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What The Joint Admission Medical Program (Jamp) Can Do For Texas Physicians; What Texas Physicians Can Do For Jamp - See More At: Http://Www.Texmed.Org/Aug12journal/#Sthash.M6pv8cjh.Dpuf, Alan Podawiltz, James Richardson, Wallace Gleason, Kathleen Fallon, David Jones, Elizabeth Peck, Jeffrey Rabek, Manuel Schydlower, William Thomson, Russell Warne, Budge Mabry, Paul Hermesmeyer, Quentin Smith
What The Joint Admission Medical Program (Jamp) Can Do For Texas Physicians; What Texas Physicians Can Do For Jamp - See More At: Http://Www.Texmed.Org/Aug12journal/#Sthash.M6pv8cjh.Dpuf, Alan Podawiltz, James Richardson, Wallace Gleason, Kathleen Fallon, David Jones, Elizabeth Peck, Jeffrey Rabek, Manuel Schydlower, William Thomson, Russell Warne, Budge Mabry, Paul Hermesmeyer, Quentin Smith
Russell T Warne
Texas faces health challenges requiring a physician workforce with understanding of a broad range of issues – including the role of culture, income level, and health beliefs – that affect the health of individuals and communities. Building on previous successful physician workforce "pipeline" efforts, Texas established the Joint Admission Medical Program (JAMP), a first-of-its-kind program to encourage access to medical education by Texans who are economically disadvantaged. The program benefits those from racial and ethnic minority groups and involves all 31 public and 34 private Texas undergraduate colleges and universities offering life science degrees, as well as all 9 medical …
Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter
Statistical Methods Used In Gifted Education Journals, 2006-2010, Russell Warne, Maria Lazo, Tami Ramos, Nicola Ritter
Russell T Warne
This article describes the statistical methods used in quantitative and mixed methods articles between 2006 and 2010 in five gifted education research journals. Results indicate that the most commonly used statistical methods are means (85.9% of articles), standard deviations (77.8%), Pearson’s r (47.8%), χ2 (32.2%), ANOVA (30.7%), t tests (30.0%), and MANOVA (23.0%). Approximately half (53.3%) of the articles included reliability reports for the data at hand; Cronbach’s alpha was the most commonly reported measure of reliability (41.5%). Some discussions of best statistical practice and implications for the field of gifted education are included.
Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne
Managing Clustered Data Using Hierarchical Linear Modeling, Russell Warne
Russell T Warne
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 assumption and lead to correct analysis of data, yet it is rarely used in nutrition research. The purpose of this viewpoint is to illustrate the benefits of hierarchical linear modeling within a nutrition research context.