Statistical power, role

Statistics plays a major role in the design of the clinical trial. The groups or subgroups to be studied, the frequencies, dosages, and the markers to monitor drug efficacy are all important factors to consider. The statistical analysis provides the tool to demonstrate, at a certain confidence level, whether the drug is effective. This is normally reported in the form of a statistical power test, analyzing the Type I and Type II errors. 

Progress in the theoretical description of reaction rates in solution of course correlates strongly with that in other theoretical disciplines, in particular those which have profited most from the enonnous advances in computing power such as quantum chemistry and equilibrium as well as non-equilibrium statistical mechanics of liquid solutions where Monte Carlo and molecular dynamics simulations in many cases have taken on the traditional role of experunents, as they allow the detailed investigation of the influence of intra- and intemiolecular potential parameters on the microscopic dynamics not accessible to measurements in the laboratory. No attempt, however, will be made here to address these areas in more than a cursory way, and the interested reader is referred to the corresponding chapters of the encyclopedia. 

Understanding the role of surface roughness in mixed lubrication is a first step toward the microscopic study of tribology. It has been an effort for more than 30 years, starting from statistic models, but it is the deterministic approach that provides a powerful means to explore the tribological events occurring at the micrometre scale. 

Figure 21.3 Modeling and simulation in the general context of the study of xenobiot-ics. The network of signals and regulatory pathways, sources of variability, and multistep regulation that are involved in this problem is shown together with its main components. It is important to realize how between-subject and between-event variation must be addressed in a model of the system that is not purely structural, but also statistical. The power of model-based data analysis is to elucidate the (main) subsystems and their putative role in overall regulation, at a variety of life stages, species, and functional (cell to organismal) levels. Images have been selected for illustrative purposes only. See color plate.

SAS has always had and will maintain a central role in the data management, analysis, and reporting of clinical trial data. Because of the strong suite of SAS statistical procedures and the power of Base SAS programming, SAS remains a favorite of statisticians for the analysis of clinical trial data. Several companies have built their clinical trial data management and statistical analysis systems entirely with SAS software. More recently, SAS has offered SAS Drug Development as an industry solution that provides a comprehensive clinical trial analysis and reporting environment compliant with 21 CRF-Part 11. 

New techniques for data analysis abound in statistical literature. GAM is a powerful tool technique, and a full historical account of GAM with ample references can be found in the research monograph of Hastie and Tibshirani (15). GAM is closer to a reparameterization of the model than a reexpression of the response. Once an additive model is fitted to the data, one can plot their p coordinate functions separately to examine the roles of predictors in modeling response. With the GAM approach the dependence of a parameter (P) on covariates (predictors) Xi,..., Xp are modeled. Usually, the multiple linear regression (MLR) approach is the method of choice for this type of problem. The MLR model is expressed in the following form ... 

Genetic predisposition may also influence the development of drug-induced aplastic anemia. Studies in animals and a case report of chloramphenicol-induced aplastic anemia in identical twins suggest a genetic predisposition to the development of drug-induced aplastic anemia. " Furthermore, pharmacogenetic research that focuses on patients who may be slow or normal metabolizers of drugs may increase the clinician s ability to predict the development of aplastic anemia. Initial case-control studies have not had the power necessary to identify a statistical difference between controls and cases, bnt continued research may establish the role of altered metabolism in this population. ... 

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