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Measurements of Agreement and Reliability

Workshop

In many fields of research, it is common to have several individuals rate a common set of study participants or objects. These measurements are almost always prone to various sorts of errors. Agreement statistics gauge how close the repeated measurements are by estimating the measurement error. Reliability statistics assess how well study participants\objects can be […]

Principal Component Analysis

Workshop

Principal Component Analysis (PCA) is a popular multivariate technique used for data reduction. By analyzing the variance-covariance structure of a set of variables, uncorrelated linear combinations of the variables (called principal components) are calculated that maximize the amount of variance explained. The resulting principal components can then be used in further analyses such as regression […]

Model Selection and Multimodel Inference

Workshop

Multimodel inference (MMI) is a model selection framework that has recently gained some popularity as an alternative to null hypothesis significance testing. This type of inference favors stepwise approaches (forward and backwards model selection) to determine a single best “final” model. This workshop gives an overview of the MMI framework, in which researchers generate a […]

Introduction to Ordination

Workshop

Ordination is a statistical technique that allows us to graphically summarize complex relationships. Also considered “dimension reduction,” these techniques offer a way to simplify many correlated variables (“dimensions”) into two or three, axes, which are must easier to interpret. In two dimensions we can then map our data points on a figure, and this often […]

Response Surface Methodology

Workshop

Response surface methodology is a related design topic in which the goal is to determine settings for optimizing the expected response. The designs and methodology will be illustrated using examples from the rsm library in R.

Exploratory Factor Analysis

Workshop

Factor Analysis is a widely used multivariate technique. It is a data reduction technique that examines the underlying relations that exist among a set of variables. In doing so it assumes that a small number of unobserved variables, called factors, are responsible for the correlation among a large number of observed variables. This workshop is […]

Introduction to Ordinal Logistic Regression

Workshop

Ordinal logistic regression is an extension of binary logistic regression. This statistical method can be implemented when modeling a dependent variable that is an ordinal (categorical) variable. This workshop will discuss the assumptions behind the ordinal logistic model, the interpretation of the coefficients from the model, post hoc tests.