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1. |
Record Nr. |
UNICAMPANIAVAN00245850 |
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Titolo |
Advances in VLSI, Communication, and Signal Processing : Select Proceedings of VCAS 2019 / David Harvey ... [et al.] editors |
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Pubbl/distr/stampa |
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Singapore, : Springer, 2021 |
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Descrizione fisica |
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XXII, 741 p. : ill. ; 24 cm |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910827493303321 |
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Autore |
Biemer Paul P |
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Titolo |
Latent class analysis of survey error / / Paul P. Biemer |
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Pubbl/distr/stampa |
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Hoboken, N.J., : Wiley, 2011 |
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ISBN |
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9786612884436 |
9781118099575 |
1118099575 |
9781282884434 |
1282884433 |
9780470891155 |
0470891157 |
9780470891148 |
0470891149 |
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Descrizione fisica |
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1 online resource (412 p.) |
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Collana |
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Wiley series in survey methodology |
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Disciplina |
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Soggetti |
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Error analysis (Mathematics) |
Sampling (Statistics) |
Estimation theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Latent Class Analysis of Survey Error; Contents; Preface; Abbreviations; CHAPTER 1: Survey Error Evaluation; CHAPTER 2: A General Model for Measurement Error; CHAPTER 3: Response Probability Models for Two Measurements; CHAPTER 4: Latent Class Models for Evaluating Classification Errors; CHAPTER 5: Further Aspects of Latent Class Modeling; CHAPTER 6: Latent Class Models for Special Applications; CHAPTER 7: Latent Class Models for Panel Data; CHAPTER 8: Survey Error Evaluation: Past, Present, and Future; APPENDIX A: Two-Stage Sampling Formulas; APPENDIX B: Loglinear Modeling Essentials |
ReferencesIndex |
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Sommario/riassunto |
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"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 latent class analysis (LCA), a wide range of related models and applications are also discussed"-- |
"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"-- |
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