@article { ISI:000255532900018,
	title = {Hypothesis testing in comparative and experimental studies of function-valued traits},
	journal = {EVOLUTION},
	volume = {62},
	number = {5},
	year = {2008},
	month = {MAY},
	pages = {1229-1242},
	publisher = {BLACKWELL PUBLISHING},
	type = {Article},
	address = {9600 GARSINGTON RD, OXFORD OX4 2DQ, OXON, ENGLAND},
	abstract = {Many traits of evolutionary interest, when placed in their developmental, physiological, or environmental contexts, are function-valued. For instance, gene expression during development is typically a function of the age of an organism and physiological processes are often a function of environment. In comparative and experimental studies, a fundamental question is whether the function-valued trait of one group is different from another. To address this question, evolutionary biologists have several statistical methods available. These methods can be classified into one of two types: multivariate and functional. Multivariate methods, including univariate repeated-measures analysis of variance (ANOVA), treat each trait as a finite list of data. Functional methods, such as repeated-measures regression, view the data as a sample of points drawn from an underlying function. A key difference between multivariate and functional methods is that functional methods retain information about the ordering and spacing of a set of data values, information that is discarded by multivariate methods. In this study, we evaluated the importance of that discarded information in statistical analyses of function-valued traits. Our results indicate that functional methods tend to have substantially greater statistical power than multivariate approaches to detect differences in a function-valued trait between groups.},
	keywords = {Functional data analysis, multivariate analysis, phenotype, power, repeated-measures ANOVA, repeated-measures regression},
	issn = {0014-3820},
	doi = {10.1111/j.1558-5646.2008.00340.x},
	author = {Griswold, Cortland K. and Gomulkiewicz, Richard and Heckman, Nancy}
}
