In social and behavioral sciences, data are typically not normally distributed, which can invalidate hypothesis testing and lead to unreliable results when being analyzed by methods developed for normal data. The existing methods of generating multivariate non-normal data typically create data according to specific univariate marginal measures…

High dimensional multivariate data, where the number of variables approaches or exceeds the sample size, is an increasingly common occurrence for social scientists. Several tools exist for dealing with such data in the context of univariate regression, including regularization methods such as Lasso, Elastic net, Ridge Regression, as well as the…

A latent variable modeling approach for scale reliability evaluation in heterogeneous populations is discussed. The method can be used for point and interval estimation of reliability of multicomponent measuring instruments in populations representing mixtures of an unknown number of latent classes or subpopulations. The procedure is helpful also…

Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…

In some instances, intentionally or not, study designs are such that there is clustering in one group but not in the other. This paper describes methods for computing effect size estimates and their variances when there is clustering in only one group and the analysis has not taken that clustering into account. The authors provide the effect size…

In this article, the authors talk about variation and how variation between measurements may be reduced if sampling is not random. They also talk about replication and its variants. A replicate is a repeated measurement from the same experimental unit. An experimental unit is the smallest part of an experiment or a study that can be subject to a…

We focus on the identification of differential item functioning (DIF) when more than two groups of examinees are considered. We propose to consider items as elements of a multivariate space, where DIF items are outlying elements. Following this approach, the situation of multiple groups is a quite natural case. A robust statistics technique is…

It is a false, but common, belief that statistical significance testing evaluates result replicability. In truth, statistical significance testing reveals nothing about results replicability. Since science is based on replication of results, methods that assess replicability are important. This is particularly true when multivariate methods, which…

Purpose: Residential care/assisted living describes diverse facilities providing non-nursing home care to a heterogeneous group of primarily elderly residents. This article derives typologies of assisted living based on theoretically and practically grounded evidence. Design and Methods: We obtained data from the Collaborative Studies of Long-Term…

Estimates of the Comprehensive Employment and Training Act's net impact on participant earnings, using Continuous Longitudinal Manpower Survey data, were compared to a similar sample from the Current Population Survey. The use of multivariate matching and weighting yielded acceptable results. (GDC)

The Schools and Staffing Survey (SASS) is a periodic, integrated system of sample surveys on elementary and secondary schools in the United States that collects information on school and district administrators and teachers in public and private schools. This technical report is one in a series of methodological studies relating to the SASS of the…