Social and Behavioral Sciences Commons^™

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

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

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.

An Introduction To Item Response Theory For Health Behavior Researchers, Russell Warne

Russell T Warne

OBJECTIVE:

To introduce item response theory (IRT) to health behavior researchers by contrasting it with classical test theory and providing an example of IRT in health behavior.

METHOD:

Demonstrate IRT by fitting the 2PL model to substance-use survey data from the Adolescent Health Risk Behavior questionnaire (n=1343 adolescents).

RESULTS:

An IRT 2PL model can produce viable substance use scores that differentiate different levels of substance use, resulting in improved precision and specificity at the respondent level.

CONCLUSION:

IRT is a viable option for health researchers who want to produce high-quality scores for unidimensional constructs. The results from our example-although not …

Does The Normal Curve Accurately Model The Distribution Of Intelligence?, Lindsey R. Godwin, Kyle V. Smith, Russell T. Warne

Russell T Warne