Introduction to Basic Statistics for Clinical Research

1
Introduction to Basic Statistics for Clinical
Research
2
Learning the Language

• Concept of Sampling
• Variable types
• Categorical (qualitative nominal)
• Ordinal
• Numerical (continuous interval ratio)
• Independent vs. Correlated Data
• Parametric vs. Non-parametric

3
Learning the Language

• Study Design
• Sampling Strategy
• Analysis Types
• Discrete vs. Time-dependent (survival)
• Logistic vs Linear Regression
• Model Building
• Interactions

4
Sample Size

• The number of subjects required in a study to
  achieve statistical significance, given a
  number of a priori assumptions.

5
Power Considerations The assumptions

• Control value or rate
• Effect size
• dependent on parameter of interest
• best to have pilot data
• Significance level (?)
• 1-tailed or 2-tailed testing
• Power (1-?)
• Confounders
• Non-compliance
• Cross-overs
• Drop Ins
• Drop Outs
• Lost to follow up

6
Standards for Effect Size

• Small -0.2
• Medium - 0.5
• Large -0.80
• only rough guidelines- small medium and large are
  subject dependent

7
Adequacy of Sample Size Matters
8
Effect of trial size on results 24 trials of
?-blockade vs. Placebo
9
Ways to Reduce Required Sample Size

• Higher Event Rate
• High risk populations
• Composite Endpoints
• Larger Effect Size
• Lower power
• Larger ?
• 1-tailed or 2
• Change analysis type
• Time dependent

10
Sample size planning

• How much money do you have?
• How much time to you have?
• How many patients of that specific type can you
  expect to reasonably get?
• What sample size and study design can I afford?

11
The words to use to describe this

• The study was designed to have gt80 power to
  detect an effect size of gt20 with a 2-tailed
  significance level of 0.05, with a planned sample
  size of 400 participants in each group.

12
Suggested Reading

• Reference texts
• Dawson-Saunders B, Trapp RG. Basic and Clinical
  Biostatistics, Appleton and Lange, Norwalk, CT,
  2nd Edition, 1994.
• Sackett DL. Clinical Epidemiology a basic
  science for clinical medicine. Little Brown,
  Boston, MA, 2nd Edition, 1991.
• Selected papers
• Bias
• Sackett DL. Bias in analytic research. J Chron
  Dis 1979 3251-63
• Power
• Moher D, Dulberg CS, Wells GA. Statistical power,
  sample size, and their reporting in randomized
  controlled trials. JAMA 1994 272 122-4.
• Subgroup anlayses
• Assmann SF, Pocock SJ, Enos LE, Kasten LE.
  Subgroup analysis and other (mis)use of baseline
  data in clinical trials. Lancet 2000 355
  1064-1069.
• Yusuf S, Wittes J, Probstfield J, Tyroler HA.
  Analysis and interpretation of treatment effects
  in subgroups of patients in randomized clinical
  trials. JAMA 1991 266 93-98.