caa a22 4500 606196404 CHVBK 20210128100924.0 cr unu---uuuuu 210128e20150301xx s 000 0 eng 10.1007/s10260-014-0271-x doi (NATIONALLICENCE)springer-10.1007/s10260-014-0271-x Tests for statistical significance of a treatment effect in the presence of hidden sub-populations [Elektronische Daten] [B. Karmakar, K. Dhara, K. Dey, A. Basu, A. Ghosh] For testing the statistical significance of a treatment effect, we often compare between two parts of a population; one is exposed to the treatment, and the other is not exposed to it. Standard parametric or nonparametric two-sample tests are commonly used for this comparison. But direct applications of these tests can yield misleading results, especially when the population has some hidden sub-populations, and the effect of this sub-population difference on the response dominates the treatment effect. This problem becomes more evident if these sub-populations have widely different proportions of representatives in the samples obtained from these two parts. In this article, we propose some simple methods to overcome these limitations. These proposed methods first use a suitable clustering algorithm to find the hidden sub-populations, and then they eliminate the sub-population effect by using a suitable transformation of the data. Standard two-sample tests, when they are applied on the transformed data, usually yield better results. We analyze some simulated and real data sets to demonstrate the utility of these proposed methods. Springer-Verlag Berlin Heidelberg, 2014 Dunn index nationallicence Gap statistic nationallicence EM algorithm nationallicence Bayesian model averaging nationallicence PAM clustering algorithm nationallicence Univariate and multivariate two-sample tests nationallicence Karmakar B. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut Dhara K. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut Dey K. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut Basu A. National Institute of Biomedical Genomics, 741251, Kalyani, India aut Ghosh A. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut Statistical Methods & Applications Springer Berlin Heidelberg 24/1(2015-03-01), 97-119 1618-2510 24:1<97 2015 24 10260 https://doi.org/10.1007/s10260-014-0271-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10260-014-0271-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Karmakar B. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut NATIONALLICENCE 700 1- Dhara K. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut NATIONALLICENCE 700 1- Dey K. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut NATIONALLICENCE 700 1- Basu A. National Institute of Biomedical Genomics, 741251, Kalyani, India aut NATIONALLICENCE 700 1- Ghosh A. Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, India aut NATIONALLICENCE 773 0- Statistical Methods & Applications Springer Berlin Heidelberg 24/1(2015-03-01), 97-119 1618-2510 24:1<97 2015 24 10260