Literature DB >> 17552475

Extending the CLAST sequential rule to one-way ANOVA under group sampling.

Carmen Ximénez1, Javier Revuelta.   

Abstract

Several studies have demonstrated that the fixed-sample stopping rule (FSR), in which the sample size is determined in advance, is less practical and efficient than are sequential-stopping rules. The composite limited adaptive sequential test (CLAST) is one such sequential-stopping rule. Previous research has shown that CLAST is more efficient in terms of sample size and power than are the FSR and other sequential rules and that it reflects more realistically the practice of experimental psychology researchers. The CLAST rule has been applied only to the t test of mean differences with two matched samples and to the chi-square independence test for twofold contingency tables. The present work extends previous research on the efficiency of CLAST to multiple group statistical tests. Simulation studies were conducted to test the efficiency of the CLAST rule for the one-way ANOVA for fixed effects models. The ANOVA general test and two linear contrasts of multiple comparisons among treatment means are considered. The article also introduces four rules for allocating N observations to J groups under the general null hypothesis and three allocation rules for the linear contrasts. Results show that the CLAST rule is generally more efficient than the FSR in terms of sample size and power for one-way ANOVA tests. However, the allocation rules vary in their optimality and have a differential impact on sample size and power. Thus, selecting an allocation rule depends on the cost of sampling and the intended precision.

Mesh:

Year:  2007        PMID: 17552475     DOI: 10.3758/bf03192847

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  3 in total

1.  Minimizing animal numbers: the variable-criteria sequential stopping rule.

Authors:  Douglas A Fitts
Journal:  Comp Med       Date:  2011-06       Impact factor: 0.982

2.  Ethics and animal numbers: informal analyses, uncertain sample sizes, inefficient replications, and type I errors.

Authors:  Douglas A Fitts
Journal:  J Am Assoc Lab Anim Sci       Date:  2011-07       Impact factor: 1.232

3.  Statistical conclusion validity: some common threats and simple remedies.

Authors:  Miguel A García-Pérez
Journal:  Front Psychol       Date:  2012-08-29
  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.