Statistics Question
In this assignment, you will be working with the Framingham Study data to answer the
research question, is high blood pressure associated with risk of death? Follow the
steps below. Submit your responses to the questions below, as well as your SAS log, via
Canvas.
Complete the following steps.
Step 1 (4 points): Import frmgham2.sas7bdat file, examine the meta data and first 10
observations of the data file. Subset the dataset to only include observations where
PERIOD=1. Run a PROC FREQ to examine the frequencies of data for Death (DEATH),
Incident MI or Stroke (CVD), Sex (SEX), and Anti-Hypertensive Meds (BPMEDS). Run a
PROC MEANS to examine data for Age at exam (AGE), systolic blood pressure (SYSBP)
and diastolic blood pressure (DIABP).
Step 2 (3 points): Create a binary high blood pressure variable where
high blood pressure is defined as systolic blood pressure ?130 mm Hg
OR diastolic blood pressure ?80 mm Hg. Run a PROC FREQ to examine the
prevalence of high blood pressure in the sample.
Step 3 (4 points): Create a 2×2 table comparing your newly created high blood pressure
variable against the outcome of death and then run a PROC LOGISTIC statement to
compute the unadjusted odds ratio and 95% confidence interval for this relationship.
Interpret the odds ratio. Provide a one sentence interpretation of the association
between high blood pressure and deth.
Step 4 (3 points): Consider the role of Age in the association you tested in Step 3.
Determine whether you should consider age as a confounder, effect modifier or
mediator in this association. If you determine age to be a confounder, then estimate and
present age-adjusted odds ratios. If you determine age to be an effect modifier, then
estimate and present age-stratified odds ratios. If you determine age to be a mediator, it
should not be included in your multivariable regression model. Provide 1-2 sentence
rationale for your determination as well as a one sentence interpretation of the
association between high blood pressure and death.
Step 5 (3 points): Consider the role of Sex in the model you tested in Step 3. Determine
whether you should consider sex a confounder, effect modifier or mediator in this
association. If you determine sex to be a confounder, then estimate and present sex-
adjusted odds ratios. If you determine sex to be an effect modifier, then estimate and
present sex-stratified odds ratios. If you determine sex to be a mediator, it should not be
included in your multivariable regression model. Provide 1-2 sentence rationale for your
determination as well as a one sentence interpretation of the association between high
blood pressure and death.
Step 6 (3 points): Consider the role of anti-hypertensive medication use in the model you
tested in Step 5. Determine whether anti-hypertensive medication use serves as a
confounder, effect modifier or mediator in this association and present the appropriate
analyses. Provide a 1-2 sentence rationale for your determination as well as a one
sentence interpretation of the association between high blood pressure and death.
Step 7 (Bonus + 5): Re-run your regression models from prior steps but estimate risk
ratios (and 95% confidence intervals) rather than odds ratios. Describe how the risk
ratios compare to your previously estimated odds ratios.
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