Information bias is one type of systematic error that can occur in epidemiologic studies. Bias
is any systematic error in an epidemiologic study that results in an incorrect estimate of the …

As we have emphasized throughout, epidemiologic research is best conceived as an
exercise in measurement. The primary objectives of this measurement depend on the nature …

Quantitative bias analyses allow researchers to adjust for uncontrolled confounding, given
specification of certain bias parameters. When researchers are concerned about unknown …

Bias, confounding, and random variation/chance are the reasons for a non-causal
association between an exposure and outcome. This chapter will define and discuss these …

The concept of bias is the lack of internal validity or incorrect assessment of the association
between an exposure and an effect in the target population in which the statistic estimated …

Quantitative bias analysis comprises the tools used to estimate the direction, magnitude, and
uncertainty from systematic errors affecting epidemiologic research. Despite the availability …

In this chapter, a catalog of the various types of bias that can affect the validity of clinical
epidemiologic studies is presented. The biases are classified by stage of research: literature …

Purpose Measurement error discussions often assume classification errors of key variables
are independent. Yet, small amounts of dependent error can create large biases in effect …

Optimal use of epidemiologic findings in decision making requires more information than
standard analyses provide. It requires calculating and reporting the total uncertainty in the …

Bias analysis quantifies the infiuence of systematic error on an epidemiology study's
estimate of occurrence or estimate of association. The fundamental methods of bias analysis …