کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1146341 1489688 2012 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nonparametric bootstrap tests of conditional independence in two-way contingency tables
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آنالیز عددی
پیش نمایش صفحه اول مقاله
Nonparametric bootstrap tests of conditional independence in two-way contingency tables
چکیده انگلیسی

When analyzing a two-way contingency table, a preliminary question is often whether the categorical variables under study, say RR and SS, are independent or not. Suppose now that for each individual in the table, a continuous variable XX is also known. It is then worth analyzing the table conditionally on XX. Contrasting these “local” results to the global unconditional case allows one to go beyond the initial analysis and provide a better understanding of the underlying phenomenon. Recently, Geenens and Simar (2010) [11] have proposed two nonparametric procedures for testing whether RR and SS are conditionally independent given XX, free of any constraining linearity assumptions. However, based on an average of kernel-based estimators, the asymptotic criterion they suggested shows an inflated Type I error (false positive) for small to moderate sample sizes. In this paper, we address this problem by proposing consistent bootstrap versions of the Geenens–Simar test procedures when testing for local independence. A comprehensive simulation study indeed shows the superiority of the bootstrap rejection criterion as compared to the asymptotic criterion in terms of Type I error. It also highlights the advantage of the flexibility guaranteed by the nonparametric Geenens–Simar tests when compared with parametric competitors, e.g. logistic models. The approach is finally illustrated with a real-data example.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 112, November 2012, Pages 130–144
نویسندگان
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