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Abstract

Finding potent and clinically standardized biomarkers is of utmost importance for early detection of any disease which further helps in developing prevention and cure techniques. Use of statistical techniques becomes inevitable to validate the predictive power of the biomarkers and also to ensure the reproducibility of results. Identification of statistically significant covariates and competing risks is another important aspect of any biostatistical study for understanding disease progression. This paper attempts to review some useful statistical and biostatistical techniques being utilized in the study of dementia, Alzheimer's disease (AD) in particular, and also proposes some potentially reliable techniques which can be helpful in critically examining the complexities involved in brain activities of AD patients and its association with other pathological and physical changes in the patients. This paper concludes by proposing an objective-wise methodological structure for biostatistical analyses of AD.