Providing software solutions since 1976
Capabilities
- Analysis of Variance
- Bayesian Analysis
- Categorical Data Analysis
- Cluster Analysis
- Descriptive Statistics
- Distribution Analysis
- Discriminant Analysis
- Exact Methods
- Group Sequential Design and Analysis
- Market Research
- Missing Value Imputation
- Mixed Models
- Multivariate Analysis
- Nonparametric Statistics
- Power and Sample Size
- Psychometric Analysis
- Regression
- Spatial Analysis
- Structural Equations
- Survey Sampling and Analysis
- Survival Analysis
- Transformations
- SAS/STAT Procedures A-Z
The NESTED Procedure
- performs random-effects analysis of variance for data from an experiment with a nested (hierarchical) structure and classification effects
- descriptive analysis of covariation
- obtain separate analyses on observations in groups
- capacity to handle unbalanced data
- automatically displays the following for each dependent variable:
- Coefficients of Expected Mean Squares
- each Variance Source in the model (the different components of variance) and the total variance
- degrees of freedom (DF) for the corresponding sum of squares
- Sum of Squares for each classification factor
- F Value for a factor and the significance levels of a test of the hypothesis that each variance component equals zero
- the appropriate Error Term for an F test
- Mean Square due to a factor
- estimates of the Variance Components
- Percent of Total (the proportion of variance due to each source)
- Mean
- automatically displays the following when there are multiple dependent variables:
- degrees of freedom
- sum of products
- mean products
- covariance component
- variance component correlation
- mean square correlation
- use ODS to create a SAS data set corresponding to any table
For further details see the SAS/STAT User's Guide:
The NESTED Procedure
( PDF | HTML )
Examples
Statistics and Operations Research Home Page | SAS/STAT Software
