A Parametric Bootstrap Approach for One-Way ANOVA Under Unequal Variances with Unbalanced Data

نویسنده

  • Guoyi Zhang
چکیده

This research is to provide a solution of one-way ANOVA without using transformation when variances are heteroscedastic and group sizes are unequal. Parametric boothstrap test (Krishnamoorthy, Lu, & Mathew, 2007) has been shown to be competitive with many other methods when testing the equality of group means. We extend the parametric bootstrap algorithm to a multiple comparison procedure. Simulation results show that the parametric bootstrap approach works well for one-way ANOVA.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Comparing two testing procedures in unbalanced two-way ANOVA models under heteroscedasticity‎: Approximate degree of freedom and parametric bootstrap approach

‎The classic F-test is usually used for testing the effects of factors in homoscedastic two-way ANOVA models‎. ‎However‎, ‎the assumption of equal cell variances is usually violated in practice‎. ‎In recent years‎, ‎several test procedures have been proposed for testing the effects of factors‎. ‎In this paper‎, ‎the two methods that are approximate degree of freedom (ADF) and parametric bootstr...

متن کامل

A parametric bootstrap approach for ANOVA with unequal variances: Fixed and random models

This article is about testing the equality of several normal means when the variances are unknown and arbitrary, i.e., the set up of the one-way ANOVA. Even though several tests are available in the literature, none of them perform well in terms of type I error probability under various sample size and parameter combinations. In fact, the type I errors can be highly inflated for some of the com...

متن کامل

On the Size of the F-Test for the One-Way Random Model with Heterogeneous Error Variances

Traditional analysis of variance (ANOVA) tests are based on the assumption of homogeneous error variances, which often fails in real situations. Violation of this assumption affects not only the power of the standard F-test, but also its size. When a design is unbalanced, the effect of unequal error variances is even more complicated. In this paper, we study the effect of heterogeneous error va...

متن کامل

A Bootstrap-based Non-parametric ANOVA Method with Applications to Factorial Microarray Data

Many microarray experiments have factorial designs, but there are few statistical methods developed explicitly to handle the factorial analysis in these experiments. We propose a bootstrap-based non-parametric ANOVA (NANOVA) method and a gene classification algorithm to classify genes into different groups according to the factor effects. The proposed method encompasses one-way and two-way mode...

متن کامل

Comparing the Student ' s t and the ANOVA contrast procedure with five alternative procedures

A robustness study to investigate the performance of six procedures for comparing two or more groups, under several circumstances, has been carried out. The study was divided in four parts. The first three were Monte-Carlo studies, and the fourth was a study on empirical data. The six procedures were the ANOVA (or its special case, the Student's t) procedure (1), the Satterthwaite (or its speci...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Communications in Statistics - Simulation and Computation

دوره 44  شماره 

صفحات  -

تاریخ انتشار 2015