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Post hoc ergo propter hoc

Post hoc ergo propter hoc is a logical fallacy in which a causal connection is assumed between two sequential events solely because one precedes the other, encapsulated by the Latin phrase meaning "after this, therefore because of this."^[1]^[2] This error, a subtype of the broader false cause fallacy, ignores alternative explanations, coincidences, or underlying factors that may influence outcomes.^[1]^[2] The concept traces its recognition to ancient philosophy, where it was identified as a prevalent mistake in reasoning about causes. Aristotle discussed false cause fallacies, including assuming causation from temporal sequence, in his Sophistical Refutations, emphasizing that temporal order alone does not establish causation.^[1] Greeks and Romans broadly acknowledged such flawed arguments thousands of years ago, integrating them into discussions of rhetoric and logic.^[3] In modern contexts, post hoc ergo propter hoc appears frequently in everyday reasoning, superstitions, pseudoscience, and even scientific debates, underscoring the need for rigorous evidence to distinguish correlation from causation.^[1] Examples include attributing a sports victory to a lucky charm worn beforehand or linking a policy change to subsequent economic trends without considering other variables.^[2] Identifying and avoiding this fallacy is essential in fields like medicine, law, and policy analysis to ensure decisions are based on sound logic rather than misleading temporal associations.^[3]

Definition

Meaning and Translation

The Latin phrase post hoc ergo propter hoc translates directly to "after this, therefore because of this."^[4]^[5] This expression identifies a common error in reasoning where one assumes that because one event follows another in time, the earlier event must have caused the later one, without establishing any actual causal connection.^[1]^[2] In informal logic, post hoc ergo propter hoc is classified as a type of non sequitur fallacy, where the conclusion does not logically follow from the premises due to the unwarranted leap from temporal sequence to causation.^[6] The phrase is typically pronounced in English as /ˌpoʊst ˈhɒk ˈɛrɡoʊ ˈprɒptər ˈhɒk/.^[7]

Logical Fallacy Classification

Post hoc ergo propter hoc is classified as an informal fallacy within logical theory, as it involves errors in reasoning content rather than strictly invalid logical form.^[1] Informal fallacies, unlike formal ones that violate deductive rules such as affirming the consequent, depend on the substantive relevance or empirical accuracy of premises to conclusions, often arising in everyday or inductive arguments.^[1] Specifically, post hoc ergo propter hoc falls under the category of causal fallacies, where a temporal sequence is erroneously interpreted as evidence of causation, and it also qualifies as a non sequitur because the conclusion does not logically follow from the premises without additional justifying evidence.^[2] This fallacy is particularly associated with errors in inductive reasoning, where observed correlations—such as one event preceding another—are mistakenly elevated to causal claims without sufficient controls for alternative explanations or confounding factors.^[1] In inductive contexts, it exemplifies the broader problem of confusing mere temporal proximity with necessity or sufficiency in causation, a common pitfall in probabilistic or empirical inference.^[2] In Aristotelian logic, post hoc ergo propter hoc aligns with the fallacy of non causa pro causa (assuming the wrong thing as the cause), as outlined in Aristotle's Sophistical Refutations, where he critiques arguments that attribute causation based on irrelevant or incidental connections rather than true efficient causes.^[1] Modern critical thinking taxonomies continue this tradition; for instance, Irving M. Copi in Introduction to Logic categorizes it as a variety of false cause under informal fallacies, emphasizing its role in misleading causal attributions.^[8]

Etymology and History

Origins in Latin Rhetoric

The phrase post hoc ergo propter hoc derives directly from Latin, translating literally as "after this, therefore because of this." It combines "post hoc," meaning "after this," with "ergo," denoting "therefore," and "propter hoc," signifying "because of this." This linguistic construction encapsulates a specific error in reasoning central to rhetorical and logical discourse.^[1] The roots of the fallacy lie in classical rhetoric, where the dangers of inferring causation solely from temporal succession were recognized in discussions of argumentative validity. Roman rhetorical traditions, adapting Greek concepts of causation—particularly Aristotle's framework of the four causes (material, formal, efficient, and final) as outlined in Physics and Metaphysics—stressed rigorous causal analysis to avoid fallacious appeals in legal and political debates, thereby influencing how sequence-based errors were critiqued in public discourse.^[1] Although the concept of false cause was discussed in medieval scholastic logic as a form of non causa pro causa, the explicit phrase post hoc ergo propter hoc emerged later, formalized in the 17th-century Port-Royal Logic (1662) as a named fallacy of causal inference from sequence alone. Scholastic philosophers, building on Aristotelian and Roman foundations, cataloged false cause errors in treatises on dialectics, emphasizing their role in invalid syllogisms and rhetorical refutations. This development marked a key step in the recognition of sequence-based causal errors in Western intellectual tradition.^[1]

Historical Usage and Examples

In medieval theological and philosophical debates, the post hoc ergo propter hoc fallacy manifested in discussions of causation, particularly through the broader category of "non causa pro causa" (false cause). Thirteenth-century logician and theologian Peter of Spain, in his influential Summulae Logicales, categorized false cause fallacies following Aristotle's framework, including instances where temporal sequence was mistaken for causal necessity, such as assuming a preceding event in a chain of reasoning directly produced a subsequent theological outcome without sufficient evidence.^[9] This scholastic analysis was applied in theological contexts to critique erroneous inferences about divine intervention or moral consequences following events, emphasizing the need for rigorous proof beyond mere succession in arguments about grace or sin.^[9] During the Renaissance and Enlightenment, critiques of the fallacy gained prominence in philosophical examinations of causation. David Hume, in his 1739 A Treatise of Human Nature, dissected the human tendency to infer causation from repeated observations of contiguity and temporal priority, arguing that such inferences stem from custom rather than rational necessity, thereby highlighting the post hoc error inherent in assuming sequence implies causation.^[10] Hume's analysis influenced subsequent Enlightenment thinkers by underscoring how unexamined temporal associations could lead to flawed causal claims in both natural philosophy and moral reasoning, without invoking any inherent "power" in causes.^[10] In the 19th century, the fallacy appeared in scientific contexts, notably in early epidemiology through the persistence of the miasma theory. Proponents, observing illnesses like cholera following exposure to foul-smelling air from decaying matter, inferred that such "bad air" directly caused disease, mistaking coincidental temporal or spatial associations for causal links and delaying the acceptance of germ theory until evidence from figures like John Snow demonstrated alternative mechanisms. The 20th century saw the fallacy employed in political propaganda, particularly in attributions of economic downturns to preceding events like the Treaty of Versailles after World War I. German nationalists and later propagandists claimed the 1919 treaty's reparations directly caused the 1923 hyperinflation and subsequent economic woes, ignoring intervening factors such as fiscal policies and global trade disruptions, to fuel resentment and justify revanchism.^[11] This post hoc reasoning amplified in interwar discourse contributed to narratives blaming the treaty for broader instability, exemplifying how sequential events were leveraged for ideological ends.

The Fallacy Pattern

Formal Structure

The post hoc ergo propter hoc fallacy follows a specific argumentative pattern where temporal sequence is mistaken for causal connection. The structure consists of two premises and a conclusion: Premise 1 states that event A occurred prior to event B; Premise 2 affirms that event B occurred; and the conclusion asserts that event A caused event B.^[2]^[12] Symbolically, this can be represented as inferring a causal relation (A causes B) solely from the temporal precedence (A occurs before B), often denoted as A → B where the arrow indicates sequence rather than causation.^[2] The core gap in this reasoning lies in the assumption that "post hoc" (after this) necessarily implies "propter hoc" (because of this); temporal order establishes neither necessity nor sufficiency for causation, as coincidence or unrelated factors may intervene.^[12] This pattern contrasts with valid causal arguments, which demand supplementary evidence such as explanatory mechanisms, controlled experiments, or statistical controls to rule out alternatives, beyond mere precedence.^[2] As an informal fallacy, it errs in the content of the premises rather than their logical form.^[12]

Reasons for Invalidity

The post hoc ergo propter hoc fallacy violates fundamental criteria for establishing causation by assuming that temporal precedence alone suffices to prove a causal link, whereas genuine causation requires additional evidence to exclude alternatives such as coincidence, common causes, or reverse causation.^[2] Philosophers and scientists emphasize that correlation in time does not imply causation, as the observed sequence may result from random chance or an unaccounted third factor influencing both events.^[9] For instance, ruling out reverse causation—where the supposed effect actually precedes or triggers the cause—demands rigorous testing beyond mere observation of order.^[13] This error finds its philosophical roots in David Hume's problem of induction, which argues that constant conjunction of events (repeated temporal succession) does not logically necessitate a causal connection, as no experience reveals an inherent "necessary" tie between them.^[14] Hume contended that our belief in causation arises from habit and custom rather than rational proof, rendering inferences from past sequences to future causal necessities unjustified without further premises.^[15] Thus, the post hoc pattern exemplifies Hume's critique by treating observed succession as sufficient evidence for an unproven inductive necessity.^[14] Cognitive biases exacerbate the fallacy's prevalence by predisposing individuals to perceive causal links where none exist. Confirmation bias leads people to selectively notice and recall instances supporting a hypothesized cause while ignoring disconfirming evidence, thereby reinforcing erroneous temporal associations.^[16] Similarly, illusory correlation amplifies the error through the tendency to overestimate relationships between events that are salient or stereotyped, even in the absence of actual dependency, making post hoc reasoning intuitively appealing despite its flaws.^[17] Logically, the post hoc argument is invalid because its conclusion neither follows deductively from the premises nor carries high inductive probability without supplemental evidence to establish causal mechanisms.^[1] As an informal fallacy, it fails deductive standards by not guaranteeing the truth of the conclusion from temporal premises alone, and it undermines inductive strength by overlooking the low probability that sequence alone predicts causation amid confounding possibilities.^[2]

Examples

Everyday and Cultural Examples

One common manifestation of the post hoc ergo propter hoc fallacy appears in superstitions, where individuals attribute success to coincidental preceding actions. For instance, a sports fan who wears a particular shirt during a team's victory might conclude that the shirt caused the win and continue wearing it for future games, ignoring that the outcome likely depended on players' skills rather than apparel.^[18] This belief reinforces the fallacy by linking temporal sequence to causation without evidence of a mechanistic connection.^[19] In cultural folklore and rituals, the fallacy often underpins practices aimed at influencing natural events. A classic example is the rain dance performed by certain indigenous groups during droughts; if precipitation follows the ceremony, participants may infer that the ritual directly summoned the rain, overlooking meteorological factors like seasonal patterns or atmospheric conditions.^[20] Such attributions persist in traditions worldwide, where the ritual's timing aligns with eventual outcomes, fostering a false causal narrative that sustains the custom across generations.^[21] Advertising frequently exploits this fallacy to imply product efficacy through sequential events. Advertisements might claim that sales surged after adopting a new marketing campaign, suggesting the campaign solely drove the increase, while disregarding market trends, seasonal demand, or competitor actions that could explain the rise.^[22] This tactic persuades consumers by presenting post-event success as proof of causation, encouraging purchases based on illusory links rather than controlled analysis.^[23] Political rhetoric commonly invokes the fallacy when crediting policies for economic improvements. Politicians may assert that GDP growth followed the implementation of a tax cut, thereby claiming the policy as the direct cause, without accounting for global economic cycles, prior momentum, or confounding variables like technological advancements.^[24] This oversimplification sways public opinion by emphasizing temporal proximity over rigorous evaluation, as seen in debates over trade policies where post-implementation booms are hailed as causal triumphs despite alternative explanations.^[25]

Scientific and Medical Examples

In the field of medicine, the post hoc ergo propter hoc fallacy has notably influenced anti-vaccination arguments, particularly regarding the onset of autism spectrum disorder symptoms following immunization. Parents and advocates have historically claimed that vaccines cause autism because developmental signs often emerge shortly after routine vaccinations, such as the MMR shot, around the age of 12-18 months when symptoms typically become apparent. This temporal sequence led to widespread misconceptions, exemplified by reactions to a 1998 study by Andrew Wakefield that suggested a link, despite subsequent retractions and extensive research debunking any causal connection. Large-scale epidemiological studies, including those by the Centers for Disease Control and Prevention, have shown no association, attributing the perceived link to coincidence and the natural timing of autism diagnosis rather than vaccination effects.^[26]^[27] In pseudoscientific practices like astrology, the fallacy manifests in claims that planetary alignments cause subsequent earthly events, such as disasters or personal misfortunes. A historical instance occurred in 1524, when astrologers in Europe and China predicted cataclysmic floods or the world's end due to a rare conjunction of Jupiter, Saturn, Mars, Mercury, and Venus, interpreting the alignment as a harbinger of doom. When minor floods followed in some regions, proponents cited these as validation, ignoring that such weather events were common and unrelated to celestial positions. This exemplifies how post hoc reasoning reinforces astrological beliefs without empirical causation, as modern astronomical analysis confirms no gravitational or influential mechanism links planetary positions to terrestrial outcomes.^[28]^[29] Prior to Benjamin Franklin's experiments in the 18th century, a widespread superstition in Europe held that ringing church bells during thunderstorms could avert lightning strikes, yet this practice often resulted in the opposite effect and numerous fatalities. Bell ringers were dispatched to towers to create noise believed to disperse storm clouds or appease divine wrath, but lightning frequently struck the tall, conductive structures afterward, killing over 100 ringers between 1753 and 1786 alone in documented cases across Germany, France, and Italy. Some interpretations persisted that the ringing provoked the lightning as punishment, a post hoc assumption that reinforced the ritual despite evidence of attraction rather than repulsion, leading the French Parlement to ban the practice in 1786 to prevent further deaths. This error highlights how temporal proximity between the action and natural electrical discharge was misconstrued as causation in pre-scientific understandings of atmospheric electricity.^[30]^[31] In modern ecology, the post hoc fallacy has contributed to misguided attributions of species declines solely to pesticide introduction, without adequately isolating variables like habitat loss or climate change. For instance, in the mid-20th century, the sharp drop in bird populations following widespread DDT use in the 1940s was initially blamed entirely on the pesticide based on its temporal precedence, as seen in early reports from agricultural regions in the United States and Europe where raptor eggshells thinned post-application. While DDT did bioaccumulate and cause reproductive harm, subsequent analyses revealed confounding factors such as wetland drainage and overhunting amplified the declines, yet initial post hoc claims delayed comprehensive regulatory responses until controlled studies in the 1960s confirmed multifaceted causes. This pattern underscores the risk of erroneous causal inferences in environmental research, where sequential events are assumed linked without rigorous variable control.^[32]^[33]

Cum Hoc Ergo Propter Hoc

Cum Hoc Ergo Propter Hoc is a logical fallacy that occurs when one assumes a causal relationship between two events simply because they happen to occur together in time or space, without any evidence of one influencing the other.^[2] The phrase is derived from Latin, translating literally to "with this, therefore because of this," emphasizing the erroneous inference drawn from mere co-occurrence or correlation.^[2] This fallacy highlights the common error of mistaking correlation for causation, where simultaneous or concurrent events are wrongly interpreted as one causing the other.^[34] Unlike the post hoc ergo propter hoc fallacy, which relies on a perceived temporal sequence (one event following another) to imply causation, cum hoc ergo propter hoc focuses specifically on events that coincide without a strict order, such as spatial or simultaneous associations.^[34] This distinction underscores that while both fallacies involve invalid causal claims, cum hoc centers on correlation arising from shared circumstances rather than chronology.^[9] For instance, two unrelated phenomena might both increase due to a third confounding factor, leading to the false assumption of direct causation between them.^[35] A classic example of this fallacy is the observed correlation between ice cream sales and drowning incidents, both of which rise sharply during summer months, prompting the invalid conclusion that consuming ice cream causes drownings.^[35] In reality, the summer heat drives both trends independently—higher temperatures boost ice cream consumption and increase swimming activity, thereby elevating drowning risks—without any causal link between the two.^[35] Another illustrative case involves the correlation between the number of fire trucks at a fire scene and the extent of property damage; more trucks often appear at larger fires, but this co-occurrence does not mean the trucks cause the greater damage.^[9] These examples demonstrate how cum hoc ergo propter hoc can mislead by ignoring underlying common causes or spurious associations.

Other Causal Fallacies

The single cause fallacy, also known as causal oversimplification, occurs when a complex phenomenon is erroneously attributed to a single factor, ignoring the multifaceted nature of causation.^[36] This error assumes that one variable is solely responsible for an outcome, disregarding interactions among multiple contributing elements, which leads to incomplete or misleading explanations.^[37] For instance, claiming that "poverty causes all crime" overlooks additional influences such as education levels, social policies, and psychological factors that interplay in criminal behavior.^[36] Philosophers and logicians emphasize that this fallacy undermines rigorous analysis by reducing intricate social or natural processes to simplistic narratives, often for rhetorical convenience.^[37] Another related error is the slippery slope fallacy, which posits that a relatively minor initial action will inevitably trigger a sequence of escalating events leading to an extreme and undesirable outcome, without sufficient evidence for the causal chain.^[1] This argument relies on unsubstantiated projections of consequences, treating potential developments as certain domino effects rather than contingent possibilities.^[38] A classic example involves opposition to minor policy changes, such as legalizing certain drugs, by arguing it will lead unchecked to widespread societal collapse, ignoring intervening safeguards or empirical data that might halt the progression.^[1] Critical thinking resources highlight that while some causal sequences are plausible, the fallacy arises when the links are asserted dogmatically, bypassing probabilistic assessment.^[38] Reverse causation, or the wrong direction fallacy, involves mistaking the direction of causality by assuming that an effect produces its cause, rather than vice versa.^[39] This inversion confuses temporal or correlational patterns with the true causal arrow, leading to flawed inferences about relationships between variables.^[40] For example, asserting that "illness causes poverty" reverses the more likely dynamic where economic hardship contributes to health decline through limited access to care and nutrition.^[39] Statistical analyses warn that such errors are common in observational studies, where bidirectional influences or confounding variables obscure the actual pathway, necessitating experimental designs to clarify directionality.^[40] The common cause fallacy, distinct from mere correlational errors, arises when two correlated events are presumed to have a direct causal link (one causing the other), failing to recognize an underlying third factor that influences both.^[2] In this scenario, the oversight attributes causation to one of the observed variables while ignoring the shared antecedent, resulting in spurious conclusions.^[2] For instance, a rise in ice cream sales and drowning incidents might be linked fallaciously as causal, when summer heat—a common cause—drives both.^[36] Logical frameworks stress that identifying potential confounders through controlled inquiry is essential to avoid this pitfall in causal reasoning.^[2]

Detection and Avoidance

Critical Thinking Strategies

To counter the post hoc ergo propter hoc fallacy, individuals can employ practical critical thinking strategies that emphasize scrutiny of assumed causal connections based solely on temporal order. A foundational step is questioning the temporal sequence by inquiring whether the preceding event is truly the cause or if other factors might better explain the outcome. For example, when presented with a claim that a policy change led to economic improvement simply because it occurred beforehand, one should probe for intervening variables like market trends or unrelated global events that could account for the result. This approach helps dismantle the invalid assumption that sequence implies causation, as highlighted in analyses of common reasoning errors.^[5] Seeking alternative explanations is another essential strategy, focusing on possibilities such as mere coincidence, reverse causation (where the outcome influences the prior event), or confounding variables that affect both. Critical thinkers are encouraged to list potential non-causal links, such as shared underlying influences, to broaden their perspective and avoid hasty conclusions. This method promotes intellectual humility by recognizing that temporal proximity alone rarely establishes causality, drawing from established frameworks for evaluating arguments.^[2] Demanding robust evidence further strengthens reasoning against the fallacy. This involves insisting on a clear mechanism detailing how the antecedent event produces the effect, along with supporting data from observations or tests that rule out alternatives. Without such substantiation, claims remain suspect; for instance, requiring explanations of processes or patterns that consistently link the events ensures claims are grounded rather than speculative.^[18] Educational tools, such as checklists derived from critical thinking curricula, provide structured ways to apply these strategies. Common prompts include: "Does the outcome invariably follow the antecedent, or only coincidentally?" and "What independent evidence supports a causal mechanism beyond timing?" These questions, adapted from resources on causal evaluation, foster habitual vigilance and improve decision-making in everyday arguments.^[41]

Statistical and Scientific Approaches

Controlled experiments employ randomization to assign participants to treatment or control groups, ensuring that potential confounders are evenly distributed and minimizing biases that could lead to erroneous attributions of causality based solely on temporal order. By creating comparable groups, randomization isolates the effect of the intervention from extraneous variables, thereby preventing the post hoc ergo propter hoc fallacy where sequence is mistaken for causation.^[42] Blinding, or masking the allocation of treatments from participants, researchers, or both, further safeguards against performance and detection biases that might inflate perceived causal links due to expectations rather than actual effects.^[43] Together, these techniques enable researchers to attribute outcomes to the manipulated variable with greater confidence, as demonstrated in randomized controlled trials where they reduce the risk of spurious temporal associations.^[44] Statistical tests provide rigorous tools for detecting causality in observational data, particularly when experimental control is infeasible. The Granger causality test, developed for time-series analysis, assesses whether values of one variable improve predictions of another beyond what the latter's own past values can achieve, thus requiring more than mere precedence to infer a directional influence and countering post hoc assumptions.^[45] In econometrics and neuroscience, this test has been widely applied to disentangle lead-lag relationships in dynamic data, such as financial markets or neural signals, where temporal ordering alone often misleads.^[46] Complementing this, regression analysis controls for confounders by incorporating them as covariates in the model, allowing estimation of the independent effect of the exposure variable while adjusting for alternative explanations that might correlate with both cause and effect.^[47] This approach, when assumptions like no omitted variables are met, facilitates causal inference by partitioning variance attributable to the predictor of interest.^[48] Longitudinal studies track the same subjects or cohorts over extended periods, enabling researchers to observe the sequence of events and changes in variables to differentiate true causal pathways from coincidental correlations. By measuring exposures before outcomes and accounting for time-varying factors, these designs establish temporality—a cornerstone against reverse causation—and reveal whether an antecedent reliably precedes and influences subsequent developments, as seen in cohort analyses of health risks where baseline data precede follow-up assessments.^[49] For instance, in orthopedic research examining body mass index and mortality post-joint arthroplasty, long-term follow-up excludes early events that could confound interpretations, clarifying that low BMI temporally precedes higher mortality risks without implying unexamined mediators.^[50] This temporal depth helps mitigate post hoc errors by providing empirical evidence of directionality and stability over time, unlike cross-sectional snapshots that conflate association with causation.^[51] In epidemiology, the Bradford Hill criteria offer a structured framework for evaluating whether observed associations warrant causal interpretation, emphasizing multiple lines of evidence beyond mere temporal sequence. Proposed in 1965, these nine viewpoints include strength of association, consistency across studies, specificity of effect, temporality (ensuring cause precedes effect), biological gradient (dose-response relationship), plausibility, coherence with existing knowledge, experimental evidence, and analogy to similar causal links.^[52] Temporality directly addresses post hoc concerns by requiring that the putative cause manifest before the outcome, while strength and consistency guard against weak or idiosyncratic findings mistaken for causation.^[53] Applied to public health investigations, such as linking smoking to lung cancer, the criteria collectively assess causal claims, with no single viewpoint being definitive but their convergence providing robust support against fallacy-driven conclusions.^[54]

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Causal statements are sentences which say that one thing causes, or doesn't cause, another thing. For example, smoking causes lung cancer.
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Selection of Control, Randomization, Blinding, and Allocation ...
Aug 28, 2019 · Randomization is the method adopted to eliminate the bias of selection and confounder. It has got two steps; generation of random number and ...
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Blinding: Who, what, when, why, how? - PMC - NIH
Blinding refers to the concealment of group allocation from one or more individuals involved in a clinical research study, most commonly a randomized ...
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CONSORT 2010 Explanation and Elaboration: updated guidelines ...
Mar 24, 2010 · Turning a blind eye: the success of blinding reported in a random sample of randomised, placebo controlled trials. BMJ 2004;328:432. OpenUrl ...Missing: isolate | Show results with:isolate
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Granger Causality: A Review and Recent Advances - PMC
Granger causality has become a popular tool for analyzing time series data in many application domains, from economics and finance to genomics and neuroscience.
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Introduction to Granger Causality - Aptech
Jun 29, 2021 · Granger causality is an econometric test used to verify the usefulness of one variable to forecast another. A variable is said to: Granger-cause ...<|separator|>
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[PDF] Causal inference using regression on the treatment variable
In general, then, causal effects can be estimated using regression if the model includes all confounding covariates (predictors that can affect treatment ...
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Full article: Causal inference in regression: advice to authors
Dec 10, 2021 · The first type of causal confounding is omitted variable bias. Suppose that we are interested in estimating the causal effect of an exposure X on an outcome Y.
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How to Distinguish Correlation from Causation in Orthopaedic ... - NIH
Correlation does not imply causation, whereas, causation frequently occurs with correlation. Correlation and causation are related concepts, but may require ...
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How to Distinguish Correlation From Causation in Orthopaedic ...
In this article, we illustrate the main concepts surrounding correlation and causation using intuitive real-world examples from the orthopaedic literature.
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Risky Business: Correlation and Causation in Longitudinal Studies ...
Substantial longitudinal correlations within domains of academic achievement and socioemotional behaviors are predicted by these skill-building causal models ...
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Assessing causality in epidemiology: revisiting Bradford Hill to ... - NIH
Abstract. The nine Bradford Hill (BH) viewpoints (sometimes referred to as criteria) are commonly used to assess causality within epidemiology.
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Applying the Bradford Hill criteria in the 21st century: how data ... - NIH
Sep 30, 2015 · In 1965, Sir Austin Bradford Hill published nine “viewpoints” to help determine if observed epidemiologic associations are causal.
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The role of causal criteria in causal inferences: Bradford Hill's
Jun 17, 2009 · The criteria used in the Report were the consistency, strength, specificity, temporal relationship, and coherence of the association. Following ...