Prerequisites
HS 851, or equivalent, instructor may review syllabi of previously
taken courses (past 5 years) and/or require a test to assess the
equivalence of the student background, as necessary.
Course Description
This is a general linear modeling course, building on HS 851, focusing on
commonly employed scientific computing techniques used in health sciences.
The primary aim of the course is to provide students with the necessary skills
to determine appropriate use, carry out, and interpret general linear modeling.
Statistical software will be used to manipulate data, fit models and perform
model diagnostics.
Objectives
Students will learn how to:
- Compare and contrast advanced statistical concepts, grasp model assumptions/limitations and apply them for quantitative analyses in healthcare research
- Apply multivariate statistical modeling enabling consistency between research questions and selected advanced statistical analyses
- Critique and select appropriate advanced statistical linear models for defined healthcare issues
- Conduct multivariate statistical analyses, such as multidimensional chi squares, logistic regression, principal components analysis, survival analysis, repeated measures ANOVA, MANOVA, MANCOVA, linear mixed models, hierarchical linear models.
Examples of Topics Covered
- MLR Regression
- GLM
- ANOVA
- ANCOVA
- MANOVA
- MANCOVA
- Repeated measures ANOVA
- partial) correlation
- Time series analysis
- Fixed, randomized and mixed models
- Hierarchical Linear Models
- Mixture modeling
- Surveys
- Longitudinal data
- Generalized Estimating Equations (GEE) models
- Model Fitting and Model Quality (KS-test)
- Common mistakes and misconceptions in using probability and statistics, identifying potential assumption violations, and avoiding them.
Teaching and Learning Methods
This course meets weekly four times on campus however, as necessary,
blended instructional techniques will be employed to accommodate student and
program constrains. Synchronous web-streaming of lectures/labs and asynchronous
virtual office hour forums will be supported. Assignments will be announced on
the web and will be electronically collected, graded and recorded. A variety of
teaching methods will be used including lecture, Journal Club, discussion, small
group work, and guest presentation.
HS852 is a 4 credit hour course (3 lectures + 1 lab/discussion).
Assignments and Evaluation Methods
- 40% Homework Projects
- 30% Midterm Exam
- 30% Final Paper