Although findings from animal experiments cannot be directly applied to humans, well-designed animal studies remain powerful tools for advancing scientific knowledge, especially in biomedical fields including aging research. Most applied researchers share the idea with statisticians that statistics is an essential component for successful scientific research. This appreciation is not always clearly reflected in appropriate analysis and interpretation of results in published studies (Olsen, 2003; Williams et al, 1997; Murphy, 2004). Therefore, a brief review of basic statistical concepts and considerations is important not only for the completeness of this comprehensive book but also for quality of research practice. In this chapter, we review some basic statistical concepts, summary statistics, hypothesis testing, and study design considerations. We then discuss statistical methods to test differences in maximum lifespan. Finally, using a maximum lifespan example, we illustrate how to choose an appropriate design and statistical methods.
Our goal is to provide applied researchers on aging with a better understanding of basic statistical concepts to help them communicate more effectively with the statistical support staff who actually conduct the analyses. Therefore, the primary task of this chapter is to provide a general overview of statistical concepts and issues, not to provide a detailed and exhaustive discussion. We will focus on statistical hypothesis testing and statistical methods useful for animal experiments in which, typically, the researcher can control factors that affect the outcomes, but not have to face issues that are common in human clinical trials such as loss to follow-up, missing data, and noncompliance to treatment. Motivated readers looking for more extensive discussions are referred to some excellent texts (Daniel, 1998; Alterman, 1999; Fisher and van Belle, 1993).
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