Your task:
Using the HTML formatted output, apply concepts of basic epidemiology and descriptive and analytic biostatistics to address the questions that follow. Students are invited to run the code as well and generate the same output using the .rmd R Markdown file, but this is not required. Students who choose to run the R Markdown code in R Studio must save the .rmd file and the Uganda Malaria HIV Data.xlsx file in the same directory! For example, if you would like your R Studio working directory to be your Desktop, you must save all files to Desktop. You can choose your own location for the working directory, but the .rmd file and the .xlsx file must be in the same location. Additionally, for the student interested in running the program in R Studio, one of the final research questions requires saving and loading another data frame, ugandarct.RData. In following the assignment as written, students will note the appropriate point for loading this data frame.
A. Incidence Rates
1. Malaria Incidence Rate:
Your biostatistician has calculated a malaria incidence rate of 65.7/1000 person-years(rounded). A Northwestern University MSGH student is collaborating with your team and asks you for assistance in interpreting this value. Share your interpretation. (1 point)
2. HIV Incidence Rate:
The MSGH student asks you why your team is interested in the HIV incidence rate. Share one reason why your team might want to know this rate. (1 point)
3. Death Incidence Rate:
The MSGH student recalls learning about adjusted death rates. While adjusted rates are not reported for this data, the student asks you to share what factor is generally adjusted for in this process and under what circumstances adjusted death rates are likely to be reported. In other words, when do epidemiologists generally require adjusted rates? Share your response. (1 point)
B. QQ Plots
1. Your MSGH student is very interested in recalling the fundamentals of creating and using QQ plots. In planning your response, you review a video explaining QQ plots. The student has the afternoon off and wants to recreate one of the plots by hand as demonstrated in the video. The student asks how many quantiles should be created for our data and if the comparison normal curve should be divided into the same number of quantiles. Next, the student asks how to interpret the plot when the created points do not follow the line. Provide your response to these questions. (1 point)
2. Exhausted by the tedious task of manually creating a QQ plot, the student inquires why the biostatistician would be interested in determining if variables are normally distributed. Specifically, how might this information impact the planned analysis? Provide your response. (1 point)
3. Before the student inquires further, you preemptively review parametric and nonparametric statistical tests. Share one point of comparison and one point of contrast. (1 point)
C. Correlation for Continuous Variables
1. HIV RNA and CD4:
The MSGH student has completed the internship with your team, thanked you for sharing your insight, and leaves you on your own for the next questions. For the HIV infected patients, evaluate the correlation between HIV RNA (viral load) and CD4 cell count ( a measure of immune function). What is the correlation coefficient? Is this association statistically significant? Support your conclusion. How do you interpret this? (1 point)
2. Hemoglobin and BMI:
For all the subjects, evaluate the correlation between hemoglobin (hgb) (measure of anemia) and BMI. Note that your consultant first confirmed the distribution of the BMI variable before proceeding with the analysis. Does the BMI variable appear approximately normally distributed? Does the consultant use a parametric test? What is the correlation coefficient? Is this association statistically significant? Support your conclusion. How do you interpret this? (1 point)
D. Associations for Categorical Variables
1. Condoms and HIV Infection:
Is condom use (dichotomized as EVER/NEVER or YES/NO) associated with HIV infection? Support your conclusion. Report and interpret the relative risk, attributable risk, and number needed to treat. While some of
the programming steps are different from the code created by your biostatistician, you may find this video helpful for interpreting the R output. (1 point)
2. Bed Nets and Malaria Infection:
Is bed net use (dichotomized as EVER/NEVER or YES/NO) associated with malaria infection? Support your conclusion. Report and interpret the relative risk, attributable risk, and number needed to treat. (1 point)
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