Revisiting field experimentation: field notes for the future

Field experiments in the social sciences were increasingly used in the 20th century. This article briefly reviews some important lessons in design, analysis, and theory of field experiments emerging from that experience. Topics include the importance of ensuring that selection into experiments and assignment to conditions occurs properly, how to prevent and analyze attrition, the need to attend to power and effect size, how to measure and take partial treatment implementation into account in analyses, modern analyses of quasi-experimental and multilevel data, Rubin's model, and the role of internal and external validity. The article ends with observations on the computer revolution in methodology and statistics, convergences in theory and methods across disciplines, the need for an empirical program of methodological research, the key problem of selection bias, and the inevitability of increased specialization in field experimentation in the years to come.