PS -

Above I said "I would like to know which books are most popularly used today to teach survey sampling (sampling from finite populations)." However, I think I should have said "teach or learn" survey sampling, or just "learn," rather than just teach. Any book you have found useful which covers this subject is eligible, not just one used in a classroom.

Thank you. - Jim

Here are some recommended ones: 1. "Sampling Techniques" by William G. Cochran This classic book covers a wide range of sampling methods with practical examples. It’s comprehensive and delves into both theory and application, making it valuable for students and professionals. 2. "Survey Sampling" by Leslie Kish'' This is another foundational text, known for its detailed treatment of survey sampling design and estimation methods. Kish's book is especially useful for those interested in practical survey applications. 3. "Model Assisted Survey Sampling" by Carl-Erik Särndal, Bengt Swensson, and Jan Wretman This book introduces model-assisted methods for survey sampling, which blend traditional design-based methods with model-based techniques. It's ideal for more advanced readers interested in complex survey designs. 4. "Sampling of Populations: Methods and Applications" by Paul S. Levy and Stanley Lemeshow This text is widely used in academia and provides thorough explanations of different sampling methods with a focus on real-world applications. It also includes case studies and practical exercises, making it helpful for hands-on learners. 5. "Introduction to Survey Sampling" by Graham Kalton This introductory book offers a concise and accessible overview of survey sampling methods. It’s well-suited for beginners who need a straightforward introduction to key concepts. 6. "Designing Surveys: A Guide to Decisions and Procedures" by Johnny Blair, Ronald F. Czaja, and Edward A. Blair This book focuses on the practical aspects of designing and conducting surveys, with particular emphasis on decision-making and procedural choices in the survey process.

Thank you Gideon. I have some of those books. Something along the line of "'Model Assisted Survey Sampling' by Carl-Erik Särndal, Bengt Swensson, and Jan Wretman," Springer, you mentioned, is what I had in mind, though that book was published in 1992 (2003 being the softcover printing - which I have), but I'd like to see a newer recommendation, at that level or higher.

Please note that I said that "I would like to know which books are most popularly used today...."

Thank you - Jim

Subquestion to question above: 

Above, Gideon Amponsah Adjei suggested the following book, among others:

Levy, P.S. and Lemeshow, S.(2008), 4th ed, Sampling of Populations: Methods and Applications, Wiley. 

When I asked this question on ASA Connect (from the American Statistical Association) one of the suggestions I received from another member was the following:

Wu, C. and Thompson, M.E.(2020), Sampling Theory and Practice, Springer. 

So, if anyone has experience with both of these books, I would like to know how these two books compare. (Please do not just cut-and-paste reviews.  I can find those.  I want to know actual impressions from anyone with experience with these two books.)  Also, if you have experience with just one of these two books, I would still like to hear about that.  Thank you. 

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Please also consider the main question regarding reference/textbook recommendations.  (If you are a publisher representative, please disclose this fact.) 

Please consider this:

Lohr(2022) has a comparison between randomization theory and model-based theory on pages 56 - 61, sections 2.9 and 2.10.  She shows the connection between simple random sampling and the common mean model. -  Ratio and regression estimation is taken up in Chapter 4.

Thompson(2012) shows two examples (examples 1 and 3 in Chapter 7: "Auxiliary Data and Ratio Estimation") where he compares results from a small sample and small population experiment, first using a design-based ratio estimator and then ratio modeling for prediction (with the same level of heteroscedasticity as implied in the design-based case, I'll note).

Brewer(2002) explained (mid-page 111 with other references to this in his book) why the degree of heteroscedasticity (I'll note) associated with (implied by) the classical ratio estimator is the minimum to be expected. In Särndal, Swensson and Wretman(1992), section 7.3.3, on "Optimal Sampling Design for pi Weighted Ratio Estimation," would be impacted by this.  Many other works to this day might look into a homoscedastic option for ratio modeling which should not exist - though I've found that data quality problems for small units could cause this to be simulated to an extent. 

. 

These should be influential sections of textbooks/reference books to note and I'm working on doing just that in a future paper. (I've written about Ken Brewer's discovery on multiple occasions, but it seems to not be widely known.)

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Any other suggestions for sampling textbooks/reference books?  Those which compare design-based and model-based techniques are particularly of interest.

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Brewer, K.R.W.(2002), Combined Survey Sampling Inference: Weighing Basu's Elephants, Arnold: London and Oxford University Press.

Lohr, S.L.(2022), Sampling: Design and Analysis, 3rd ed, CRC Press. (Copyright Sharon L. Lohr)

Särndal, C.-E., Swensson, B., and Wretman, J.(1992), Model Assisted Survey Sampling, Springer-Verlang.

Thompson, S.K.(2012), Sampling, 3rd ed, John Wiley & Sons.

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I have other books in my collection, but the above is a meaningful excerpt from the material upon which I am working.

Again, are there any other suggestions for sampling textbooks/reference books?

Thank you.  -  Jim Knaub

I recently added the following to my personal library:

Chaudhuri, A. and Pal S.(2022), A Comprehensive Textbook on Sample Surveys, Springer/Indian Statistical Institute Series.

[As I am retired, it should be obvious that anything I say is my personal opinion. When working for the US Federal Government in the past, that was also the case, though I did get grief from Government lawyers for having my affiliation given on a book review for the Journal of Official Statistics. I did not think anyone would think that meant i was writing an official Government position on a book, and when I told JOS the concern, it was laughed off.]

Regarding the book above, I know that the first author has a great deal of knowledge.  In the book, he did, however, note in the Preface that a "shortcoming" was stated to be the absence of material on nonprobability sampling. It was explained that the authors have a lack of confidence in its efficacy, and lack "participation" in this area. They suggested Wu and Thompson (2020) for some of this material, which is a book I noted above in the question section. Also I note that a great deal of the current literature in journal articles is on inference from nonprobability sampling, so that can be used. There is a chapter in Valliant, Dever, and Kreuter (2018) below. It seems to rely on methods involving covariates. At the US Energy Information Administration (EIA) I caused the implementation of a prediction approach with modified cutoff sampling to be used for multiple surveys, and there has been and continues to be a great deal of success over a number of years for many thousands of applications at the EIA. Results have been tested thoroughly and have held up since the start, circa 1990, with development which followed.

However, nonprobabability sampling for establishment surveys with repeated sample and census surveys for Official Statistics can be a great deal different from that done with social web surveys where covariate data may be less reliable and techniques perhaps less helpful, I would think.  See https://www.researchgate.net/publication/383976649_Cut-off_Cutoff_Quasi-Cutoff_and_Other_Nonprobability_Sampling_with_Inference and https://www.researchgate.net/publication/362370770_Application_of_Efficient_Sampling_with_Prediction_for_Skewed_Data.

For the book above, Chaudhuri and Pal (2022), at the end of a chapter on small area estimation, they note that they have "limited coverage" and suggest other books.

I see in that book, which I recently obtained, that my main interest in this book is the prediction approach in chapter 8, where development by Ken Brewer and Richard Royall is noted. Actually, I have interest in comparison of this to the design-based model-assisted approach which I see is in chapter 7, as I am comparing ratio estimation with ratio model prediction, as found in various books. Thus I expect to be examining parts of those two chapters.

On another book, Levy, P.S. and Lemeshow, S.(2008), 4th ed, Sampling of Populations: Methods and Applications, Wiley, I have noticed, interestingly, that they have reversed the usual roles of Y and X for regression to estimate totals, as I think used to be the case in some older works, if I remember correctly.  At any rate, I think I have seen that somewhere before. They have some chapters added by other authors for part of a selected topics section of the book.

I have ordered a copy of THEORY AND METHODS OF SURVEY SAMPLING (2008), 2nd ed: MUKHOPADHYAY, PARIMAL.

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There are a number of good books including

Chaudhuri, A. and Pal, S.(2022), A Comprehensive Textbook on Sample Surveys, Springer (INSIS).

Lohr, S.(2022), Sampling: Design and Analysis, 3rd ed, CRC Press.

Wu, C. and Thompson, M.(2020), Sampling Theory and Practice, Springer.

Tillé, Y.(2020), Sampling and Estimation from Finite Populations, Wiley. 

Valliant, R., Dever, J.A., and Kreuter, F. (2018), Practical Tools for Designing and Weighting Survey Samples, 2nd ed, Springer.

Thompson, S.K.(2012), Sampling, 3rd ed, John Wiley & Sons.

Chambers, R, and Clark, R(2012), An Introduction to Model-Based Survey Sampling with Applications, Oxford Statistical Science Series. 

Valliant, R, Dorfman, A.H., and Royall, R.M.(2000), Finite Population Sampling and Inference: A Prediction Approach, Wiley Series in Probability and Statistics.

Särndal, C.-E., Swensson, B., and Wretman, J.(1992), Model Assisted Survey Sampling, Springer-Verlang.

Levy, P.S. and Lemeshow, S.(2008), 4th ed, Sampling of Populations: Methods and Applications, Wiley. 

and others ...

including older books like ...

Cochran, W.G. (1953, 1977) Sampling Techniques, 1st and 3rd eds, Wiley.

Sukhatme, P.V. (1954), Sampling Theory of Surveys with Applications, The Indian Society of Agricultural Statistics and The Iowa State College Press.  

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There are other reference/textbooks which I could mention.

There was some input above by Gideon Amponsah Adjei, and another member of ResearchGate sent me a response in private. A couple of other people also responded when I asked on ASA Connect about current use of sampling books. 

But I'd like to hear from more people, preferable answering here.

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Any comments on any sampling references/texts for finite populations, especially newer ones in use now, for research (R&D) or classroom, would be welcomed.  Thank you.