Generalizability Theory With One-Facet Nonadditive Models

Generalizability Theory: Overview

36 Generalizability Theory

Generalizability (G) theory is a statistical theory for evaluating the dependability (or reliability) of behavioral measurements (Cronbach, Gleser, Nanda, & Rajaratnam, 1972; see also Brennan, 2001; Shavelson & Webb, 1991). G theory permits the researcher to address such questions as: Is the sampling of tasks or judges the major source of measurement error? Can I improve the reliability of the ...

On generalizability of MOOC models

The big data imposes the key problem of generalizability of the results. In the present contribution, we discuss statistical tools which can help to select variables adequate for target level of abstraction. We show that a model considered as over-fitted in one context can be accurate in another. We illustrate this notion with an example analysis experiment on the data from 13 university Massiv...

Fundamental measure density functional theory for nonadditive hard-core mixtures: the one-dimensional case.

We treat a one-dimensional binary mixture of hard-core particles that possess nonadditive diameters. For this model, a density functional theory is constructed following similar principles as an earlier extension of Rosenfeld's fundamental measure theory to three-dimensional nonadditive hard-sphere mixtures. The theory applies to arbitrary positive and moderate negative nonadditivity and reduce...

Generalizability in Causal Inference: Theory and Algorithms

of the Dissertation Generalizability in Causal Inference: Theory and Algorithms