Geodesic
Confidence intervals for large non-centrality parameters
Discussiones Mathematicae. Probability and Statistics, Tome 35 (2015) no. 1-2, pp. 45-56

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We use asymptotic linearity to derive confidence intervals for large non-centrality parameters. These results enable us to measure relevance of effects and interactions in multifactors models when we get highly statistically significant the values of F tests statistics. We show how to use our approach by considering two sets of data as application examples.
Keywords: asymptotic linearity, non-centrality parameters, highly significant, F tests, measure relevance 
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Inacio, Sonia; Oliveira, Manuela; Mexia, João. Confidence intervals for large non-centrality parameters. Discussiones Mathematicae. Probability and Statistics, Tome 35 (2015) no. 1-2, pp. 45-56. http://geodesic.mathdoc.fr/item/DMPS_2015_35_1-2_a2/