Random Error In Case Control Study
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Measurement Error
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How To Reduce Random Error
Asia Toggle navigation The BMJ logo Site map Search Search form SearchSearch Advanced search information bias Search responses Search blogs Toggle top menu ResearchAt a glance Research papers Research methods and reporting Minerva Research news EducationAt a recall bias glance Clinical reviews Practice Minerva Endgames State of the art News & ViewsAt a glance News Features Editorials Analysis Observations Head to head Editor's choice Letters Obituaries Views and reviews Rapid responses Campaigns Archive For authors http://www.ncbi.nlm.nih.gov/pubmed/23333321 Jobs Hosted About The BMJ Resources for online and print readers Publications Epidemiology for the uninitiated Chapter 4. Measurement error and bias Chapter 4. Measurement error and bias More chapters in Epidemiology for the uninitiated Epidemiological studies measure characteristics of populations. The parameter of interest may be a disease rate, the prevalence of an exposure, or more often some measure of the association between an exposure and disease. Because studies are http://www.bmj.com/about-bmj/resources-readers/publications/epidemiology-uninitiated/4-measurement-error-and-bias carried out on people and have all the attendant practical and ethical constraints, they are almost invariably subject to bias. Selection bias Selection bias occurs when the subjects studied are not representative of the target population about which conclusions are to be drawn. Suppose that an investigator wishes to estimate the prevalence of heavy alcohol consumption (more than 21 units a week) in adult residents of a city. He might try to do this by selecting a random sample from all the adults registered with local general practitioners, and sending them a postal questionnaire about their drinking habits. With this design, one source of error would be the exclusion from the study sample of those residents not registered with a doctor. These excluded subjects might have different patterns of drinking from those included in the study. Also, not all of the subjects selected for study will necessarily complete and return questionnaires, and non-responders may have different drinking habits from those who take the trouble to reply. Both of these deficiencies are potential sources of selection bias. The possibility of selection bias should always be considered when defining a study sample. Furthermore, when responses are incomplete, the scope for bias must be assessed. The problems of incomplete response to surveys are consi
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