Reference no: EM133770803
Assignment: Biostatistics using R Studio & HersDataSet
Answer each question using the Heart and Estrogen/Progestin Study (HERS), a clinical trial of hormone therapy for prevention of recurrent heart attacks and deaths among 2,763 post-menopausal women with existing coronary heart disease (Hulley et al., 1998). Copy and paste your completed syntax into this assignment for complete credit.
Provide univariate statistics for systolic blood pressure (sbp), diabetes, race/ethnicity (raceth), age, smoking, weight-height-ratio (WHR1), glucose, and total cholesterol (tchol).
Provide bivariate statistics for the associations for systolic blood pressure (sbp) and diabetes with race/ethnicity (raceth), age, smoking, weight-height-ratio (WHR1), glucose, and total cholesterol (tchol). Provide an interpretation for statistically significant associations.
1. Conduct a multiple linear regression with systolic blood pressure as the outcome and race/ethnicity (raceth), age, smoking, weight-height-ratio (WHR1), glucose, and total cholesterol (tchol) as the explanatory variables.
2. Present the results in a table (including unstandardized and standardized coefficients, standard errors, and p-values, with model fit information in the foot notes. In order to receive all points, the table needs to be publication quality.
3. Provide an explanation of the results with special attention to any significant explanatory variables.
Conduct a multiple logistic regression with presences/absence of diabetes as the outcome and race/ethnicity (raceth), age, smoking, weight-height-ratio (WHR1), glucose, and total cholesterol (tchol) as the explanatory variables. *Hint you will need to recode presence or absence of diabetes into a numeric binary (1/0) outcome.
1. Present the results in a table (odds ratios, confidence intervals, and p-values, with model fit information in the foot notes). In order to receive all points, the table needs to be publication quality.
2. Provide an explanation of the results with special attention to any significant explanatory variables.
3. After reviewing the results, how do you think these analyses could have been improved to better situate the results in a health equity framework or test for cross-cultural differences? Be sure to reflect on both new potential analyses and missing explanatory variables.