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index.qmd
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---
title: "Course Materials for PHC 6099: 'R Computing for Health Sciences'"
author:
- name: Gabriel Odom
affiliations:
- Florida International University
- Robert Stempel College of Public Health and Social Work
toc: true
number-sections: true
format: html
embed-resources: false
---
## Source Code for PHC6099 Course Notes
This material is for the course "R Computing for Health Sciences". The course notes are published here: <https://gabrielodom.github.io/PHC6099_rBiostat/>
### Topics
The chapters are:
1. Exploring Data
- `ggplot2::` mosaic plots, histograms, and violin plots
- `ggplot2::` scatterplots and facets
<!-- - `rayshader::` -->
- `skimr::`
- `table1::`
- `gtsummary::`
2. One-Sample Tests
- $Z$-test
- Paired $t$-test
- Paired Wilcoxon test
- Transformations to Normality
- McNemar's Test
- Fisher's Exact Test
- Chi-Square Goodness of Fit
- Bootstrapped Confidence Intervals
3. Two-Sample Tests
- $t$-test
- Welch's $t$-test
- Mann-Whitney $U$ test
- Cochran's $Q$ test
- $\chi^2$ Test for Independence
4. ANOVA and Linear Regression
- One-Way ANOVA
- Two-way ANOVA
- Welch's ANOVA
- Kruskal-Wallace Test
- Tukey HSD Post-Hoc Test
- Repeated Measures ANOVA
- Random Intercept Models
- Correlation Matrices and Covariances
- Multiple Regression (linear)
- Polynomial regression
5. Generalized Linear Models
- Generalized Linear Models: Binary
- Generalized Linear Models: Ordered
- Generalized Linear Models: Count (Poisson)
- Generalized Linear Models: Count (Negative Binomial)
6. Special Topics
- Linear Mixed Effects Models
- Structural Equation Models
- Cox Proportional Hazards Regression
- (TBD) Multivariate Methods for Genetics/Genomics
- Ridge, LASSO, and Elastic Net Regression
7. Power Calculations (in progress)
### Lesson Outline
This is a shell of a lesson that can be copied and pasted for new lessons (or to edit and clean up existing lessons). If you copy this shell, then change all the headings from level 4 to 2. Replace \<the method\> with the name of your method, or its abbreviation. The file `lessons/00_lesson_template.qmd` has a `.qmd` template with these sections.
#### Introduction to \<the method\>
#### Mathematical definition of \<the method\>
#### Data source and description
#### Cleaning the data to create a model data frame
#### Assumptions of \<the method\>
#### Checking the assumptions with plots
#### Code to run \<the method\>
#### Code output
#### Brief interpretation of the output