The new biostatistics of resampling.
The statistical techniques reported in medical journals are often poorly understood and misused by researchers, and difficult for readers to comprehend. Even the relatively simple t test embodies an intricate collection of mathematical formulas such as the Normal approximation, with unintuitive elements such as pi and e. The researcher must consult a body of rules indicating whether a technique is applicable or inapplicable. If he or she does select a sound method and use it correctly, its mathematical complexity will still leave most readers in the dark. In most situations the resampling approach is at least as efficient as the formulaic method. It is transparently clear to the researcher and reader, and it protects the researcher from using the wrong formulaic technique. In this paper we will define the four steps in the resampling method, compare this procedure with standard formulaic treatment of the same data, and discuss the advantages of the resampling approach.
Simon
J L
JL
College of Business and Management, University of Maryland, College Park 20742.
Bruce
P
P
D000328:Adult; D001699:Biometry / Q000379:methods*; D002784:Cholesterol / Q000097:blood; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D003863:Depression / Q000628:therapy; D006801:Humans; D007230:Infant, Low Birth Weight; D007231:Infant, Newborn; D008297:Male; D015233:Models, Statistical; D009203:Myocardial Infarction / Q000097:blood; D012107:Research Design; D012306:Risk; D012494:Sampling Studies
D002784:Cholesterol