Linking Methods for Multidimensional Forced Choice Tests Using the Multi-Unidimensional Pairwise Preference Model.

Applications of multidimensional forced choice (MFC) testing have increased considerably over the last 20 years. Yet there has been little, if any, research on methods for linking the parameter estimates from different samples. This research addressed that important need by extending four widely used methods for unidimensional linking and comparing the efficacy of new estimation algorithms for MFC linking coefficients based on the Multi-Unidimensional Pairwise Preference model (MUPP).

Estimating the Multidimensional Generalized Graded Unfolding Model with Covariates Using a Bayesian Approach.

Noncognitive constructs are commonly assessed in educational and organizational research. They are often measured by summing scores across items, which implicitly assumes a dominance item response process. However, research has shown that the unfolding response process may better characterize how people respond to noncognitive items.

Comparison of parameter estimation approaches for multi-unidimensional pairwise preference tests.

Multidimensional forced-choice (MFC) testing has been proposed as a way of reducing response biases in noncognitive measurement. Although early item response theory (IRT) research focused on illustrating that person parameter estimates with normative properties could be obtained using various MFC models and formats, more recent attention has been devoted to exploring the processes involved in test construction and how that influences MFC scores. This research compared two approaches for estimating multi-unidimensional pairwise preference model (MUPP; Stark et al.

: An R Package for Bayesian Estimation of the Multidimensional Generalized Graded Unfolding Model With Covariates.

Over the past couple of decades, there has been an increasing interest in adopting ideal point models to represent noncognitive constructs, as they have been demonstrated to better measure typical behaviors than traditional dominance models do. The generalized graded unfolding model () has consistently been the most popular ideal point model among researchers and practitioners. However, the GGUM2004 software and the later developed package in R can only handle unidimensional models despite the fact that many noncognitive constructs are multidimensional in nature.

Social support and quality of life among rural family caregivers of persons with severe mental illness in Sichuan Province, China: mediating roles of care burden and loneliness.

Objective: To explore the relationship between social support and quality of life (QoL) among family caregivers of persons with severe mental illness (SMI) and examine the mediating roles of care burden and loneliness.

Methods: A cross-sectional study was carried out between December 2017 and May 2018. A random sample of 256 family caregivers of persons with SMI in rural areas of Sichuan Province, China was recruited for participation.

Built environment, physical activity, and obesity of adults in Pingshan District, Shenzhen City in Southern China.

Background: The relation between neighbourhood built environment and obesity has been described as both nuanced and complex.

Aim: The objective of this study was to examine the relationship between the built environment, physical activity, and obesity in a rapidly urbanised area of China.

Subjects And Methods: This is a cross-sectional study.

The Relationship Between Health Literacy, Social Support, Depression, and Frailty Among Community-Dwelling Older Patients With Hypertension and Diabetes in China.

Population aging is one of the major challenges facing modern society and has attracted global attention. With population aging becoming a global phenomenon, the impact of age-related diseases on health is increasing rapidly. Frailty is one of the most pressing issues facing older adults.