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| Titel: |
Type i error rates for divisive clustering methods for grouping means in analysis of variance |
| Auteur: |
Carmer, S. G. Lin, W. T. |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 12 (1983) nr. 4 pagina's 451-466 |
| Jaar: |
1983 |
| Inhoud: |
Five univariate divisive clustering methods for grouping means in analysis of variance are considered.Unlike pairwise multiple comparison procedures, cluster analysis has the advantage of producing non-overlapping groups of the treatment means. Comparisonwise Type I error rates and average numbers of clusters per experiment are examined for a heterogeneous set of 20 true treatment means with 11 embedded homogenous sub-groups of one or more treatments. The results of a simulation study clearly show that observed comparisonwise error rate and number of clusters are determined to a far greater extent by the precision of the experiment (as determined by the magnitude of the standard deviation) than by either the stated significance level or the clustering method used. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 14 van 14 gevonden artikelen
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