Relative marginal and summary effects in the analysis of longitudinal data

The purpose of this research is to demonstrate two nonparametric relative effects with an analysis for longitudinal data with application to liver cancer studies. Relative marginal effects and relative summary effects are introduced and the hypotheses are formulated in terms of either the distribution functions themselves or the corresponding relative effects. Missing observations are especially common in studies and two strategies for addressing this problem are compared: complete case analysis and last observation carried forward. They are used to test the efficacy of green tea polyphenols (GTP) in reducing the level of aflatoxin B1 (AFB1) in blood, 8-hydroxy-2’-deoxyguanosine (8-OHdG) in urine samples and test the effect of green tea in increasing the levels of active components of GTP: -epicatechine (EC) and -epigallocatechin (EGC) in urine. The results of this research could be a way to improve chemoprevention in liver cancer studies. In last part of the paper, we give an example of Cortisol Concentration in Plasma to describe how summary variables are computed.