Analysis of covariance /
This title presents a technique for analyzing the effects of variables, groups, and treatments in both experimental and observational settings, considering not only the main effects of one variable upon another, but also the effects of group cases.
| Основен автор: | Wildt, Albert R. |
|---|---|
| Други автори: | Ahtola, Olli. |
| Формат: | Електронна книга |
| Език: | English |
| Публикувано: |
Beverly Hills, Calif. :
Sage Publications,
℗♭1978.
|
| Серия: |
Quantitative applications in the social sciences ;
ser. no. 07-012. |
| Предмети: | |
| Онлайн достъп: |
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=24679 |
| Подобни документи: |
Print version::
Analysis of covariance. |
Съдържание:
- 1. Introduction
- Overview of analysis of covariance
- Alternate problem perspectives with analysis of covariance
- 2. Applications of analysis of covariance
- Application one: Coerciveness and change
- Application two: Partitioning and perceived crowding in a public space
- Application three: Comparison of alternate teaching methods
- Application four: American occupational structure
- 3. Principal uses of analysis of covariance
- Increase precision of randomized experiments
- Remove bias due to nonrandom assignment of experimental test units
- When to use analysis of covariance in experimental settings
- Remove bias in observational studies
- Regression with multiple classifications
- 4. Statistical procedures for analysis of covariance for a one-way layout
- Introduction
- Covariance model
- Completely randomized design
- Testing [beta]
- Comparisons among means
- A priori orthogonal comparisons
- A posteriori nonorthogonal comparisons
- Numeric example for completely randomized design
- Geometric representation
- Alternate perspective of testing with analysis of covariance
- Other problem perspectives
- Analysis under second perspective
- Analysis under regression perspective
- 5. Analysis of covariance for more complex layouts
- Randomized complete block design
- Covariance model
- Testing [beta]
- Mean comparisons
- Numeric example for randomized complete block design
- Factorial design
- Covariance model
- Further considerations
- Testing [beta]
- Comparisons among means
- Numeric example for two-factor design with equal cell size
- Analysis with unequal cell sizes
- Other designs.