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9780495110842

Intl Stdt Ed-Sampling : Design and Analysis

by
  • ISBN13:

    9780495110842

  • ISBN10:

    0495110841

  • Edition: 2nd
  • Format: Paperback
  • Copyright: 2009-12-18
  • Publisher: Duxbury Press

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Summary

Sharon L. Lohr's SAMPLING: DESIGN AND ANALYSIS, 2e, International Edition provides a modern introduction to the field of survey sampling intended for a wide audience of statistics students. Practical and authoritative, the book is listed as a standard reference for training on real-world survey problems by a number of prominent surveying organizations. Lohr concentrates on the statistical aspects of taking and analyzing a sample, incorporating a multitude of applications from a variety of disciplines. The text 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. Recent research on theoretical and applied aspects of sampling is included, as well as optional technology instructions for using statistical software with survey data.

Table of Contents

Introduction
A Sample Controversy
Requirements of a Good Sample
Selection Bias
Measurement Error
Questionnaire Design
Sampling and Nonsampling Errors
Exercises
Simple Probability Samples
Types of Probability Samples
Framework for Probability Sampling
Simple Random Sampling
Sampling Weights
Confidence Intervals
Sample Size Estimation
Systematic Sampling
Randomization Theory Results for Simple Random Sampling
A Prediction Approach for Simple Random Sampling
When Should a Simple Random Sample Be Used? Chapter Summary
Exercises
Stratified Sampling
What Is Stratified Sampling? Theory of Stratified Sampling
Sampling Weights in Stratified Random Sampling
Allocating Observations to Strata
Defining Strata
Model-Based Inference for Stratified Sampling
Quota Sampling
Chapter Summary
Exercises
Ratio And Regression Estimation
Ratio Estimation in a Simple Random Sample
Estimation in Domains
Regression Estimation in Simple Random Sampling
Poststratification
Ratio Estimation with Stratified Samples
Model-Based Theory for Ratio and Regression Estimation
Chapter Summary
Exercises
Cluster Sampling With Equal Probabilities
Notation for Cluster Sampling
One-Stage Cluster Sampling
Two-Stage Cluster Sampling
Designing a Cluster Sample
Systematic Sampling
Model-Based Inference in Cluster Sampling
Chapter Summary
Exercises
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
Chapter Summary
Exercises
Complex Surveys
Assembling Design Components
Sampling Weights
Estimating a Distribution Function
Plotting Data from a Complex Survey
Univariate Plots
Design Effects
The National Crime Victimization Survey
Sampling and Experiment Design
Chapter Summary
Exercises
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? Chapter Summary
Exercises
Variance Estimation In Complex Surveys
Linearization (Taylor Series) Methods
Random Group Methods
Resampling and Replication Methods
Generalized Variance Functions
Confidence Intervals
Chapter Summary
Exercises
Categorical Data Analysis In Complex Surveys
Chi-Square Tests with Multinomial Sampling
Effects of Survey Design on Chi-Square Tests
Corrections to x2 Tests
Loglinear Models
Chapter Summary
Exercises
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
Chapter Summary
Exercises
Two-Phase Sampling
Theory for Two-Phase Sampling
Two-Phase Sampling with Stratification
Two-Phase Sampling with Ratio Estimation
Subsampling Nonrespondents
Designing a Two-Phase Sample
Chapter Summary
Exercises
Estimating Population Size
Capture-Recapture Estimates
Contingency Tables for Capture-Recapture Experiments
Assessing Undercoverage
Chapter Summary
Exercises
Rare Populations And Small Area Estimations
Sampling for Rare Events
Small Area Estimation
Chapter Summary
Exercises
Survey Quality
Nonresponse Error
Measurement Error
Sensitive Questions
Processing Error
Sampling Error
Interaction of Error Sources
The Future of Sampling
Chapter Summary
Exercises
Appendices: Probability Concepts Used In Sampling
Probability
Random Variables and Expected Value
Conditional Probability
Conditional Expectation
References
Table of Contents provided by Publisher. All Rights Reserved.

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