Prerequisites: Biostat 651 and Biostat 695 or Perm. Instr.
Description: Probability models for two-way tables; multi-factor, multi-response framework; product multinomial distribution theory; Taylor series estimates of variance, weighted least squares and Wald statistics; constraint equations; models for characterizing interactions; step-wise variable selection; factorial designs with multinomial responses; repeated measurement experiments; log-linear models; paired-choice and bioassay experiments; life-table models.
Advisory Prerequisites: PUBHLTH 383 and familiarity with R software
Description: PUBHLTH 375 provides an introduction to the quantitative skills required to analyze health data in applied public health settings. Emphasizing a hands-on learning approach that guides students through the lifecycle of a public health data project, students will develop conceptual foundations and practical techniques needed to work with real-world health data.
Learning Objectives: • Learn, explain, and implement the requirements of conduct a public health study involving human subjects, such as the preparation of Informed-Consent Form.
• Learn, explain and conduct the design and implementation of public health study design to control confounding factors such as randomization and propensity score matching.
• Learn and practice the database management and data privacy protection in the process of data sharing.
• Learn and exercise skills of identifying and handling abnormal data cases as part of data cleaning.
• Learn, practice and assess strategies of handling missing observations.
• Learn and perform the evaluation of statistical model performance.
• Learn, utilize, and implement R-programming language to analyze observational study data and interpret analysis results.
• Learn and illustrate the communication of statistical analysis reports to the public.
