Mixed- and Random-Effects Models
Data that are collected or generated in the context of any practical problem always exhibit variability. This variability calls for the use of appropriate statistical methodology for the data analysis. Data that are obtained from designed experiments are typically analyzed using a model that takes into consideration the various sources or factors that could account for the variability in the data. Here the term experiment denotes the process by which data are generated based on the basis of planned changes in one or more input variables that are expected to influence the response. The plan or layout used to carry out the experiment is referred to as an experimental design or design of the experiment. The analysis of the data is based on an appropriate ...
Looks like you do not have access to this content.
Reader's Guide
Descriptive Statistics
Distributions
Graphical Displays of Data
Hypothesis Testing
Important Publications
Inferential Statistics
Item Response Theory
Mathematical Concepts
Measurement Concepts
Organizations
Publishing
Qualitative Research
Reliability of Scores
Research Design Concepts
Research Designs
Research Ethics
Research Process
Research Validity Issues
Sampling
Scaling
Software Applications
Statistical Assumptions
Statistical Concepts
Statistical Procedures
Statistical Tests
Theories, Laws, and Principles
Types of Variables
Validity of Scores
- All
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z