1. Medical Estimation
Copyright  2008 by The McGraw-Hill Companies. This material is intended for educational purposes by licensed users of LearningStats. It may not be copied or resold for profit.

2. Questions What is the purpose of the study?
What assumptions must be made?
What is the quality of the data?
What if the estimate is too low? Too high?

3. It pays to consult an expert
Getting the Answer
Expect problems such as outliers, missing values, and incompatible samples. Medical studies usually require careful experimental design to ensure adequate sample sizes and to ensure that the study will actually address the question(s) of interest.
It pays to consult an expert
on such matters.

4. Statistics is not Magic
The scientific aura of statistics may divert attention from more fundamental issues such as:
Goals of the proposed study
Quality of the underlying data
Interpretation and use of the results
But statistics can help structure the dialogue between statistician and client in planning a study.

5. These are just a few examples.
Specialized Tools
Tool
Purpose
Odds ratio, Yule's Q
Analyze of tabulated data or logistic regression coefficients
ROC curves
Show tradeoffs between specificity and sensitivity
Data mining
Find structure in large databases with many potential predictors
Kaplan-Meier plot
Estimate survival function for individuals with censored data
Structural equation modeling
Causal modeling (more general than regression, ANOVA, etc.)
These are just a few examples.

6. The Ubiquitous 2x2 Table Definitions: Sensitivity = a/(a+c)
Specificity = d/(b+d)

7. Odds Ratio Definition:
OR = Odds ratio = {[(a/(a+b)] / [b/(a+b)]} /{[(c/(c+d)] / [d/(c+d)]} = (a/b)/(c/d)
Invariance property:
From these equivalent forms, we see that the odds ratio is the same regardless of row/column order (for calculations, we use the last one):
OR = (a/b)/(c/d) = (a/c)/(b/d) = (d/b)/(c/a) = (d/c)/(b/a) = ad/bc

8. Web Sites to Explore http://www.priory.com/anaes/stat.htm