Sampling: Design and Analysis

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Summary: nice introduction to survey sampling
Review: For me the classic book on survey sampling is Cochran's. The second edition of Cochran was published in 1977 and there have been many advances since including the use of superpopulation models. Lohr provides the basic concepts first followed with many exercises at the end of the chapters. It is designed for a first course which could be taken by statistics majors or undergraduates in fields that use survey sampling such as business, sociology, psychology or biology. Many real surveys are presented and the standard topics (e.g. stratified and cluster sampling) are covered. Issues of nonresponse are also discussed. Chapter 12 covers topics not commonly seen in survey sampling texts including two-phase sampling and capture-recapture analysis. Warner's method of randomized response to deal with sensitive questionnaires is also covered in Chapter 12. It is also unusual in that it provides a great deal of coverage of resampling methods to estimate variance components including the bootstrap, jackknife and balanced repeated replicates. It also deals with regression and logistic regression in problems involving complex survey data. Missing data issues are also discussed as are imputation methods The book contains a many references to the literature and also includes a CD ROM with some data sets and a software program called SURVEY.

Rating:
Summary: I've seen better math textbooks.
Review: I took a sampling course last year and I must say this text on its own is terrbily deficient. Few completed examples, no solutions at the back of the book, no solutions manual provided to the professor and a horribly vague and sometimes irrelevant exercise section gives any student using this text a difficult time to read/learn.

I suggest sourcing out another before using this one. A bland reference at most.

Rating:
Summary: A well-written guide to sampling design and analysis.
Review: Sharon Lohr does a great job of covering the subject of sampling, which seems to be overlooked in most curricula even though the need for it is ubiquitous across disciplines. This text is appropriate at an intermediate level such as third or fourth year undergraduate or first-year graduate study. The math notation appears to be an attempt to bridge between the notation used at the introductory level and that which appears in graduate texts such as Greene. I found it relatively easy to follow, but it might not be so easy for someone who is seeing it for the first time. The best feature of the book is its comprehensive coverage of the subject. If you have a question about sampling, there is likely a concise and understandable answer available in this text.

Rating:
Summary: Mediocre
Review: This book is not very student-friendly. Over-all, the book is an easy read and the examples in each section are helpful. However, the notation used by Lohr differs from the notation used by the statistical community (and professors) which makes applying her text to real life problems or other classes complicated. Also, the questions at the end of the chapters are asked in a vague manner. I am never sure what the questions are really asking. There is no answer key to the questions in the text, so your guess is as good as mine...

Rating:
Summary: excellent sampling textbook
Review: this is an excellent book on sampling. it accommadates all reader levels (undergrad, graduate, practioner and theorist). i can't comment too much about the theoretical aspects of the book because that is not my focus. but for those who want to learn about sampling and use it for their jobs or school projects, i cannot think of a better text. i find myself referring to the text constantly. her examples are relatively clear and easy to follow, in my opinion. she covers cluster sampling and complex surveys (variance calculations) in depth and with great clarity.