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Lead time bias happens when survival time appears longer because diagnosis was done earlier (for instance, by screening), irrespective of whether the patient lived longer. Lead time is the duration of time between the detection of a disease (by screening or based on new experimental criteria) and its usual clinical presentation and diagnosis ...
The Bradford Hill criteria, otherwise known as Hill's criteria for causation, are a group of nine principles that can be useful in establishing epidemiologic evidence of a causal relationship between a presumed cause and an observed effect and have been widely used in public health research. They were established in 1965 by the English ...
Reporting bias. In epidemiology, reporting bias is defined as "selective revealing or suppression of information" by subjects (for example about past medical history, smoking, sexual experiences). [ 1] In artificial intelligence research, the term reporting bias is used to refer to people's tendency to under-report all the information available.
Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in a defined population . It is a cornerstone of public health, and shapes policy decisions and evidence-based practice by identifying risk factors for disease and targets for preventive healthcare.
Selection bias. Selection bias is the bias introduced by the selection of individuals, groups, or data for analysis in such a way that proper randomization is not achieved, thereby failing to ensure that the sample obtained is representative of the population intended to be analyzed. [ 1] It is sometimes referred to as the selection effect.
In epidemiology, particularly in the discussion of infectious disease dynamics (modeling), the latent period (also known as the latency period or the pre-infectious period) is the time interval between when an individual or host is infected by a pathogen and when that individual becomes infectious, i.e. capable of transmitting pathogens to ...
Matching (statistics) Matching is a statistical technique that evaluates the effect of a treatment by comparing the treated and the non-treated units in an observational study or quasi-experiment (i.e. when the treatment is not randomly assigned). The goal of matching is to reduce bias for the estimated treatment effect in an observational-data ...
A flaw in measuring exposure, covariate, or outcome variables that results in different quality (accuracy) of information between comparison groups. The occurrence of information biases may not be independent of the occurrence of selection biases . 2. Bias in an estimate arising from measurement errors." [2]