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GPDI545 - Data Management in R

More and more users are migrating to R for data analysis. Before they can get to the analysis however they need to know how to import data, recode variables, handle missing observations and reshapre their dataset as needed. This workshop teaches many of the skills you will need for data management. Some prior R knowledge is required.

In this workshop, the following topics will be covered:
- Session I: Importing data and recoding variables
- Session II: Merging and reshaping data

Requirements:
Participants will need to bring their own laptop with R (version 3.4 or above) and Rstudio installed. Basic R knowledge is required. To learn how to install R and RStudio, please use the following resources:

Linux: https://youtu.be/YBOpy1WK-bg
Mac OS: https://youtu.be/GFImMj1lMRI
Windows: https://youtu.be/GAGUDL-4aVw

Learning Objectives



In this workshop participants will:
1. Import data from different formats including the SPSS .sav, SAS .sas7bdat and .csv
2. Change variable format
3. Recode variables into new categories
4. Estimate the number of missing observations in data
5. Merge datasets
6. Concatenate datasets
7. Save datasets

Leaders Information


This workshop is led by Yara Abu Awad, ScD, a Harvard University trained epidemiologist with expertise analyzing big data by applying causal inference methods and machine learning techniques using R. She is currently at the Department of Psychology investigating the impact of stress on obesity among children, the impact of parental expectations on children’s sleep quality and the impact of social inequalities on children’s health.

This workshop is not scheduled at this time.
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