Essentials of Biostatistics. 3. Methods of sampling and data collection

Abstract

Clinicians usually deal with samples of blood, urine, stool, etc., and also with specimens such as biopsies. Besides these, the subjects included in a medical study almost invariably are a sample. We earlier explained special meaning of the term population in statistics(1). It can be understood as the target group for which the investigation results are intended to be extrapolated. For example, in a descriptive study on acute respiratory infection (ARI) among children in a country, the target population could be all existing cases of ARI in that country. Cost and logistic considerations seldom allow study of all the subjects. Sampling becomes a natural choice. In the context of health and medicine, full coverage is rarely possible. All existing cases can possibly be included in an investigation but the cases occurring in future can not be included. And the findings would most likely be extrapolated to the future cases. Thus, sampling arguments are integral part of the science of medicine. The obvious advantages of sampling are reduced cost and faster results. The not so obvious is the possibility of getting more accurate results because better technology can be more easily used on small number of subjects. Sampling can however create a feeling of discrimination in some cases when sampled subjects get special attention and the others do not. We first describe some terms specially used in the context of sampling in Section 3.1 and then various methods of sampling in Section 3.2. In Section 3.3, a brief account of study tools that are used in data collection is given.