How many subjects?: statistical power analysis in research
Kraemer, Helena Chmura
How many subjects?: statistical power analysis in research - Newbury Park SAGE Publications 1987 - 120; ill.,bibl.; BookFind
CHAPTER 1 Introduction CHAPTER 2 General Concepts CHAPTER 3 The Pivotal Case Intraclass Correlation CHAPTER 4 Equality of News Z- and T- tests, Balanced ANOVA CHAPTER 5 Correlation Coefficients CHAPTER 6 Linear Regression CHAPTER 7 Homogeneity of Variance Tests CHAPTER 8 Binomial Tests CHAPTER 9 Contingency Table Analysis CHAPTER 10 Conclusions.
Hardback 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.
0803929498
STATISTICS, methods
How many subjects?: statistical power analysis in research - Newbury Park SAGE Publications 1987 - 120; ill.,bibl.; BookFind
CHAPTER 1 Introduction CHAPTER 2 General Concepts CHAPTER 3 The Pivotal Case Intraclass Correlation CHAPTER 4 Equality of News Z- and T- tests, Balanced ANOVA CHAPTER 5 Correlation Coefficients CHAPTER 6 Linear Regression CHAPTER 7 Homogeneity of Variance Tests CHAPTER 8 Binomial Tests CHAPTER 9 Contingency Table Analysis CHAPTER 10 Conclusions.
Hardback 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.
0803929498
STATISTICS, methods