Introduction to Statistical Computing

1
Introduction to Statistical Computing

• Methods in Clinical Research
• July 2000

2
Health Service Cost Review Commission (HSCRC) Data

• Discharge data on patients who underwent
  abdominal aortic surgery in one of 52 non-federal
  hospitals in MD.
• Data also obtained on the ICU organizational
  characteristics for hospitals in which patients
  were treated
• 1994-1996
• Subset includes 490 patients

3
Types of Data Collected

• Outcomes (e.g. length of stay, mortality)
• Patient Characteristics (e.g. age, race)
• Comorbid Diseases (e.g. dementia, diabetes)
• Complications (e.g.aspiration, septicemia)
• Surgeon and Hospital Volume
• Organizational Characteristics (e.g.
  nurse- patient ratio, frequency of morbidity
  review)

4
Motivating Question

• How are patient characteristics related to
• length of stay (los)?
• total charges (totchg)?
• days in ICU (icuday)?
• mortality (death)?

5
What variables do we have to work with?

• describe
• inspect

6
What are the distributions of the outcomes we are
considering?

• summarize
• centile
• hist
• graph
• tab
• dotplot
• stem

7
What does the patient population look like?

• age (age)
• race (nonwhite)
• gender (sex)

8
Do the outcomes differ by gender?

• boxplot
• graph
• table
• by sex summarize

9
Do the outcomes differ by race?

• boxplot
• histo
• table
• by nonwhite summarize

10
Generating New Variables

• Length of Stay (los) appears skewed
• We want to normalize it by taking the natural
  log.
• How do we make a new variable log(los)?
• generate logloslog(los)
• or
• gen logloslog(los)

11
Generating New Variables

• What if we want to create a categorical variable
  of length of stay short versus long stay?
• gen longstay1 if losgt10
• replace longstay0 if loslt10
• or
• gen longstaycond(losgt10,1,0)
• replace longstay. if los.