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Track 1: Applied Biostatistics – Core Curriculum
Track 1 is ideal for participants who are interested in an abbreviated curriculum and shorter program commitment.
Track 1 participants have access to the following 5 units of content, and are required to complete units 2-5 in order to earn a certificate of completion.
A certificate of completion for Track 1 will read: [Name] has fulfilled the requirements of Harvard Catalyst’s Applied Biostatistics: Core Curriculum program, including completing four units of content.
- Math boot camp
- Data presentation
- Basics of probability
- Basics of statistical software
- One and two-sample t-tests
- ANOVA
- Nonparametrics
- Analysis of proportions
- Power and sample size
- Additional power calculations
- Study designs for clinical research
- Advanced topics in clinical trials
- Factorial designs
- Multiple linear regression
- Regression diagnostics
- Multiple linear regression
- Partial F-tests
- Interpretation of interaction terms
- Stepwise selection/alternative model selection approaches
- Logistic regression
- Additional topics for logistic regression
- Survival analysis
- Cox proportional hazards model
- Cox proportional hazards regression: Assessment of assumptions
Track 2: Applied Biostatistics – Core Curriculum and Advanced Topics
Track 2 is ideal for learners who are interested in a more comprehensive program, with the opportunity to select from more advanced topics at the end of the program.
Track 2 participants have access to the following 9 units of content, and are required to complete units 2-5, as well as two additional units from units 6, 7, 8, or 9 in order to earn a certificate of completion.
A certificate of completion for Track 1 will read: [Name] has fulfilled the requirements of Harvard Catalyst’s Applied Biostatistics: Core Curriculum and Advanced Topics program, including completing four units of foundational content and at least two units of advanced content.
- Math boot camp
- Data presentation
- Basics of probability
- Basics of statistical software
- One and two-sample t-tests
- ANOVA
- Nonparametrics
- Analysis of proportions
- Power and sample size
- Additional power calculations
- Study designs for clinical research
- Advanced topics in clinical trials
- Factorial designs
- Multiple linear regression
- Regression diagnostics
- Multiple linear regression
- Partial F-tests
- Interpretation of interaction terms
- Stepwise selection/alternative model selection approaches
- Logistic regression
- Additional topics for logistic regression
- Survival analysis
- Cox proportional hazards model
- Cox proportional hazards regression: Assessment of assumptions
- Introduction to longitudinal data
- Longitudinal analysis with random effects
- Additional topics in longitudinal data analysis
- Multilevel models
- Repeated measures analysis with dichotomous outcomes
- Introduction to counterfactuals and DAGs
- Propensity score methods for causal inference
- Inverse probability weighting for causal inference
- Standardization for causal inference and comparison of approaches
- Introduction to prediction modeling
- Stepwise selection and lasso
- Additional topics for prediction models with regression
- Other approaches for prediction modeling
- Missing data
- Meta-analysis
- Multiple comparisons
- Unsupervised learning