Libri di Stefano Bonnini - libri Statistica & Applicazioni

Stefano Bonnini

Author's books

Nonparametric directional tests in the presence of confounding factors and categorical data
Free
digital
format: Article | STATISTICA & APPLICAZIONI - 2009 - 1
Year: 2009
In modern socio-economic systems, often the aim of a performance analysis or quality evaluation is to compare different products, different manufacturing plants or service centres, different actions or distinct treatments. The question is, ‘‘Which is better?’’ This is complicated because the considered aspects are often measured through categorical data and the results can be affected by confounding factors. To solve this problem we discuss some directional permutation tests based on the nonparametric combination of dependent permutation tests (NPC) for two-sample comparisons in the presence of ordinal categorical variables and confounding factors. In particular we present a new permutation test based on the combination of a finite number of sample moments. To reduce the confounding effects we consider the joint application of stratification and the NPC method. We also show the results of Monte Carlo simulations in order to compare permutation solutions with other nonparametric tests and to evaluate the robustness of the test based on moments.
Download
Multivariate permutation tests for evaluating effectiveness of universities through the analysis of student dropouts digital
format: Article | STATISTICA & APPLICAZIONI - 2005 - Special issue
Year: 2005
This paper deals with the problem of testing for dropping out (by censoring all graduate students) in analogy with survival analysis.
Download
 

This site or third-party tools used by this make use of cookies necessary for the operation and useful for the purposes outlined in the cookie policy.
If you want to learn more or opt out of all or some cookies, see the cookie policy.
By closing this warning, browsing this page, clicking on a link or continuing to browse otherwise, you consent to the use of cookies.

I Agree