Which of the following statement is true about criteria for a causal relationship
According to the philosopher John Stuart Mill: Show
Correlation does not prove causation!! Useful resources:
https://conjointly.com/kb/establishing-cause-and-effect/ https://cdn1.sph.harvard.edu/wp-content/uploads/sites/1268/2020/07/ci_hernanrobins_31july20.pdf References: Shadish, W., Cook, T. & Campbell, D (2002). Experimental & Quasi- Experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin. The UK Faculty of Public Health has recently taken ownership of the Health Knowledge resource. This new, advert-free website is still under development and there may be some issues accessing content. Additionally, the content has not been audited or verified by the Faculty of Public Health as part of an ongoing quality assurance process and as such certain material included maybe out of date. If you have any concerns regarding content you should seek to independently verify this. IntroductionLearning objectives: You will learn basic concepts of causation and association.At the end of the session you should be able to differentiate between the concepts of causation and association using the Bradford-Hill criteria for establishing a causal relationship. Read the resource text below. Resource textA principal aim of epidemiology is to assess the cause of disease. However, since most epidemiological studies are by nature observational rather than experimental, a number of possible explanations for an observed association need to be considered before we can infer a cause-effect relationship exists. That is, the observed association may in fact be due to the effects of one or more of the following:
Therefore, an observed statistical association between a risk factor and a disease does not necessarily lead us to infer a causal relationship. Conversely, the absence of an association does not necessarily imply the absence of a causal relationship. The judgement as to whether an observed statistical association represents a cause-effect relationship between exposure and disease requires inferences far beyond the data from a single study and involves consideration of criteria that include the magnitude of the association, the consistency of findings from other studies and biologic credibility [1]. The Bradford-Hill criteria are widely used in epidemiology as providing a framework against which to assess whether an observed association is likely to be causal. The Bradford-Hill criteria (J Roy Soc Med 1965:58:295-300)1. Strength of the association. 2. Consistency of findings. 3. Specificity of the association. 4. Temporal sequence of association. 5. Biological gradient. 6. Biological plausibility. 7. Coherence. 8. Experiment. For example, the first criterion 'strength of association' does not take into account that not every component cause will have a strong association with the disease that it produces and that strength of association depends on the prevalence of other factors. In terms of the third criterion, 'specificity', which suggests that a relationship is more likely to be causal if the exposure is related to a single outcome, Rothman argues that this criterion is misleading as a cause may have many effects, for example smoking. The fifth criterion, biological gradient, suggests that a causal association is increased if a biological gradient or dose-response curve can be demonstrated. However, such relationships may result from confounding or other biases. The process of causal inference is complex, and arriving at a tentative inference of a causal or non-causal nature of an association is a subjective process. For a comprehensive discussion on causality refer to Rothman. References 1. Hennekens CH, Buring JE. Epidemiology in Medicine, Lippincott Williams & Wilkins, 1987. Further Reading Rothman KJ, Modern Epidemiology, Lippincott Williams & Wilkins, 1998, p7-28. What are the criteria will be needed to determine a causal relationship?To establish causality you need to show three things–that X came before Y, that the observed relationship between X and Y didn't happen by chance alone, and that there is nothing else that accounts for the X -> Y relationship.
What is a true causal relationship?Causation indicates that one event is the result of the occurrence of the other event; i.e. there is a causal relationship between the two events. This is also referred to as cause and effect.
What are the 3 criteria for establishing a causal relationship quizlet? Covariance (association between variables). Temporal Order (IV done before DV). No alternative explanations (confounds are ruled out). What are the main criteria for causality?Causality. Plausibility (reasonable pathway to link outcome to exposure). Consistency (same results if repeat in different time, place person). Temporality (exposure precedes outcome). Strength (with or without a dose response relationship). Specificity (causal factor relates only to the outcome in question - not often). |