Application of the Method of Variance Analysis in Small Sample Statistics in Biomedical Research

In some areas of physiology (for example, space physiology), researchers have to deal with small samples, which makes it impossible to use classical data analysis methods and requires other approaches. Small samples are characterized by an increased influence of individual characteristics of a specific organism on the nature of the adaptation process. In this regard, a relevant task is to separate the effect of the influencing factor and individual reactions. We propose a new approach to the small sample data analysis using the example of adaptive changes in the cardiovascular system (CVS) in women under reproducing the effects of microgravity in a 5-day dry immersion (DI). Changes in the cardiovascular system were assessed using indicators reflecting hemodynamics and autonomic modulating effects on the heart rhythm. The aim of the work was to identify indicators reflecting the influencing factor effect, as well as indicators reflecting the individual characteristics of the test subjects in the experimental sample. For this purpose, our data analysis employed a methodological approach based on analysis of variance (ANOVA). As a result, we conducted a comprehensive analysis of the small sample data with a statistically justified separation of the studied factor influence and the subject individual reactions, and also identified specific individuals influencing the homogeneity of the entire sample. The presented approach allows, at the initial stage of analysis, to select those indicators that reflect the impact of the factor being studied and, accordingly, meet the set goals, while excluding indicators in which the contribution of individual characteristics is so great that it makes them inappropriate for consideration in the current study.

small sample, analysis of variance, dry immersion, individual characteristics, cardiovascular system