Bias Results From Random Variation. The components of any predictive errors are Noise Bias and Variance. In the eye of the beholder.
Analysis of results by observer will then indicate any major problems and perhaps permit some statistical correction for the bias. Others have observed that random measurement error can bias the regression slope coefficient downwards towards the null a phenomenon known as attenuation or regression dilution bias5 6 7 In reality the estimate of the association between an exposure and an outcome is attenuated by random measurement error in some situations but remain unchanged in others. Bias Is Usually Reduced When The Sample Size Is Larger.
Alternatively the bias within a survey may be neutralised by random allocation of subjects to observers.
In the eye of the beholder. Bias results from a sampling method likely to produce samples that do not represent the population. Bias results from samples that do not represent the. Each observer should be identified by a code number on the survey record.