Iranian Journal of

In epidemiologic studies, the measurement of characteristics of interest is almost always subject to random measurement error. This error and its effects are usually overlooked by researchers. One of its effects is a widespread statistical phenomenon that is well known as regression to the mean. This phenomenon occurs whenever an extreme group of people is selected from a population based on their measurements of a variable. If a second measurement is taken in this group, the mean of the second measurement will be closer to the mean of the population.  In interventional studies, this increase (decrease) might be regarded as the effect of intervention, when in fact it has had no effect. Ignoring regression to the mean will lead to the erroneous conclusions and interpretation of the results of epidemiologic studies and affects the decisions in evidence-based medicine and planning for preventive and public health measures. This paper highlights the importance of this problem and its effects in epidemiologic studies and the ways to avoid it.

Case-Cohort and nested case-control designs are the most well-known and cost-effective derivatives of prospective studies. Due to the popularity of these designs in recent years, the aim of this study is to provide a comprehensive and up-to-date description of them with respect to methodological issues such as sampling scheme, effect measure estimation, and analysis strategies. Overall, random sampling of controls in case-cohort and matching for time in nested design are considered their hallmarks. Eventually, decision on a better design depends on study objectives, sub-cohort selection, case and control determination, and method of data collection. It should be kept in mind that any particular study requires unique elaboration and delicate examination to choose from the designs.