Examine and explore the “data.xlsx” file and the associated data dictionary (“Data Dictionar.xlsx”).
CASE STUDY ASSIGNMENT
For this case study assignment, you will work in groups of one to three people to:
- Examine and explore the “data.xlsx” file and the associated data dictionary (“Data Dictionar.xlsx”).
- Come up with a research question and hypothesis that you would like to test using this data.
- Test your hypothesis using “R”
- Your analysis should include descriptive statistics for all variables included in your analysis, bivariate tests between all explanatory variables and the outcome of interest, and a multivariable model that tests your primary research question while also controlling for confounders.
- Note: You might be conducting an “explanatory model” rather than a confounding model. Explanatory models are usually used to understand the variables associated with a single outcome rather than test whether a specific variable is associated with the outcome.
- Your R code should be extremely well documented (i.e., lots of comments to explain what each line and section are for)
- Your variables should be appropriately recoded.
- Your code should be free from error.
- Your results should be properly interpreted.
- Note: Make sure that you look up how to interpret the results from your analysis.
- Write an academic paper using the provided template and instructions (“Template.docx”).
- Double spaced
- Approximately 15 pages including title page, abstract, body of text, references, tables, and figures.
- Use IMRaD format (Introduction, Methods, Results, and Discussion)
- Results should, at minimum, provide
- 1 table providing descriptive statics for each variable included in your analysis.
- 1 table providing bivariate significance tests.
- 1 table providing a multivariable model.
- 1 figure that highlights an important component of your analysis.
- Use Vancouver Stylereferences and in-text citations.
- You should cite at least 5-10 external references from academic and governmental sources. More citations may be needed to contextualize your study and results as all claims should be well-supported.
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