A Multilevel Analysis of Life Satisfaction in Central and Eastern Europe

The existence of data hierarchies is neither accidental nor ignorable. Both the group and its members influence and are influenced by the group membership. Ignoring this relationship may lead to ignoring group effects and hence to invalidating many of the traditional techniques of statistical analysis used to investigate the relationships between data. People living within the same country may be more similar to each other than people living in other countries; they share the country economic characteristics, lifestyle, social factors, and health care availability, which may have a collective influence over and above individual circumstances. The degree of satisfaction with life may be determined by factors that may be shaped by the specific country environment. The ability to model such complex relationships comes at a computational cost. Each multi-level software package has a different interface and different capabilities; therefore the choice of which to use is important. Using R and SPSS we develop a multilevel analysis of the level of satisfaction with life in general of individuals from Central and Eastern Europe that are grouped within countries. Our analysis looks at life satisfaction data and discusses the possible influence of country and/ or individual factors.