Table 2 fallacy¶

The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013.

Version: v1 · 2026-09-28 · History
Domain-specific #: 12443
Domain group: Applied Sciences & Engineering
Origin domain: Medicine & Healthcare
Subdomains: Epidemiologic Methods, Causal Inference → Medicine & Healthcare

Core Idea¶

Table 2 fallacy is treated here as the recurring epidemiologic methods identity summarized by this source-grounded definition: The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013.

The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. It is a concept in causal inference. In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2.

If the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing. The Table 2 Fallacy occurs when people seek to give a causal interpretation to the other parameters estimated using a multivariable regression model that was only designed to explore a single exposure - outcome association. Table 2 Fallacy is a common error made in reporting epidemiological results in a wide range of subject areas.

For Table 2 fallacy, the abstraction is narrower than the article's general subject matter: a positive case must preserve The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. Retaining only the name, a familiar example, or a downstream effect is insufficient. The specialist roles and tests remain anchored in epidemiologic methods, which is why this identity is domain-specific rather than prime.

Structural Signature¶

Sig role-phrases:

Defining carrier — The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013.
Constitutive relation — A high profile example was a paper exploring associations between demographic and health characteristics and death from COVID-19, which was used by the French government to define which groups of workers were deemed at risk.
Operating condition — This claim was contested by the study authors, who argued that their paper did not make causal claims.
Recognition evidence — In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2.
Admissible variation — If the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing.
Characteristic consequence — The Table 2 Fallacy occurs when people seek to give a causal interpretation to the other parameters estimated using a multivariable regression model that was only designed to explore a single exposure - outcome association.
Failure boundary — Table 2 Fallacy is a common error made in reporting epidemiological results in a wide range of subject areas.

What It Is Not¶

Not the whole field of epidemiologic methods. The node requires the specific identity stated by The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013.
Not an over-broad reading. This claim was contested by the study authors, who argued that their paper did not make causal claims.
Not an over-broad reading. The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013.
Not an over-broad reading. In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2.
Not automatically Causal reasoning. Retrieval proximity does not establish equivalence; the two identities must be compared by carrier, operation, and failure boundary.

Scope of Application¶

Table 2 fallacy applies literally inside epidemiologic methods wherever the source-defined carrier and relation can be established. Its documented habitats include:

Documented setting. If the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing.
Documented setting. A high profile example was a paper exploring associations between demographic and health characteristics and death from COVID-19, which was used by the French government to define which groups of workers were deemed at risk.
Documented setting. The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013.
Documented setting. In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2.
Documented setting. The Table 2 Fallacy occurs when people seek to give a causal interpretation to the other parameters estimated using a multivariable regression model that was only designed to explore a single exposure - outcome association.
Documented setting. Table 2 Fallacy is a common error made in reporting epidemiological results in a wide range of subject areas.

Outside epidemiologic methods, the name should be retained only when these same operational conditions survive; otherwise the comparison belongs to the broader parent Measurement or should be marked as analogy.

Clarity¶

A clear use of Table 2 fallacy names the carrier, the operative relation, and the conditions under which the source treats the identity as present. The minimal definition is The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. The strongest recognition evidence in the frozen account is: In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2. A report should distinguish that evidence from a proxy, consequence, or common implementation. It should also state the qualification This claim was contested by the study authors, who argued that their paper did not make causal claims. so that a reader can reproduce the classification rather than infer it from topical resemblance.

Manages Complexity¶

Table 2 fallacy compresses multiple epidemiologic methods details into a stable diagnostic relation. The source shows both the central mechanism—a high profile example was a paper exploring associations between demographic and health characteristics and death from COVID-19, which was used by the French government to define which groups of workers were deemed at risk.—and the practical consequence—the Table 2 Fallacy occurs when people seek to give a causal interpretation to the other parameters estimated using a multivariable regression model that was only designed to explore a single exposure - outcome association. This compression makes cases comparable while leaving parameters, conventions, exceptions, and evidential quality explicit. It is lossy by design: local history and implementation details may be omitted only when they do not alter the defining relation.

Abstract Reasoning¶

Type the carrier. Identify the epidemiologic methods entities to which the claim applies.
State the relation. Use the source-grounded identity: The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013.
Check operation and conditions. This claim was contested by the study authors, who argued that their paper did not make causal claims.
Demand recognition evidence. In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2.
Test variation. Change an implementation or setting while preserving if the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing.
Run the collapse test. Remove the defining operation; if the label still seems equally apt, only a topic or correlate was retained.
Reduce cautiously. When the specialist conditions cannot be carried, route the residual comparison to Measurement.

Knowledge Transfer¶

Within the home domain. Knowledge about Table 2 fallacy transfers literally when a new case preserves the same carrier type, relation, and recognition test. If the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing. A high profile example was a paper exploring associations between demographic and health characteristics and death from COVID-19, which was used by the French government to define which groups of workers were deemed at risk.

Beyond the home domain. No canonical parent is asserted for Table 2 fallacy. An outside case receives the specialist name only when the same typed roles and rejection conditions can be filled literally; otherwise the comparison remains an analogy pending later graph densification.

Examples¶

Canonical¶

The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. This case is canonical because it supplies a concrete carrier and lets the defining relation be checked rather than merely named.

Mapped back: carrier → the entities in the documented case; operation → The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013; recognition evidence → In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2

Applied / In Practice¶

In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2. The applied case shows how the identity is used under a second setting or qualification while keeping the same operative relation.

Mapped back: changed setting → the applied context; invariant → The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013; boundary → the case exits the class when this claim was contested by the study authors, who argued that their paper did not make causal claims

Structural Tensions¶

T1 — Stable identity versus admissible variation. This claim was contested by the study authors, who argued that their paper did not make causal claims. The tension matters because emphasizing only one side either dissolves the identity or overstates what the evidence and domain conventions warrant.

Diagnostic: Which changes preserve the defining relation, and which replace it?

T2 — Recognition versus proxy. The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. The tension matters because emphasizing only one side either dissolves the identity or overstates what the evidence and domain conventions warrant.

Diagnostic: Does the cited evidence establish the identity or only a correlated sign?

T3 — Definition versus implementation. In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2. The tension matters because emphasizing only one side either dissolves the identity or overstates what the evidence and domain conventions warrant.

Diagnostic: Is the observed implementation constitutive, optional, or merely common?

T4 — Scope versus overextension. If the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing. The tension matters because emphasizing only one side either dissolves the identity or overstates what the evidence and domain conventions warrant.

Diagnostic: Can every claimed application fill the same typed roles without metaphor?

T5 — Transfer versus domain accent. The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. The tension matters because emphasizing only one side either dissolves the identity or overstates what the evidence and domain conventions warrant.

Diagnostic: Does the receiving case instantiate Table 2 fallacy literally, co-instantiate Measurement, or only resemble it?

T6 — Autonomy versus reduction. A high profile example was a paper exploring associations between demographic and health characteristics and death from COVID-19, which was used by the French government to define which groups of workers were deemed at risk. The tension matters because emphasizing only one side either dissolves the identity or overstates what the evidence and domain conventions warrant.

Diagnostic: What does Table 2 fallacy distinguish that the broader parent Measurement leaves together?

Structural–Framed Character¶

Table 2 fallacy is mixed or framed-leaning. Its structural side is the repeatable organization summarized by The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. Its framed side is the epidemiologic methods vocabulary that fixes the carrier, evidence, exceptions, and admissible transformations.

Evaluative weight: the identity can be stated descriptively even when applications carry practical stakes. Human-practice dependence: the source-grounded carrier determines whether the relation exists independently or is constituted by a practice. Institutional origin: disciplinary conventions stabilize the name and test. Vocabulary portability: This claim was contested by the study authors, who argued that their paper did not make causal claims. Import versus recognition: literal transfer requires the same mechanism; shape alone is analogy.

Its portable skeleton is Measurement. Its character: a recurring specialist identity whose thin organization can be abstracted, while its operational meaning remains domain-bound.

Structural Core vs. Domain Accent¶

What is skeletal. The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. The stable skeleton is the typed relation expressed in that definition and the entry's recognition and collapse tests. The source identifies these operative conditions: The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. A high profile example was a paper exploring associations between demographic and health characteristics and death from COVID-19, which was used by the French government to define which groups of workers were deemed at risk. It further constrains recognition and variation through: This claim was contested by the study authors, who argued that their paper did not make causal claims. In scientific papers reporting observational studies, people often report both crude and adjusted associations between variables included in a regression model and the outcome of interest in Table 2.

What is domain-bound. epidemiologic methods supplies the operative entities, technical vocabulary, warrants, and exceptions that make Table 2 fallacy literal. Its documented scope includes the condition that If the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing. Another bounded application condition is that A high profile example was a paper exploring associations between demographic and health characteristics and death from COVID-19, which was used by the French government to define which groups of workers were deemed at risk. These are not decorative examples; they determine which carrier and evidence can fill the abstraction's roles.

Why no parent is asserted. Removing those specialist details does not currently yield one live catalog node that is a necessary genus for every instance. The entry is therefore approved as unparented rather than attached by topical resemblance. Its collapse evidence remains specific—If the purpose of the analysis is causal inference, usually, the variables one would choose to adjust for will differ for each exposure - outcome pairing.—and future graph densification may discover a defensible relation only if it preserves that boundary.

This entry is a kind of Informal Fallacy.

Approved unparented node. No current live node supplies a defensible necessary genus or structural prerequisite for Table 2 fallacy. The reviewed identity is: The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013. The accelerated suggestion was declined because topical or lexical similarity does not establish hierarchy; the node is admitted without a parent pending later graph densification.
Related reasoning operations. Evidence, representation, comparison, classification, transformation, or evaluation may participate in particular cases, but participation does not make any one of them a necessary parent of every instance.

Relationships to Other Abstractions¶

Current abstraction Table 2 fallacy Domain-specific

Parents (1) — more general patterns this builds on

Table 2 fallacy is a kind of Informal Fallacy Prime

The Table 2 fallacy is a named recurring inferential error caused by interpreting adjusted regression coefficients outside the causal role and estimand warranted by the model.

Hierarchy path (1) — routes to 1 parentless root

Table 2 fallacy → Informal Fallacy

Neighborhood in Abstraction Space¶

Table 2 fallacy sits in a moderately populated region (59^th percentile for distinctiveness): it has near-neighbors but no dense thicket of look-alikes.

Family — Inferential Fallacies & Research Biases (18 abstractions)

Nearest neighbors

Computed from structural-signature embeddings · 2026-10-08

Not to Be Confused With¶

Measurement. The parent omits the specialist differentia. Tell: Can the case establish The Table 2 Fallacy is a term coined by Daniel Westreich and Sander Greenland in 2013?
Causal reasoning. Infer, compare, test, or revise cause–effect structure by distinguishing interventions and counterfactual alternatives from association alone. Tell: Which entry's carrier, operation, and failure condition are satisfied?
Fallacy of the Single Cause. An informal reasoning error that treats one contributing factor as the sole or adequately complete cause when the explanatory claim requires additional enabling, interacting, alternative, or background conditions. Tell: Which entry's carrier, operation, and failure condition are satisfied?
Faulty generalization. An informal fallacy that infers a broad population claim from evidence too small, biased or unrepresentative to warrant that scope. Tell: Which entry's carrier, operation, and failure condition are satisfied?
A measurement, proxy, or consequence. Those may provide evidence without being the identity. Tell: Would Table 2 fallacy remain present if the detector or downstream effect changed?
A metaphorical analogue. A similar shape outside epidemiologic methods lacks the specialist mechanism. Tell: Do the native roles transfer literally, or only the parent Measurement?

References¶

Frozen Wikipedia discovery revision: https://en.wikipedia.org/wiki/Table_2_fallacy (revision 1316974088).
Preserved source candidate: https://academic.oup.com/aje/article/177/4/292/147738
Preserved source candidate: https://onlinelibrary.wiley.com/doi/10.1111/cdoe.12617
Preserved source candidate: https://www.sciencedirect.com/science/article/pii/S1063458421007056
Preserved source candidate: https://x.com/OBerruyer/status/1315757533643051010/photo/1

The frozen Wikipedia revision is discovery provenance. The retained source set was reviewed for identity, formal or operational relation, and scope. The encyclopedia's structural synthesis is bounded to those claims; a thin authority surface is recorded as a nonblocking source-strengthening repair rather than concealed.