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Sampling : design and analysis / Sharon L. Lohr

Main Author Lohr, Sharon L., 1960- Country Estados Unidos. Publication Pacific Grove : Duxbury Press, cop. 1999 Description XV, 494 p. : il. ; 25 cm + CD-Rom ISBN 0-534-35361-4 CDU 303.02 303.5
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Holdings
Item type Current location Call number Status Date due Barcode Item holds Course reserves
Monografia Biblioteca da UMinho no Campus de Azurém
BPG 303.02 - L Available 332842

Licenciatura em Estatística Aplicada Sondagens e Técnicas de Amostragem 2º semestre

Produtos Computador Biblioteca da UMinho no Campus de Azurém
BREG9 303.02 - L Available 332852
Total holds: 0

Enhanced descriptions from Syndetics:

Sharon L. Lohr's SAMPLING: DESIGN AND ANALYSIS provides a modern introduction to the field of sampling. With a multitude of applications from a variety of disciplines, the book concentrates on the statistical aspects of taking and analyzing a sample. Overall, the book gives guidance on how to tell when a sample is valid or not, and how to design and analyze many different forms of sample surveys.

Table of contents provided by Syndetics

  • 1 Introduction A Sample Controversy
  • Requirements of a Good Sample
  • Selection Bias
  • Measurement Bias
  • Questionnaire Design
  • Sampling and Nonsampling Errors
  • Exercises
  • 2 Simple Probability Samples Types of Probability Samples
  • Framework for Probability Sampling
  • Simple Random Sampling
  • Confidence Intervals
  • Sample Size Estimation
  • Systematic Sampling
  • Randomization Theory Results for Simple Random Sampling
  • A Model for Simple Random Sampling
  • When Should a Simple Random Sample Be Used?
  • Exercises
  • 3 Ratio and Regression Estimation Ratio Estimation
  • Regression Estimation
  • Estimation in Domains
  • Models for Ration and Regression Estimation
  • Comparison
  • Exercises
  • 4 Stratified Sampling What is Stratified Sampling?
  • Theory of Stratified Sampling
  • Sampling Weights
  • Allocating Observations to Strata
  • Defining Strata
  • A Model for Stratified Sampling
  • Poststratification
  • Quota Sampling
  • Exercises
  • 5 Cluster Sampling with Equal Probabilities Notation for Cluster Sampling
  • One-Stage Cluster Sampling
  • Two-Stage Cluster Sampling
  • Using Weights in Cluster Samples
  • Designing a Cluster Sample
  • Systematic Sampling
  • Models for Cluster Sampling
  • Summary Exercises
  • 6 Sampling with Unequal Probabilities Sampling One Primary Sampling Unit
  • One-Stage Sampling with Replacement
  • Two-Stage Sampling with Replacement
  • Unequal-Probability Sampling Without Replacement
  • Examples of Unequal-Probability Samples
  • Randomization Theory Results and Proofs
  • Models and Unequal-Probability Sampling
  • 7 Complex Surveys Assembling Design Components
  • Sampling Weights
  • Estimating a Distribution Function
  • Plotting Data from a Complex Survey
  • Design Effects
  • The National Crime Victimization Survey
  • Sampling and Experiment Design
  • Exercises
  • 8 Nonresponse Effects of Ignoring Nonresponse
  • Designing Surveys to Reduce Nonsampling Errors
  • Callbacks and Two-Phase Sampling
  • Mechanisms for Nonresponse
  • Weighting Methods for Nonresponse
  • Imputation
  • Parametric Models for Nonresponse
  • What is An Acceptable Response Rate?
  • Exercises
  • 9 Variance Estimation in Complex Surveys Linearization (Taylor Series) Methods
  • Random Group Methods
  • Resampling and Replication Methods
  • Generalized Variance Functions
  • Confidence Intervals
  • Summary and Software
  • Exercises
  • 10 Categorical Data Analysis in Complex Surveys Chi-square Tests with Multinomial Sampling
  • Effects of Survey Design on Chi-Square Tests
  • Corrections to Chi-Square Tests
  • Loglinear Models
  • Exercises
  • 11 Regression with Complex Survey Data Model-based Regression in Simple Random Samples
  • Regression in Complex Surveys
  • Should Weights be Used in Regression?
  • Mixed Models for Cluster Samples
  • Logistic Regression
  • Generalized Regression Estimation for Population Totals
  • Exercises
  • 12 Other Topics in Sampling Two-Phase Sampling
  • Capture-Recapture Estimation
  • Estimation in Domains, Revisited
  • Sampling for Rare Events
  • Randomized Response
  • Appendix A The Survey Program
  • Appendix B Probability Concepts Used in Sampling
  • Probability
  • Random Variables and Expected Value
  • Conditional Probability
  • Conditional Expectation
  • Appendix C Data Sets
  • Appendix D Computer Codes Used for Examples
  • Appendix E Statistical Table
  • References
  • Author Index
  • Subject Index

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