Major Sources Of Bias In Research Studies

Major Sources of Bias in Research Studies There are two types of error associated with most forms of research: random and systematic. Random errors, i.e., those due to sampling variability or measurement precision, occur in essentially all quantitative studies and can be minimized but not avoided. Systematic errors, or biases, are reproducible inaccuracies that produce a consistently false pattern of differences between observed and true values. Both random and systematic errors can threaten the validity of any research study. However, random errors can be easily determined and addressed using statistical analysis; most systematic errors or biases cannot. This is because biases can arise from innumerable sources, including complex human factors. For this reason, avoidance of systematic errors or biases is the task of proper research design Major Categories of Research Bias
There are many different types of biases described in the research literature. The most common categories of bias that can affect the validity of research include the following: 1. Selection biases, which may result in the subjects in the sample being unrepresentative of the population of interest
2. Measurement biases, which include issues related to how the outcome of interest was measured
3. Intervention (exposure) biases, which involve differences in how the treatment or intervention was carried out, or how subjects were exposed to the factor of interest More detail on each of these three categories of bias is provided below, including some specific types and examples. For more detail on the various types of biases, including how they can be controlled, link to the following article: Hartman, J.M., Forsen, J.W., Wallace, M.S., Neely, J.G. (2002). Tutorials in clinical research: Part IV: Recognizing and controlling bias. Laryngoscope, 112, 23-31. Selection Biases