Search

Study design forms a core component of research, mainly determined by the study objectives, and it in turn further decides the type of statistical analyses to be carried out. Observational studies are devoid of the investigator's control over assignment of a subject to the treated or control group, in contrast to interventional studies Even though randomized controlled trials are seen as the best study design, evidence shows that properly conducted observational studies give similar results, and is relevant in medical research where ethics and feasibility concerns assume great significance. Observational studies point out towards possible causal associations, are less resource intensive than trials and have a better external validity. This review article discusses various types of observational study designs such as case reports, cross sectional, cohort, case-control and nested case-control studies with real literature examples.

Medical research does not deal with only medical sciences; it is also dependent on other disciplines, and statistics is an integral part in its conduct. It is challenging for a medical researcher to grasp the importance of statistics and also to decide the types of statistical issues in the various phases of his/her medical research. There are inherent variations within and between the human/animal subjects used in medical research and these uncertainties can only be grasped using statistical tools. Initiating a medical research while taking into account the statistical aspects right at the planning stage is one of the best ways to conduct better evidence-based research. The validity of the results of a medical research depends not only on the methodology of conducting the study but also on the analysis of data collected. As opposed to the general perception, statistics not only deals with analysis of data but is also intricately interwoven with the methodology section of the research where sample sizes, inclusion/exclusion criteria, and others are mentioned. Although statistical softwares simplify the computational aspect of statistics, the confusing conceptual aspects make interpretation of the outputs difficult and incorrect. Seemingly simple terms such as population, sample, parameters, and variables have been explained keeping the medical researchers' perspective in mind. This first article in the series Statistics in Medical Research makes an attempt to facilitate the medical researcher to overcome the initial questions that challenge him/her with regard to statistics.