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data550-group1-midterm's Introduction

data-550-group1-midterm

Group 1's Midterm Project for DATA 550


Objective

In this project, we will estimate the effect of chronic conditions (specifically: diabetes, COPD, asthma, immune suppression, CVD, and obesity) on hospitalization and death of COVID-19 patients in Mexico.

Source: https://datos.gob.mx/busca/dataset/informacion-referente-a-casos-covid-19-en-mexico


Team Members

  • Pragati Prasad
  • Jess Chan
  • Kanak Belgaum
  • Ariana Parquette
  • Sim Fan

Code Description

code/01_data_cleaning.R

  • run with make data
  • inputs raw data from raw_data/ folder
    • raw_data/covid_sub.csv
  • Handle missing data
  • Set outcome variables to binary
  • Change dependent variables (chronic conditions) to either binary or categorical with reference groups
  • outputs cleaned/final dataset to output/ folder
    • output/data_cleaned.rds

code/02_descriptive_stat.R

  • run with make descriptive
  • inputs cleaned dataset from output/ folder
    • output/data_cleaned.rds
  • Make table 1 describing population data
  • Histograms of dependent variables (chronic conditions)
  • Scatter plot to visualize distribution of dependent variables (chronic conditions) amongst the patient data
  • outputs all plots and tables to output/ folder
    • output/02_table_one.rds
    • output/02_conditioncount.png
    • output/02_table2.png
    • output/02_heatmap.png

code/03_modeling.R

  • run with make regression
  • inputs cleaned dataset from output/ folder
    • output/data_cleaned.rds
  • runs logistic regression models to estimate the effect of chronic conditions on hospitalization and death of COVID-19 patients in Mexico
  • outputs regression models in output folder
    • output/model_1.rds
    • output/model_2.rds
    • output/model_1_results.rds
    • output/model_2_results.rds

code/04_visualization.R

  • run with make visualize
  • inputs regression files from output/ folder
    • output/data_cleaned.rds
    • output/model_1.rds
    • output/model_2.rds
  • Create regression model table
  • Diagnostic plots to evaluate model selection
    • Assess linearity assumption
  • outputs diagnostic plots to output/ folder
    • output/model_1_effects.rds
    • output/model_2_effects.rds

report.Rmd

  • run with make report.html
  • inputs all plots and tables
  • outputs formatted report file

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