Training
Here is a list of training sessions, workshops, or courses I have delivered or attended:
Handling Missing Data: A practical Introduction to techniques and methods
Type: Workshop Delivered
Date: May 13th 2025
Location: Edinburgh Futures Institute, Edinburgh, Scotland
Description: This training event begins with a gentle introduction into handling missing data theory, covering the necessities to engage appropriately with the practical elements of the course. By the end of the session attendees will have a solid familiarity with the different types of missingness and how each may cause potential issues surrounding bias within statistical analysis.
- View Training Powerpoint
- View Example Dataset #1
- View Example Dataset #2
- View Example Dataset #3
- View Stata Session #1
- View Stata Session #2
- View Stata Session #3
- View Stata Session #4
- View R Session #1
- View R Session #2
- View R Session #3
- View R Session #4
- View Jupyter Notebook #1 - Missing Data Methods using R, Stata, and Python
- View Jupyter Notebook #2 - Simulation Comparing Missing Data Methods
- View Reference List
Survey and Questionnaire Construction: the Shiny Package in R
Type: Workshop Delivered
Date: November 24th 2024
Location: Edinburgh Futures Institute, Edinburgh, Scotland
Description: This training event will cover teaching users about the Shiny package within the R environment. The Shiny package allows users to create their own applications free of charge and host them online. This training will focus on a key aspect of app creation – creating one’s own survey/questionnaire that can be used in their own research agenda.
- View Training Materials
- View Example Code #1
- View Example Code #2
- View Example Code #3
- View Example Code #4
- View Example Code #5
- View Example Code #6
- View Example Code #7
- View Example Code #8
- View Example .css Code
- View Example .js Code
- View PowerPoint
Introduction to Statistics in Stata
Type: Training Materials
Date: September 1st 2023
Location: Edinburgh, Scotland
Description: These files will provide a holistic undergraduate level understanding of quantiative methods.
- View Intro to Quantitative Statistics
- View Intro to Advanced Quantitative Statistics
- View Example Dataset
- View Example Code #1
- View Example Code #2
- View Example Code #3