Analysis of variance—why it is more important than ever
نویسندگان
چکیده
منابع مشابه
Analysis of variance---why it is more important than ever
Analysis of variance (Anova) is an extremely important method in exploratory and confirmatory data analysis. Unfortunately, in complex problems (for example, splitplot designs), it is not always easy to set up an appropriate Anova. We propose a hierarchical analysis that automatically gives the correct Anova comparisons even in complex scenarios. The inferences for all means and variances are p...
متن کاملDiscussion of “ Analysis of Variance — Why It Is More Important than Ever ” by a . Gelman
Bayesian inference and fixed and random effects. Professor Gelman writes " Bayesians see analysis of variance as an inflexible classical method. " He adopts a hierarchical Bayesian framework to " identify ANOVA with the structuring of parameters into batches. " In this framework he sidesteps " the overloaded terms fixed and random " and defines effects " as constant if they are identical for al...
متن کاملDiscussion of “ Analysis of Variance — Why It Is More Important than Ever ”
Andrew Gelman’s contribution shifts the focus of “Analysis of Variance” (ANOVA) from the limited sense in which it has been commonly used in classical statistics, as a method of testing, to the broader framework of estimation and inference. The term more commonly used in this sense, “variance components modeling,” also captures the same spirit. The essential idea is that of constructing distrib...
متن کاملRejoinder to “analysis of Variance—why It Is More Important than Ever” by A. Gelman
ANOVA is more important than ever because we are fitting models with many parameters, and these parameters can often usefully be structured into batches. The essence of “ANOVA” (as we see it) is to compare the importance of the batches and to provide a framework for efficient estimation of the individual parameters and related summaries such as comparisons and contrasts. Classical ANOVA is asso...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2005
ISSN: 0090-5364
DOI: 10.1214/009053604000001048