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Robust Measures of Variable Importance for Multivariate Group Designs

Methods: http://digitalcommons.wayne.edu/jmasm/vol16/ iss2/6 Tolulope T. Sajobi University of Calgary Calgary, AB Lisa M. Lix University of Manitoba Winnipeg, MB Variable importance measures based on

The use of latent variable mixture models to identify invariant items in test construction

Purpose Patient-reported outcome measures (PROMs) are frequently used in heterogeneous patient populations. PROM scores may lead to biased inferences when sources of heterogeneity (e.g., gender, ethnicity, and social factors) are ignored. Latent variable mixture models (LVMMs) can be used to examine measurement invariance (MI) when sources of heterogeneity in the population are...

Differential Item Functioning in the SF-36 Physical Functioning and Mental Health Sub-Scales: A Population-Based Investigation in the Canadian Multicentre Osteoporosis Study

Background Self-reported health status measures, like the Short Form 36-item Health Survey (SF-36), can provide rich information about the overall health of a population and its components, such as physical, mental, and social health. However, differential item functioning (DIF), which arises when population sub-groups with the same underlying (i.e., latent) level of health have...

Discriminant Analysis for Repeated Measures Data: Effects of Mean and Covariance Misspecification on Bias and Error in Discriminant Function Coefficients

Coefficients Tolulope T. Sajobi 0 Lisa M. Lix 0 Longhai Li 0 0 University of Saskatchewan Follow this and additional works at: http://digitalcommons.wayne.edu/jmasm Part of the Applied Statistics Commons ... in an efficient classification rule in multivariate or RM data when there is a large Tolulope T. Sajobi completed his Ph.D. in the School of Public Health. Email him at: . Lisa M. Lix is an Associate

Metabolic system alterations in pancreatic cancer patient serum: potential for early detection

Background The prognosis of pancreatic cancer (PC) is one of the poorest among all cancers, due largely to the lack of methods for screening and early detection. New biomarkers for identifying high-risk or early-stage subjects could significantly impact PC mortality. The goal of this study was to find metabolic biomarkers associated with PC by using a comprehensive metabolomics...