOTAL DE CITAÇÕES | 171 |
| TOTAL COMO AUTOR | 17 |
| TOTAL COMO EDITOR | 2 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 1991 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2023 |
| ÍNDICE H | 4 |
The third national survey of child and adolescent well-being
Big Data Meets Survey Science”
This article is part of the SSCR special issue on Big Data and Survey Science, guest edited by Adam Eck (Oberlin College), Ana Lucía Córdova Cazar (Universidad San Francisco de Quito), Mario Callegaro (Google Ltd.), and Paul Biemer (RTI International & UNC-CH)
Total Survey Error in Practice
This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields c…
Are Survey Weights Needed? A Review of Diagnostic Tests in Regression Analysis
Researchers apply sampling weights to take account of unequal sample selection probabilities and to frame coverage errors and nonresponses. If researchers do not weight when appropriate, they risk having biased estimates. Alternatively, when they unnecessarily apply weights, they can create an inefficient estimator without reducing bias. Yet in practice researchers rarely test the necessity of weighting and are sometimes guided more by the curren…
Weighting Survey Data
Big Data in Survey Research
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 by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, and the way in which they a…
Local Dependence in Latent Class Analysis of Rare and Sensitive Events
For survey methodologists, latent class analysis (LCA) is a powerful tool for assessing the measurement error in survey questions, evaluating survey methods, and estimating the bias in estimates of population prevalence. LCA can be used when gold standard measurements are not available and applied to essentially any set of indicators that meet certain criteria for identifiability. LCA offers quality inference, provided the key threat to model val…
Survey Measurement and Process Quality
Census Geocoding for Nonresponse Bias Evaluation in Telephone Surveys
Journal Article Census Geocoding for Nonresponse Bias Evaluation in Telephone Surveys: An Assessment of the Error Properties Get access Paul P. Biemer, Paul P. Biemer * *Address all correspondence to Paul Biemer, RTI International, P.O. Box 12194, Research Triangle Park, NC 27709-2194, USA; e-mail: [email protected]. Search for other works by this author on: Oxford Academic Google Scholar Andy Peytchev Andy Peytchev Search for other works by this autho…
Latent Class Analysis of Survey Error
This book concerns the error in data collected using sample surveys, the nature and magnitudes of the errors, their effects on survey estimates, how to model and estimate the errors using a variety of modeling methods, and, finally, how to interpret the estimates and make use of the results in reducing the error for future surveys. The book focuses on models that are appropriate for categorical data, although there are references to the differenc…
Total Survey Error
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 paradigm is viewed as part of a much larger design strategy that seeks to optimize surveys by maximizing total survey quality; i.e., quality more broadly defined to include user-specified dimensions of quality. Survey methodology, viewed within this larger framework, alters…
Introduction to Part 2
Approaches to the Modeling of Measurement Errors
Measurement Errors in Surveys
Introduction to Survey Quality
The principles and concepts of survey measurement quality Issues of survey quality have become increasingly more prominent in recent years. As more and more professionals who are not necessarily trained as survey researchers take on tasks associated with surveys, the need arises for a grounded, basic introduction to current survey methods and quality issues associated with them. Introduction to Survey Quality summarizes the history of survey rese…
An Evaluation of Procedures and Operations Used by the Voter News Service for the 2000 Presidential Election
Journal Article An Evaluation of Procedures and Operations Used by the Voter News Service for the 2000 Presidential Election Get access PAUL BIEMER, PAUL BIEMER Search for other works by this author on: Oxford Academic Google Scholar RALPH FOLSOM, RALPH FOLSOM Search for other works by this author on: Oxford Academic Google Scholar RICHARD KULKA, RICHARD KULKA Search for other works by this author on: Oxford Academic Google Scholar JUDITH LESSLER…
Measurement Errors in Surveys
Partial table of contents: THE QUESTIONNAIRE. The Current Status of 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 in Establishment Surveys (W. Edwards & D. Cantor). INTERVIEWERS AND OTHER MEANS OF DATA COLLECTION. The Design and Analysis of Reinterview: An Overvi…
Measurement Errors in Surveys
An Application of Bootstrapping for Determining a Decision Rule for Site Location
This article provides a general methodology for determining and evaluating a decision rule for hotel site location. Given (a) an indicator of hotel success, (b) an ideal decision rule based on this indicator if it were known without error, and (c) a model for predicting the value of the success indicator at a proposed site, we propose a procedure for finding the optimal model-based decision rule for any specified optimality criterion and for eval…
Total Survey Error
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 paradigm is viewed as part of a much larger design strategy that seeks to optimize surveys by maximizing total survey quality; i.e., quality more broadly defined to include user-specified dimensions of quality. Survey methodology, viewed within this larger framework, alters…
Measurement Errors in Surveys
Big Data in Survey Research
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 by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, and the way in which they a…
Census Geocoding for Nonresponse Bias Evaluation in Telephone Surveys
Journal Article Census Geocoding for Nonresponse Bias Evaluation in Telephone Surveys: An Assessment of the Error Properties Get access Paul P. Biemer, Paul P. Biemer * *Address all correspondence to Paul Biemer, RTI International, P.O. Box 12194, Research Triangle Park, NC 27709-2194, USA; e-mail: [email protected]. Search for other works by this author on: Oxford Academic Google Scholar Andy Peytchev Andy Peytchev Search for other works by this autho…
Local Dependence in Latent Class Analysis of Rare and Sensitive Events
For survey methodologists, latent class analysis (LCA) is a powerful tool for assessing the measurement error in survey questions, evaluating survey methods, and estimating the bias in estimates of population prevalence. LCA can be used when gold standard measurements are not available and applied to essentially any set of indicators that meet certain criteria for identifiability. LCA offers quality inference, provided the key threat to model val…
An Evaluation of Procedures and Operations Used by the Voter News Service for the 2000 Presidential Election
Journal Article An Evaluation of Procedures and Operations Used by the Voter News Service for the 2000 Presidential Election Get access PAUL BIEMER, PAUL BIEMER Search for other works by this author on: Oxford Academic Google Scholar RALPH FOLSOM, RALPH FOLSOM Search for other works by this author on: Oxford Academic Google Scholar RICHARD KULKA, RICHARD KULKA Search for other works by this author on: Oxford Academic Google Scholar JUDITH LESSLER…
Big Data Meets Survey Science”
This article is part of the SSCR special issue on Big Data and Survey Science, guest edited by Adam Eck (Oberlin College), Ana Lucía Córdova Cazar (Universidad San Francisco de Quito), Mario Callegaro (Google Ltd.), and Paul Biemer (RTI International & UNC-CH)
Measurement Errors in Surveys
An Application of Bootstrapping for Determining a Decision Rule for Site Location
This article provides a general methodology for determining and evaluating a decision rule for hotel site location. Given (a) an indicator of hotel success, (b) an ideal decision rule based on this indicator if it were known without error, and (c) a model for predicting the value of the success indicator at a proposed site, we propose a procedure for finding the optimal model-based decision rule for any specified optimality criterion and for eval…
Measurement Errors in Surveys
Partial table of contents: THE QUESTIONNAIRE. The Current Status of 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 in Establishment Surveys (W. Edwards & D. Cantor). INTERVIEWERS AND OTHER MEANS OF DATA COLLECTION. The Design and Analysis of Reinterview: An Overvi…
Measurement Errors in Surveys
Introduction to Survey Quality
The principles and concepts of survey measurement quality Issues of survey quality have become increasingly more prominent in recent years. As more and more professionals who are not necessarily trained as survey researchers take on tasks associated with surveys, the need arises for a grounded, basic introduction to current survey methods and quality issues associated with them. Introduction to Survey Quality summarizes the history of survey rese…
An Evaluation of Procedures and Operations Used by the Voter News Service for the 2000 Presidential Election
Journal Article An Evaluation of Procedures and Operations Used by the Voter News Service for the 2000 Presidential Election Get access PAUL BIEMER, PAUL BIEMER Search for other works by this author on: Oxford Academic Google Scholar RALPH FOLSOM, RALPH FOLSOM Search for other works by this author on: Oxford Academic Google Scholar RICHARD KULKA, RICHARD KULKA Search for other works by this author on: Oxford Academic Google Scholar JUDITH LESSLER…
Approaches to the Modeling of Measurement Errors
Measurement Errors in Surveys
Introduction to Part 2
Latent Class Analysis of Survey Error
This book concerns the error in data collected using sample surveys, the nature and magnitudes of the errors, their effects on survey estimates, how to model and estimate the errors using a variety of modeling methods, and, finally, how to interpret the estimates and make use of the results in reducing the error for future surveys. The book focuses on models that are appropriate for categorical data, although there are references to the differenc…
Total Survey Error
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 paradigm is viewed as part of a much larger design strategy that seeks to optimize surveys by maximizing total survey quality; i.e., quality more broadly defined to include user-specified dimensions of quality. Survey methodology, viewed within this larger framework, alters…
Survey Measurement and Process Quality
Census Geocoding for Nonresponse Bias Evaluation in Telephone Surveys
Journal Article Census Geocoding for Nonresponse Bias Evaluation in Telephone Surveys: An Assessment of the Error Properties Get access Paul P. Biemer, Paul P. Biemer * *Address all correspondence to Paul Biemer, RTI International, P.O. Box 12194, Research Triangle Park, NC 27709-2194, USA; e-mail: [email protected]. Search for other works by this author on: Oxford Academic Google Scholar Andy Peytchev Andy Peytchev Search for other works by this autho…
Local Dependence in Latent Class Analysis of Rare and Sensitive Events
For survey methodologists, latent class analysis (LCA) is a powerful tool for assessing the measurement error in survey questions, evaluating survey methods, and estimating the bias in estimates of population prevalence. LCA can be used when gold standard measurements are not available and applied to essentially any set of indicators that meet certain criteria for identifiability. LCA offers quality inference, provided the key threat to model val…
Weighting Survey Data
Big Data in Survey Research
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 by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, and the way in which they a…
Are Survey Weights Needed? A Review of Diagnostic Tests in Regression Analysis
Researchers apply sampling weights to take account of unequal sample selection probabilities and to frame coverage errors and nonresponses. If researchers do not weight when appropriate, they risk having biased estimates. Alternatively, when they unnecessarily apply weights, they can create an inefficient estimator without reducing bias. Yet in practice researchers rarely test the necessity of weighting and are sometimes guided more by the curren…
Total Survey Error in Practice
This book provides an overview of the TSE framework and current TSE research as related to survey design, data collection, estimation, and analysis. It recognizes that survey data affects many public policy and business decisions and thus focuses on the framework for understanding and improving survey data quality. The book also addresses issues with data quality in official statistics and in social, opinion, and market research as these fields c…
Big Data Meets Survey Science”
This article is part of the SSCR special issue on Big Data and Survey Science, guest edited by Adam Eck (Oberlin College), Ana Lucía Córdova Cazar (Universidad San Francisco de Quito), Mario Callegaro (Google Ltd.), and Paul Biemer (RTI International & UNC-CH)
The third national survey of child and adolescent well-being
Computer Science (16 obras) · Mathematics (11 obras) · Statistics (10 obras) · Survey Methodology and Nonresponse (10 obras) · Geography (6 obras) · Statistical Methods and Bayesian Inference (4 obras) · Surveys (4 obras) · Artificial Intelligence (3 obras) · Data mining (3 obras) · Data-Driven Disease Surveillance (3 obras)