Sampling frame

Abstract: Addendum: The supplementary documents referenced in this manuscript are posted on the Web site https://www.fia.fs.fed.us/library/sampling/index.phpThe Forest Inventory and Analysis (FIA) Program of the U.S. Department of Agriculture Forest Service is in the process of moving from a system of quasiindependent, regional, periodic inventories to an enhanced program featuring greater national consistency, annual measurement of a proportion of plots in each State, new reporting requirements, and integration with the ground sampling component of the Forest Health Monitoring Program. This documentation presents an overview of the conceptual changes, explains the three phases of FIA's sampling design, describes the sampling frame and plot configuration, presents the estimators that form the basis of FIA's National Information Management System (NIMS), and shows how annual data are combined for analysis. It also references a number of Web-based supplementary documents that provide greater detail about some of the more obscure aspects of the sampling and estimation system, as well as examples of calculations for most of the common estimators produced by FIA.

Abstract: Series Foreword Preface Chapter 1. An Introduction to Surveys and to This Book The Practice of Survey Research The Uses of Surveys Overview of the Survey Process A Brief Summary of This Book Chapter 2. Stages of a Survey Stage 1: Survey Design and Preliminary Planning Stage 2: Pretesting Stage 3: Final Survey Design and Planning Stage 4: Data Collection Stage 5: Data Coding, Data-File Construction, Analysis, and Final Report Example of a Time Schedule for a Study Chapter 3. Selecting the Method of Data Collection Evaluating the Advantages and Disadvantages of the Four Survey Methods Mail Surveys Internet Surveys Telephone Surveys Face-to-Face Surveys Combinations of Methods Chapter 4. Questionnaire Design: Writing the Questions Questionnaire Design as Process Factors in Questionnaire Development Writing Questions Chapter 5. Questionnaire Design: Organizing the Questions Introducing the Study What Questions Should the Questionnaire Begin With? Grouping Questions into Sections Questionnaire Length and Respondent Burden Avoiding Other Flaws in Mail Questionnaire Design Chapter 6. Questionnaire Design: Testing the Questions Importance of Respondents' Comprehension of and Ability to Answer Questions Conventional Pretests and Interviewer Debriefings Post-Interview Interviews Behavior Coding A Note on Intercoder Reliability Cognitive Interviews Respondent Debriefing Expert Panel Examining Interviewer Tasks Revising and Retesting: Deciding Which Pretest Problems to Address Deciding How Much Testing Is Enough Pilot Tests Combined Methods Some Last Advice Chapter 7. Designing the Sample The Basics Defining the Population Constructing a Sampling Frame Matching Defined Populations and Sampling Frames Recognizing Problems with Sampling Frames Determining Sample Size Hypothesis Testing and Power Using Census Data Chapter 8. Selecting a Sample Example 1: A Community List-Assisted Telephone Sample Example 2: A Directory-Based Community Telephone Sample Example 3: Other RDD Telephone Samples Selecting Respondents within Households Example 4: A List Sample of Students Example 5: A Sample of University Classes Chapter 9. Reducing Sources of Error in Data Collection The Origins of Error Chapter 10. Special Topics Ethical Issues in Survey Research The Methodology Report The Utility of the Methodology Report What to Include in the Methodology Report Costs and Contingencies: Planning for the Unexpected For Further Study: Suggested Readings Appendix A Appendix B Appendix C Glossary/Index

Abstract: Constructing scientifically sound samples of hard-to-reach populations, also known as hidden populations, is a challenge for many research projects. Traditional sample survey methods, such as random sampling from telephone or mailing lists, can yield low numbers of eligible respondents while non-probability sampling introduces unknown biases. The authors describe a venue-based application of time-space sampling (TSS) that addresses the challenges of accessing hard-to-reach populations. The method entails identifying days and times when the target population gathers at specific venues, constructing a sampling frame of venue, day-time units (VDTs), randomly selecting and visiting VDTs (the primary sampling units), and systematically intercepting and collecting information from consenting members of the target population. This allows researchers to construct a sample with known properties, make statistical inference to the larger population of venue visitors, and theorize about the introduction of biases that may limit generalization of results to the target population. The authors describe their use of TSS in the ongoing Community Intervention Trial for Youth (CITY) project to generate a systematic sample of young men who have sex with men. The project is an ongoing community level HIV prevention intervention trial funded by the Centers for Disease Control and Prevention. The TSS method is reproducible and can be adapted to hard-to-reach populations in other situations, environments, and cultures.