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- Keyword
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- Gene- or region-based association study (1)
- Missing data analysis; missingness mechanisms; planned missing design; multiple imputation; full information maximum likelihood (1)
- Multiple quantitative traits (1)
- Partial least square (1)
- Planned missing designs; simulation; full information maximum likelihood (FIML); multiple imputation (MI); 3-form survey (1)
Articles 1 - 4 of 4
Full-Text Articles in Physical Sciences and Mathematics
Influence Of Introgression And Geological Processes On Phylogenetic Relationships Of Western North American Mountain Suckers (Pantosteus, Catostomidae), Peter J. Unmack, Thomas E. Dowling, Nina J. Laitinen, Carol L. Secor, Richard L. Mayden, Dennis K. Shiozawa, Gerald R. Smith
Influence Of Introgression And Geological Processes On Phylogenetic Relationships Of Western North American Mountain Suckers (Pantosteus, Catostomidae), Peter J. Unmack, Thomas E. Dowling, Nina J. Laitinen, Carol L. Secor, Richard L. Mayden, Dennis K. Shiozawa, Gerald R. Smith
Biological Sciences Faculty Research Publications
Intense geological activity caused major topographic changes in Western North America over the past 15 million years. Major rivers here are composites of different ancient rivers, resulting in isolation and mixing episodes between river basins over time. This history influenced the diversification of most of the aquatic fauna. The genus Pantosteus is one of several clades centered in this tectonically active region. The eight recognized Pantosteus species are widespread and common across southwestern Canada, western USA and into northern Mexico. They are typically found in medium gradient, middle-elevation reaches of rivers over rocky substrates. This study (1) compares molecular data …
Comparing Partial Least Square Approaches In Gene-Or Region-Based Association Study For Multiple Quantitative Phenotypes, Zhongshang Yuan, Xiaoshuai Zhang, Fangyu Li, Jinghua Zhao, Fuzhong Xue
Comparing Partial Least Square Approaches In Gene-Or Region-Based Association Study For Multiple Quantitative Phenotypes, Zhongshang Yuan, Xiaoshuai Zhang, Fangyu Li, Jinghua Zhao, Fuzhong Xue
Human Biology Open Access Pre-Prints
On thinking quantitatively of complex diseases, there are at least three statistical strategies for association study: single SNP on single trait, gene-or region (with multiple SNPs) on single trait and on multiple traits. The third of which is the most general in dissecting the genetic mechanism underlying complex diseases underpinning multiple quantitative traits. Gene-or region association methods based on partial least square (PLS) approaches have been shown to have apparent power advantage. However, few attempts are developed for multiple quantitative phenotypes or traits underlying a condition or disease, and the performance of various PLS approaches used in association study for …
On The Joys Of Missing Data, Todd D. Little, Terrence D. Jorgensen, Kyle M. Lang, E. Whitney G. Moore
On The Joys Of Missing Data, Todd D. Little, Terrence D. Jorgensen, Kyle M. Lang, E. Whitney G. Moore
Kinesiology, Health and Sport Studies
We provide conceptual introductions to missingness mechanisms—missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR)—and state-of-the-art methods of handling missing data—full-information maximum likelihood (FIML) and multiple imputation (MI)—followed by a discussion of planned missing designs: multiform questionnaire protocols, two-method measurement models, and wave-missing longitudinal designs. We reviewed 80 articles of empirical studies published in the 2012 issues of the Journal of Pediatric Psychology to present a picture of how adequately missing data are currently handled in this field. To illustrate the benefits of utilizing MI or FIML and incorporating planned missingness into study designs, …
Planned Missing Data Designs & Small Sample Size: How Small Is Too Small?, Fan Jia, E. Whitney G. Moore, Richard Kinai, Kelly S. Crowe, Alexander M. Schoemann, Todd D. Little
Planned Missing Data Designs & Small Sample Size: How Small Is Too Small?, Fan Jia, E. Whitney G. Moore, Richard Kinai, Kelly S. Crowe, Alexander M. Schoemann, Todd D. Little
Kinesiology, Health and Sport Studies
Utilizing planned missing data (PMD) designs (ex. 3-form surveys) enables researchers to ask participants fewer questions during the data collection process. An important question, however, is just how few participants are needed to effectively employ planned missing data designs in research studies. This paper explores this question by using simulated three-form planned missing data to assess analytic model convergence, parameter estimate bias, standard error bias, mean squared error (MSE), and relative efficiency (RE).Three models were examined: a one-time point, cross-sectional model with 3 constructs; a two-time point model with 3 constructs at each time point; and a three-time point, mediation …