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Nonprobability sampling

About: Nonprobability sampling is a research topic. Over the lifetime, 3068 publications have been published within this topic receiving 58967 citations.


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Journal ArticleDOI
TL;DR: Seven major types of sampling for observational studies of social behavior have been found in the literature and the major strengths and weaknesses of each method are pointed out.
Abstract: Seven major types of sampling for observational studies of social behavior have been found in the literature. These methods differ considerably in their suitability for providing unbiased data of various kinds. Below is a summary of the major recommended uses of each technique: In this paper, I have tried to point out the major strengths and weaknesses of each sampling method. Some methods are intrinsically biased with respect to many variables, others to fewer. In choosing a sampling method the main question is whether the procedure results in a biased sample of the variables under study. A method can produce a biased sample directly, as a result of intrinsic bias with respect to a study variable, or secondarily due to some degree of dependence (correlation) between the study variable and a directly-biased variable. In order to choose a sampling technique, the observer needs to consider carefully the characteristics of behavior and social interactions that are relevant to the study population and the research questions at hand. In most studies one will not have adequate empirical knowledge of the dependencies between relevant variables. Under the circumstances, the observer should avoid intrinsic biases to whatever extent possible, in particular those that direcly affect the variables under study. Finally, it will often be possible to use more than one sampling method in a study. Such samples can be taken successively or, under favorable conditions, even concurrently. For example, we have found it possible to take Instantaneous Samples of the identities and distances of nearest neighbors of a focal individual at five or ten minute intervals during Focal-Animal (behavior) Samples on that individual. Often during Focal-Animal Sampling one can also record All Occurrences of Some Behaviors, for the whole social group, for categories of conspicuous behavior, such as predation, intergroup contact, drinking, and so on. The extent to which concurrent multiple sampling is feasible will depend very much on the behavior categories and rate of occurrence, the observational conditions, etc. Where feasible, such multiple sampling can greatly aid in the efficient use of research time.

12,470 citations

Journal ArticleDOI
TL;DR: It is concluded that the choice of the techniques (Convenience Sampling and Purposive Sampling) depends on the nature and type of the research.
Abstract: This article studied and compared the two nonprobability sampling techniques namely, Convenience Sampling and Purposive Sampling. Convenience Sampling and Purposive Sampling are Nonprobability Sampling Techniques that a researcher uses to choose a sample of subjects/units from a population. Although, Nonprobability sampling has a lot of limitations due to the subjective nature in choosing the sample and thus it is not good representative of the population, but it is useful especially when randomization is impossible like when the population is very large. It can be useful when the researcher has limited resources, time and workforce. It can also be used when the research does not aim to generate results that will be used to create generalizations pertaining to the entire population. Therefore, there is a need to use nonprobability sampling techniques. The aim of this study is to compare among the two nonrandom sampling techniques in order to know whether one technique is better or useful than the other. Different articles were reviewed to compare between Convenience Sampling and Purposive Sampling and it is concluded that the choice of the techniques (Convenience Sampling and Purposive Sampling) depends on the nature and type of the research.

4,956 citations

Journal ArticleDOI
TL;DR: A new variant of chain-referral sampling, respondent-driven sampling, is introduced that employs a dual system of structured incentives to overcome some of the deficiencies of such samples and discusses how respondent- driven sampling can improve both network sampling and ethnographic investigation.
Abstract: A population is “hidden” when no sampling frame exists and public acknowledgment of membership in the population is potentially threatening. Accessing such populations is difficult because standard probability sampling methods produce low response rates and responses that lack candor. Existing procedures for sampling these populations, including snowball and other chain-referral samples, the key-informant approach, and targeted sampling, introduce well-documented biases into their samples. This paper introduces a new variant of chain-referral sampling, respondent-driven sampling, that employs a dual system of structured incentives to overcome some of the deficiencies of such samples. A theoretic analysis, drawing on both Markov-chain theory and the theory of biased networks, shows that this procedure can reduce the biases generally associated with chain-referral methods. The analysis includes a proof showing that even though sampling begins with an arbitrarily chosen set of initial subjects, as do most chain-referral samples, the composition of the ultimate sample is wholly independent of those initial subjects. The analysis also includes a theoretic specification of the conditions under which the procedure yields unbiased samples. Empirical results, based on surveys of 277 active drug injectors in Connecticut, support these conclusions. Finally, the conclusion discusses how respondent- driven sampling can improve both network sampling and ethnographic 44 investigation.

3,950 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present a discussion of mixed methods sampling techniques, which combines well-established qualitative and quantitative techniques in creative ways to answer research questions posed by MM research designs.
Abstract: This article presents a discussion of mixed methods (MM) sampling techniques. MM sampling involves combining well-established qualitative and quantitative techniques in creative ways to answer research questions posed by MM research designs. Several issues germane to MM sampling are presented including the differences between probability and purposive sampling and the probability-mixed-purposive sampling continuum. Four MM sampling prototypes are introduced: basic MM sampling strategies, sequential MM sampling, concurrent MM sampling, and multilevel MM sampling. Examples of each of these techniques are given as illustrations of how researchers actually generate MM samples. Finally, eight guidelines for MM sampling are presented.

3,256 citations

Book
01 Jan 1993
TL;DR: Chapters 2-17 end with a Summary of Methodological Approaches to the Social World Conclusions.
Abstract: Chapters 2-17 end with a Summary CHAPTER 1. INTRODUCTION Why Study Research Methods? Methodological Approaches to the Social World Conclusions I. THE SCIENTIFIC AND ETHICAL CONTEXTS OF SOCIAL RESEARCH CHAPTER 2. THE NATURE OF SCIENCE The Aim of Science Science as Product Science as Process Science: Ideal versus Reality CHAPTER 3. RESEARCH ETHICS Data Collection and Analysis Treatment of Human Subjects Making Ethical Decisions The Uses of Research: Science and Society II. RESEARCH DESIGN CHAPTER 4. ELEMENTS OF RESEARCH DESIGN Origins of Research Topics Units of Analysis Variables Relationships Formulating Questions and Hypotheses Research Purposes and Research Design Stages of Social Research CHAPTER 5. MEASUREMENT The Measurement Process Levels of Measurement Reliability and Validity Reliability Assessment Validity Assessment A Final Note on Reliability and Validity CHAPTER 6. SAMPLING Why Sample? Population Definition Sampling Designs Probability Sampling Nonprobability Sampling Other Sampling Designs Factors Affecting Choice of Sampling Design Factors Determining Sample Size Final Notes on Sampling Errors and Generalizability III. METHODS OF DATA COLLECTION CHAPTER 7. EXPERIMENTATION The Logic of Experimentation Staging Experiments The Experiment as a Social Occasion Experimentation Outside the Laboratory CHAPTER 8. EXPERIMENTAL DESIGNS Threats to Internal Validity Pre-experimental Designs True Experimental Designs Factorial Experimental Designs Quasi-experimental Designs CHAPTER 9. SURVEY RESEARCH General Features of Survey Research The Uses and Limitations of Surveys Survey Research Designs Steps in Survey Research: Planning Face-to-Face and Telephone Interviewing Paper-and-Pencil Mailed Questionnaires Computer-Assisted Interviews Mixed-Mode Surveys Field Administration CHAPTER 10. SURVEY INSTRUMENTATION The Survey as a Social Occasion Materials Available to the Survey Designer "Sketches" or Preliminaries Filling in the Sketch: Writing the Items Pretesting CHAPTER 11. FIELD RESEARCH The Potentials and Limitations of Field Research Research Design and Sampling Field Observation Field Interviewing Stages of Field Research CHAPTER 12. RESEARCH USING AVAILABLE DATA Sources of Available Data Advantages of Research Using Available Data General Methodological Issues in Available-Data Research Historical Analysis Content Analysis CHAPTER 13. MULTIPLE METHODS Triangulation Multiple Measures of Concepts within the Same Study Multiple Tests of Hypotheses across Different Studies A Comparison of the Four Basic Approaches to Social Research Meta-Analysis CHAPTER 14. EVALUATION RESEARCH Framework and Sample Studies Types of Evaluation Research Methodological Issues in Evaluation Research The Social and Political Context of Evaluation Research IV. DATA PROCESSING, ANALYSIS, AND INTERPRETATION CHAPTER 15. DATA PROCESSING AND ELEMENTARY DATA ANALYSIS Preview of Analysis Steps Data Processing Data Matrices and Documentation The Functions of Statistics in Social Research Inspecting and Modifying the Data Preliminary Hypothesis Testing CHAPTER 16. MULTIVARIATE ANALYSIS Modeling Relationships Elaboration: Tables and Beyond Multiple-Regression Analysis Other Modeling Techniques CHAPTER 17. WRITING RESEARCH REPORTS Searching the Literature Using the Internet Using the Library Outlining and Preparing to Write Major Headings Other Considerations Length

3,072 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20235,812
202213,211
2021396
2020444
2019381
2018313