Latent Class Analysis of Survey Error
Dados Bibliográficos
| ID | 19905331 |
|---|---|
| Autores | Paul P Biemer (0000-0003-2214-2707, Naval Dockyards Society, autor correspondente) |
| Ano | 2010 |
| Páginas | 387 |
| Data de publicação | 2010-12-06 |
| Open Access | Sim |
| Tipo | BOOK |
| Periódico | Latent class analysis of survey error (SOURCE_BOOK) |
| Editora | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/9780470891155 |
| OpenAlex | W593310612 |
| Open Library | OL25059529M |
| ISBN | 9780470891155 |
| Idioma | EN |
| Citações recebidas | 14 |
| Referências citadas | 1 |
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 differences and special problems that arise in the analysis and modeling of error for continuous data. Though the primary modeling method that is described is
Cronbach's alpha · Errors-in-Variables Models · Item response theory · Mean squared error · Observational error · Polytomous Rasch model · Psychometrics · Reliability (semiconductor) · Statistics · Mathematics · Survey Methodology and Nonresponse · Error analysis (Mathematics) · Estimation theory · Sampling (Statistics) · Sampling Studies · Selection Bias · Statistics as Topic · Surveys
Measuring obesity in the absence of a gold standard
Developing a Cross-National Comparative Framework for Studying Labour Market Segmentation
A Multiple-Indicator Latent Growth Mixture Model to Track Courses with Low-Quality Teaching
Local Dependence in Latent Class Analysis of Rare and Sensitive Events
Investigating Response Errors in Survey Data
Latent class analysis of response inconsistencies across modes of data collection
Understanding Linkages Among Mixture Models
Latent variable modeling to develop a robust proxy for sensitive behaviors
A Guide to Detecting and Modeling Local Dependence in Latent Class Analysis Models
Employment quality and mental health in China under the policy of expanding jobs and benefiting people’s livelihood
Using hidden Markov models to assess and correct for measurement error in digital trace data
Total Survey Error
Total Survey Error
Data Quality of Digital Process Data
| Obras citantes distintas | 14 |
|---|---|
| Citações por ano | 0,88 |
| Intervalo de citações | 2010 - 2025 (16) |
| Velocidade de citação | recent |
| Altamente citado | Não |
| Tipos de citação | Neutras: 7 |