How Many Subjects?: Statistical Power Analysis in Research [Hardcover]

Helena Chmura Kraemer (Author), Chmura Kraemer (Author), Sue Thiemann (Author)

List Price:	CDN$ 66.22
Price:	CDN$ 53.48 & this item ships for FREE with Super Saver Shipping. Details
You Save:	CDN$ 12.74 (19%)
	o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o

In Stock.
Ships from and sold by Amazon.ca. Gift-wrap available.

Only 1 left in stock--order soon (more on the way).

Want it delivered Tuesday, May 29? Choose One-Day Shipping at checkout.

Product Details

Hardcover: 120 pages
Publisher: Sage Publications, Inc.; 1 edition (1987)
Language: English
ISBN-10: 0803929498
ISBN-13: 978-0803929494
Product Dimensions: 23.7 x 15.6 x 1.4 cm
Shipping Weight: 249 g
Amazon Bestsellers Rank: #715,933 in Books (See Top 100 in Books)
- #30 in Books > Science > Mathematics > Research

Would you like to update product info or give feedback on images?

See Complete Table of Contents

Product Description

Review

"Until now no broad framework has existed to treat power in a unified fashion across hypothesis testing techniques... An excellent contribution to the literature... A valuable reference book... A nice addition to the statistical literature. How Many Subjects? Should be at the disposal of teachers and students of statistics." Applied Psychological Measurement

Product Description

How Many Subjects? is a practical guide to sample size calculations and general principles of cost-effective research. It introduces a simple technique of statistical power analysis which allows researchers to compute approximate sample sizes and power for a wide variety of research designs. Because the same technique is used with only slight modifications for different statistical tests, researchers can easily compare the sample sizes required by different designs and tests to make cost-effective decisions in planning a study. These comparisons, emphasized throughout the book, demonstrate important principles of design, measurement and analysis that are rarely discussed in courses or textbooks.

Inside This Book (Learn More)

First Sentence
"How large a sample size must I have?" Read the first page

Explore More
Concordance

Tag this product

(What's this?)

Think of a tag as a keyword or label you consider is strongly related to this product.
Tags will help all customers organize and find favorite items.

Customer Reviews

There are no customer reviews yet on Amazon.ca

5 star:		(0)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(0)

Share your experience with this product with others

Create your own review

Most Helpful Customer Reviews on Amazon.com ^(beta)

Amazon.com: 5.0 out of 5 stars (2 customer reviews)

30 of 30 people found the following review helpful

5.0 out of 5 stars simple well-written book about sample size determination, Feb 22 2008

By Michael R. Chernick "statman31147" - Published on Amazon.com

This review is from: How Many Subjects?: Statistical Power Analysis in Research (Hardcover)

Helen Kraemer is a Stanford Professor with a subspecialty in statistics. She wrote this delightful book with the simple title "How many subjects." Along with Jacob Cohen's book this was one of the first statistical textbooks devoted to the determination of power and sample size in hypothesis testing situations. It is a great reference book on the topic. With the appearance of statistical software to handle the problems addressed in these books and more, the book now serve the purpose of providing a deeper understanding of the issues and an aid to help the user understand what the parameters (e.g. effect size, subject to subject variance) mean.

3 of 3 people found the following review helpful

5.0 out of 5 stars significance and power, Dec 3 2008

By Jan Galkowski "Jan Galkowski" - Published on Amazon.com

Amazon Verified Purchase(What's this?)

This review is from: How Many Subjects?: Statistical Power Analysis in Research (Hardcover)

Whatever your statistical background, the approach of this book to the question of statistical power is highly illuminating. For instance, I am a poor statistician, primarily an engineer with a mathematical bent. I happen to fall into experimental and, thus, statistical contexts frequently. Nevertheless, this book elucidated the issues surrounding the somewhat ritualistic "receiver operating characteristics" tradeoffs routine of detectability versus false alarm rate more than any text in my experience. It showed how costs of failures factored into the decision threshold, rather than making some routine mimickry of a classroom derivation.

So even if statistical power isn't a routine place to visit, this book is worthwhile.

I'd say, however, that matters of statistical power ought to be considered more than they are, even if they aren't a natural fit for Bayesian formulations, which seem currently to be in vogue.

› Go to Amazon.com to see both reviews 5.0 out of 5 stars