Multistage regression, a novel method for making better predictions from your efficacy data.

Multistage regression is rarely used in therapeutic research, despite the multistage pattern of many medical conditions. Using an example of an efficacy study of a new laxative, path analysis and the 2-stage least square method were compared with standard linear regression. Standard linear regression showed a significant effect of the predictor "noncompliance" on drug efficacy at P=0.

Clinical research: a novel approach to regression substitution for handling missing data.

In clinical research, missing data are common. Imputed data are not real data but constructed values that should increase the sensitivity of testing. Regression substitution for the purpose of data imputation often did not provide a better sensitivity than did other methods.

Fuzzy modeling, a novel approach to studying pharmacodynamics.

Fuzzy logic can handle questions to which the answers may be "yes" at one time and "no" at the other, or may be partially true and untrue. Pharmacodynamic data deal with questions such as "Does a patient respond to a particular drug dose or not," or "Does a drug cause the same effects at the same time in the same subject or not." Such questions are typically of a fuzzy nature and might, therefore, benefit from an analysis based on fuzzy logic.