A Procedure for Clustering Means of Unequal-Sized Samples in ANOVA
โ Scribed by Dr. H. Neumann
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 200 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0323-3847
No coin nor oath required. For personal study only.
โฆ Synopsis
Institut fur Pflanzenzuchtnng Giilzow-Gustrow der Akademie der Lendwirtschaftewiseenschaften der DDR
Srmmay
The proposed procedure "SECOLTCO" is baaed on the sequential construction of linear contrasts. After an analysis of variance the procedure is able to claseify the treatments represented by mean values of unequahhd samples made at random into distinguhhable group. For the purpose of illustrating the procedure "SECOLICO" a simplified example is given.
๐ SIMILAR VOLUMES
We consider two simple estimators of the mean p in a variance component model (one-way classification, unbalanced case) 1 1 FI=; 7 Yjk; F2=; 2 g j \* ## I I n dependence of the estimation procedure (ANOVA, MINQ, sampling theory) we obtain several different estimators for t h e variances of pl and
Derivation of the minimum sample size is an important consideration in an applied research effort. When the outcome is measured at a single time point, sample size procedures are well known and widely applied. The corresponding situation for longitudinal designs, however, is less well developed. In