Prerequisites: Biostat 601, 602, 650 and 651 or equivalents
Advisory Prerequisites: Biostat 682 or Biostat 675
Description: Healthy People initiatives over the past several decades have been developed to eliminate health disparities. The objective of this course is to consider several statistical methodological issues in assessing and understanding the reasonings behind health disparities. There is a strong need for bringing together a set of statistical methods to address design, measurement and analysis tuned to health disparity research.
Learning Objectives: .1. Understand historical perspectives on health disparities and determinants of health
2. Understand various measures of health disparity and methods for constructing inferences about them
3. Understand methods for analyzing data from complex surveys
4. Understand methods for assessing psychometric properties of measurements used in health disparity research across subpopulations through measurement error and Item response theory modeling
5. Understand statistical techniques to assess the reasons for health disparity using regression, propensity score and causal inferential techniques
6. Understand small area/domain estimation techniques to understand geographical variation in health disparities
Advisory Prerequisites: Strong quantitative background. Such as Biostat 601, Biostat 602, Biostat 650, and Biostat 651 or equivalents for biostatistics students and Biostat 512, Biostat 521, Biostat 522 and Biostat 523 or equivalents for non-biostatistics students
Description: Tracking and understanding the reasons for health disparity due to social, economic, and environmental disadvantages, using appropriate design, measurement, and analytical techniques, is important for developing evidence-based strategies to alleviate hardships. This course covers several statistical methodological issues useful in health disparity research.
Learning Objectives: Understand historical perspectives on health disparities and determinants of health
Understand various measures of health disparity and methods for constructing inferences about them
Understand methods for analyzing data from complex surveys
Understand methods for assessing psychometric properties of measurements used in health disparity research across subpopulations through measurement error and Item response theory modeling
Understand statistical techniques to assess the reasons for health disparity using regression, propensity score and causal inferential techniques
Prerequisites: STATS 250 or STATS 280 or DATASCI 306 or PSYCH 303 or SOC 310
Advisory Prerequisites: PUBHLTH 383
Description: This course introduces students to a systematic and practical process for a public health and biomedical research addressing seven areas: (1) Development of research hypothesis (2) Choice of appropriate measurement; (3) Design of a study (4) Conduct of the study (5) Exploratory or preliminary analysis of data (6) Final analysis using statistical models and (7) Dissemination of the results. Data set from real studies using four different designs, (1) Randomized Experiment (2) Case-Control study (3) Cohort study and (4) Sample Survey will be used.
Learning Objectives: Learn the design and implementation of four major data collection approaches used in research: Randomized experiments, Case-Control and Cohort studies and Sample Surveys
Learn to analyze data from randomized experiments, case-control and cohort designs and sample surveys
Learn proper communication of results of the analysis from randomized experiments, case-control and cohort studies, and sample surveys.
Learn R-programming language to analyze data from randomized experiments, case-control and cohort studies, and sample surveys.
