Master of Science / Department of Statistics / Dallas E. Johnson / Variability is inherent in most data and often it is useful to study the variability so
scientists are able to make more accurate statements about their data. One of the most
popular ways of analyzing variance in data is by making use of a one-way ANOVA
which consists of partitioning the variability among observations into components of
variability corresponding to between groups and within groups. One then has
σ(subY)(superscript 2)=σ (sub A) (superscript)2+σ(sub e)(superscript 2). Thus there are two variance components. In certain situations, in addition
to estimating these components of variance, it is important to estimate functions of the
variance components. This report is devoted to methods for constructing confidence
intervals for three particular functions of variance components in the unbalanced One-
way random effects models. In order to compare the performance of the methods,
simulations were conducted using SAS® and the results were compared across several
scenarios based on the number of groups, the number of observations within each group,
and the value of sigma (sub A)(superscript 2).
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/4160 |
| Date | January 1900 |
| Creators | Banasik, Aleksandra Anna |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Report |
Page generated in 0.0024 seconds