A clinical trial analyst needs to create a Kaplan-Meier survival plot to visualize the time-to-event data for different treatment groups. Which PROC step should the analyst use, and what is the key statement to differentiate the treatment groups in the graph?

When using PROC REPORT to summarize clinical trials data, you want to add a summary row at the end of each BY group as well as a grand total at the end of the report. Which combination of BREAK and RBREAK statements would correctly achieve this?

You have two SAS datasets, 'baseline' and 'followup', that are supposed to have the same structure and variable attributes. However, discrepancies are suspected. You need to compare the datasets to see if there are any differences in the attributes of the variables. Which PROC COMPARE option would you use to display only those variables that differ, without listing those that match?

Given the following SAS program: `%let treatmentA = Placebo;%let treatmentB = DrugX;%let numSubjects = 50; %macro setGroups(trt1=, trt2=);%let group1 = &trt1;%let group2 = &trt2;%mend; %setGroups(trt1=&treatmentA;, trt2=&treatmentB;)

In a clinical trial, the variable 'TreatmentGroup' indicates whether a patient received the experimental drug (coded as 'Drug') or the placebo (coded as 'Placebo'). You have been tasked with reporting the frequency and percentage of patients in each treatment group. Which SAS procedure would allow you to obtain these specific statistics for categorical data?