This work reviews sampling methods used in surveys: simple random sampling, systematic sampling, stratification, cluster and multi-stage sampling, sampling with probability proportional to size, two-phase sampling, replicated sampling, panel designs, and non-probability sampling. Kalton discusses issues of practical implementation, including frame problems and non-response, and gives examples of sample designs for a national face-to-face interview survey and for a telephone survey. He also treats the use of weights in survey analysis, the computation of sampling errors with complex sampling designs, and the determination of sample size.
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2 of 2 people found the following review helpful:
3.0 out of 5 stars
Solid introduction to survey sampling,
By Steven A. Peterson (Hershey, PA (Born in Kewanee, IL)) - See all my reviews (VINE VOICE) (TOP 500 REVIEWER) (REAL NAME)
This review is from: Introduction to Survey Sampling (Quantitative Applications in the Social Sciences) (Paperback)
This is a brief but useful introduction to survey sampling. Key question: Who should be interviewed to ensure that the sample, in some manner, represents the larger public?The book considers the simplest form of sampling--the simple random sample. Often, this is impossible, since we would not have a list of the entire population. However, under certain circumstances it is possible. Other issues of importance, depending on the researcher's needs: systematic sampling, stratification, and cluster and multistage sampling. The book also discusses identifying the sampling frame. A universal problem is that--even if we have a good sampling frame and generate a good sample--nonresponse by those identified and approached to be surveyed produces potential biases. What of those who choose not to participate are different than those who do? A bias is automatically introduced. . . . Other issues: sample size, nonprobability sampling, weighting, sampling error. The book is not an easy read for someone wanting a quick and dirty introduction to the subject. But it is a helpful resource.
1 of 1 people found the following review helpful:
3.0 out of 5 stars
Not as Introductory as it sounds,
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This review is from: Introduction to Survey Sampling (Quantitative Applications in the Social Sciences) (Paperback)
This is a required text for a quantitative methods class I'm taking, but what I could really use is a more basic introduction. This book assumes that you know A LOT of statistics already -- it's full of formulas that are never really explained. It does have some great information on improving sampling schemes, but if you're looking for an actual introduction to the subject, this isn't it.
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First Sentence:
Sample surveys are nowadays widely accepted as a means of providing statistical data on an extensive range of subjects for both research and administrative purposes. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
fpc term, epsem sample, proportionate stratification, standard error formulae, interviewer variance, total nonresponse, survey estimators, proportionate stratified sample, unequal selection probabilities, sampled elements, replicated sampling, complex sample designs, unrestricted sample, sampled blocks, central office codes, sampled students, residential numbers, proportionate allocation, multistage design, sampling fraction, stratification factors, expected sample size, quota groups, weighting adjustments, survey variables Key Phrases - Capitalized Phrases (CAPs): (learn more)
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Sample surveys are nowadays widely accepted as a means of providing statistical data on an extensive range of subjects for both research and administrative purposes. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
fpc term, epsem sample, proportionate stratification, standard error formulae, interviewer variance, total nonresponse, survey estimators, proportionate stratified sample, unequal selection probabilities, sampled elements, replicated sampling, complex sample designs, unrestricted sample, sampled blocks, central office codes, sampled students, residential numbers, proportionate allocation, multistage design, sampling fraction, stratification factors, expected sample size, quota groups, weighting adjustments, survey variables Key Phrases - Capitalized Phrases (CAPs): (learn more)
United States New!
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Front Cover | Table of Contents | First Pages | Back Cover | Surprise Me!
Citations (learn more)
This book cites 77
books:
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96
books
cite this book:
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- Analysis of Variance (Quantitative Applications in the Social Sciences) by Gudmund R. Iversen in Back Matter (1), and Back Matter (2)
- Marketing Research by Seymour Sudman in Back Matter (1), and Back Matter (2)
- Survey Methods in Social Investigation by Claus Adolf Moser in Back Matter (1), and Back Matter (2)
- Research Designs (Quantitative Applications in the Social Sciences) by Paul E. Spector in Back Matter
- Sampling Theory of Surveys With Applications by Pandurang V. Sukhatme in Back Matter
See all 77 books this book cites
- Surveying the Social World: Principles and Practice in Survey Research (Understanding Social Research) by Aldridge on page 83, and Back Matter
- The Power of Survey Design: A User's Guide for Managing Surveys, Interpreting Results, and Influencing Respondents by Giuseppe Iarossi on page 95, and Back Matter
- on page 83, and Back Matter
- Household Sample Surveys in Developing and Transition Countries (Studies In Methods (Ser. F)) by United Nations on page 33, and page 66
- Secondary Analysis of Survey Data (Quantitative Applications in the Social Sciences) by K . Jill Kiecolt in Back Matter (1), and Back Matter (2)
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