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Preface.PART I: OVERVIEW AND BASIC APPROACHES.Introduction.Missing Data in Experiments.Complete-Case and Available-Case Analysis, Including Weighting Methods.Single Imputation Methods.Estimation of Imputation Uncertainty...

(NOTE: Each chapter begins with an Introduction, and concludes with Exercises and References.) I. GETTING STARTED. 1. Aspects of Multivariate Analysis. Applications of Multivariate Techniques. The Organization of Data. D...

"The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair entropy-statistical complex...

Materias / palabras clave: Statistical power; Power analysis; Statistical analysis; Behavioural sciences; Power (physics); Psychology; Computer science; Statistics; Econometrics; Mathematics; Data science; Physics

Materias / palabras clave: Power analysis; Statistical power; Statistical analysis; Statistics; Power (physics); Computer science; Mathematics; Psychology; Econometrics; Physics; Quantum mechanics

Materias / palabras clave: Statistical power; Power analysis; Statistical analysis; Psychology; Computer science; Power (physics); Econometrics; Data science; Statistics; Mathematics; Physics; Quantum mechanics

The role and limitations of retrospective investigations of factors possibly associated with the occurrence of a disease are discussed and their relationship to forward-type studies emphasized. Examples of situations in ...

Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a c...

We present here a framework for the study of molecular variation within a single species. Information on DNA haplotype divergence is incorporated into an analysis of variance format, derived from a matrix of squared-dist...

Abstract Statistical parametric maps are spatially extended statistical processes that are used to test hypotheses about regionally specific effects in neuroimaging data. The most established sorts of statistical paramet...

With the increase in genomewide experiments and the sequencing of multiple genomes, the analysis of large data sets has become commonplace in biology. It is often the case that thousands of features in a genomewide data ...

Elements of Experimentation. Single-Factor Experiments. Two-Factor Experiments. Three-or More-Factor Experiments. Comparison Between Treatment Means. Analysis of Multiobservation Data. Problem Data. Analysis of Data from...

Materias / palabras clave: Statistical power; Power (physics); Computer science; Statistical analysis; Power analysis; Extension (predicate logic); Statistical hypothesis testing; Test (biology); Statistics; Programming language; Mathematics; Comp...

The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for stat...

In this paper we are concerned with the practical issues of working with data sets common to finance, statistics, and other related fields. pandas is a new library which aims to facilitate working with these data sets an...

Despite the widespread use of exploratory factor analysis in psychological research, researchers often make questionable decisions when conducting these analyses. This article reviews the major design and analytical deci...

Factor analysis, path analysis, structural equation modeling, and related multivariate statistical methods are based on maximum likelihood or generalized least squares estimation developed for covariance structure models...

A framework for hypothesis testing and power analysis in the assessment of fit of covariance structure models is presented. We emphasize the value of confidence intervals for fit indices, and we stress the relationship o...

Simulation is the process of executing a model, that is a representation of a system with enough detail to describe it but not too excessive. This model has a set of entities, an internal state, a set of input variables ...

In this article, we present FactoMineR an R package dedicated to multivariate data analysis. The main features of this package is the possibility to take into account different types of variables (quantitative or categor...

If radiocarbon measurements are to be used at all for chronological purposes, we have to use statistical methods for calibration. The most widely used method of calibration can be seen as a simple application of Bayesian...

Algebra of Vectors and Matrices. Probability Theory, Tools and Techniques. Continuous Probability Models. The Theory of Least Squares and Analysis of Variance. Criteria and Methods of Estimation. Large Sample Theory and ...

With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of spec...

Abstract Principal component analysis (PCA) is a multivariate technique that analyzes a data table in which observations are described by several inter‐correlated quantitative dependent variables. Its goal is to extrac...