Information bias in health research: definition, pitfalls, and adjustment methods

Alaa Althubaiti · Journal of Multidisciplinary Healthcare · 2016 · epidemiology · 10.2147/jmdh.s104807 · record althubaiti2016-information-bias-in-health-researc
tag layer · index · concepts · authors · עברית
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Other fields define these differently the same word, defined another way in another discipline
Bias 38 fields · confirmation bias 4 fields · random error 3 fields · measurement error 2 fields

Tags on this paper

Every tag the record carries, each linking to every other paper in the corpus that carries it. A tag appears here whether or not its words occur in the article — the spans below are only the ones a sentence in this paper licenses. Of the 16 concept tags on this paper, all 16 are grounded in a quoted sentence. All carry the tagger's gloss of what the term means in this paper, which is not something the article can license.
Bias any systematic error in the design, conduct, or analysis of a study selection bias information bias measurement error measurement bias confirmation bias observer bias random sampling measurement error variability An analysis that ignores the effect of measurement error on the results a naïve analysis cases healthy controls The size of the difference between the observed rates of exposure to risk factors in cases and controls the observed odds ratio naïve analysis systematic error random error recall period a validation chain with no true value at the end of it what the standard toolbox silently does not cover review
Method, as described: a narrative review of the bias literature, organised by type of information bias and by the study design in which each is most likely

Legend

relation to other workclaim_relationshow this paper stands to another: agrees, contradicts, extends, qualifies
claim typeclaim_typethe shape of the claim: existence, mechanism, method, critique, prediction, null
concept edgeconcept_edgesan asserted relation between two concepts, with the sentence asserting it
conceptconceptsan idea the paper works with, quoted where the paper uses it
content tagcontent_tagsa finding, definition, quantity, statistic or variable named in the paper
contributioncontributionwhat the paper claims to add
controlcontrolsan experiment run to eliminate a rival explanation
limitationlimitationswhat the paper says its evidence cannot support
mechanismmechanismshow the reported effect is said to come about
methodmethodhow the paper produced its evidence
object of studyobject_of_studywhat the paper is about — the thing it investigates
phenomenonphenomenonthe effect or regularity under study
research questionresearch_questionthe question the paper sets itself
sensesensesa distinct use of a term, quoted where the paper fixes it

The paper

The full text is not reproduced here. This article is not cleared for redistribution, so the page carries the tag layer only. Its evidence sentences are withheld; the grounding status remains with each tag, and the article itself is at https://doi.org/10.2147/jmdh.s104807. The reading view exists for the papers whose licence permits it.

Every tag on this page

claim_relations 4 · claim_type 1 · concept_edges 8 · concepts 16 · content_tags 21 · contribution 1 · controls 4 · limitations 4 · mechanisms 11 · method 1 · object_of_study 1 · phenomenon 1 · research_question 1 · senses 6

Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; 8 of 8 relations here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.

facettagfieldconf.whose words
object_of_studyA CONCEPT WHOSE OWN VOCABULARY IS THE EXAMPLE - information bias, itself 'otherwise known as misclassification', whose two main subtypes carry four names each in a single sentence apiece, with the alternatives listed and never distinguished
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object_of_studythe paper's words
research_questionwhich forms of information bias arise in observational and experimental medical research, how each is recognised, and what can be done about it at design, measurement and analysis
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research_questionthe paper's words
contributiona short taxonomy of information bias - self-reporting bias (social desirability, recall), measurement error bias, confirmation bias - each with its named alternatives, its typical study design, and an adjustment or prevention strategy
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contributionthe paper's words
claim_typemethod
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claim_typethe paper's words
phenomenonsystematic error introduced by how a measurement is obtained rather than by whom it is obtained from - and which is often introduced unintentionally, so that it is hard to recognise even by the researcher who caused it
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phenomenonthe paper's words
methodreview
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also in: review
methodthe paper's words
mechanismsONE ERROR, FOUR NAMES, IN ONE SENTENCE: `Quotation withheld` Four names offered as interchangeable, with no test given for telling them apart - and one of them, `measurement bias`, names the consequence while the others name the cause
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mechanisms[0]0.95the tagger's words
mechanismsAND AGAIN FOR THE THIRD FORM: `Quotation withheld` And the paper's subject itself: `Information bias, otherwise known as misclassification`. Three concepts, four, four and two names, in one short review - the corpus holds papers that count 138 definitions of a term; this is the same phenomenon at the scale of a synonym list, and it is not remarked on
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mechanisms[1]0.95the tagger's words
mechanismsAND THE TOP-LEVEL DEFINITION IS A GENUS AND A DIFFERENTIA: `Quotation withheld In health studies, bias can arise from two different sources; the approach adopted for selecting subjects ... or the approach adopted for collecting or measuring data ... termed as selection bias and information bias.` The partition is by WHERE THE ERROR ENTERS, not by what it does to the estimate - which is why the same arithmetic consequence can belong to either
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mechanisms[2]0.95the tagger's words
mechanismsAND A DISTINCTION THE FIELD IS EXPLICITLY WARNED NOT TO COLLAPSE: `Quotation withheld` The warning exists because the two are routinely conflated, and the cost of conflating them is that the standard toolbox appears to cover both and covers one
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mechanisms[3]0.95the tagger's words
mechanismsAND A TERM DEFINED BY WHAT IT IGNORES: `An analysis that ignores the effect of measurement error on the results can be referred to as a naive analysis.` Its consequences are given as `inconsistent (or biased) and/or inefficient estimators of regression parameters`. A name for the default practice, which is the rhetorical move that makes an omission visible
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mechanisms[4]0.85the tagger's words
mechanismsAND THE MECHANISM OF RECALL BIAS IS SPELLED OUT AS A CHAIN: `in a case-control study, Quotation withheld As such, true exposure might be underreported in healthy controls and overreported in the cases. The size of the difference ... will consequently be inflated, and, in turn, the observed odds ratio would also increase.` The bias has a direction, and the direction is predictable from the design - which is what makes it adjustable at all
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mechanisms[5]0.95the tagger's words
mechanismsAND THE FIX FOR SELF-REPORTING IS VALIDATION AGAINST SOMETHING ELSE: `internal validation` compares responses `with other data collection methods, such as laboratory measurements`; `external validation` uses `medical record checks or reports from family or friends`. The instrument is checked against a second instrument, never against the truth - and the paper then says the laboratory measurements are themselves `often subject to measurement errors`
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mechanisms[6]0.95the tagger's words
mechanismsAND THE VALIDATION HAS ITS OWN SAMPLING PROBLEM: `It is important to have a random selection of individuals so that results from the validation can be generalized to any group of participants. When the sampling approach is not random and subjective, the results from the validation study can only apply to the same group of individuals.` A correction factor inherits the scope of the study that produced it - polman2011's MAGNIMS refusal, in a different discipline
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mechanisms[7]0.95the tagger's words
mechanismsAND A WHOLE DESIGN IS DEMOTED ON THE STRENGTH OF ONE BIAS: `bias often accompanies results from case-control studies. Hence, case-control studies can be conducted in order to generate a research hypothesis, but not to evaluate prognoses or treatment effects.` A study design assigned a permitted use - the same move donnelly2019 makes about a definition, here made about a method
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mechanisms[8]0.95the tagger's words
mechanismsAND THE ONE FIELD THAT DOES ADJUST FOR MEASUREMENT ERROR IS NAMED: `Quotation withheld` Where a number has to survive cross-examination, its error is modelled - the practice follows the consequence, not the methodology
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mechanisms[9]0.95the tagger's words
mechanismsAND THE AGREEMENT BETWEEN SELF-REPORT AND RECORDS IS DISEASE-SPECIFIC: `a high agreement was found between self-reported questionnaires and medical record diagnoses of diseases such as diabetes, hypertension, myocardial infarction, and stroke but not for heart failure.` The instrument is not uniformly valid across the things it measures, which is exactly what prigerson2009's differential item functioning analysis tests for and deletes
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mechanisms[10]0.95the tagger's words
limitationsTHE FOUR NAMES ARE LISTED AND NEVER SEPARATED. `measurement error, instrumental error, measurement imprecision, or measurement bias` are offered as one thing; `confirmatory, ascertainment, or observer bias` likewise. Some of these are not synonyms in ordinary use - *instrumental* error is a subclass of measurement error, and *observer* bias is usually distinguished from *confirmation* bias by who holds the belief. A review of error that hands the reader an unsorted synonym list is reproducing the problem it describes
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limitations[0]0.95the tagger's words
limitationsAND THE ADVICE IS ADMITTED TO BE HARD TO FOLLOW: `Bias is often not accounted for in practice. Even though a number of adjustment and prevention methods ... are available, applying them can be rather challenging due to limited time and resources. For example, measurement error bias properties might be difficult to detect, particularly if there is a lack of information about the measuring instrument.` The adjustment methods all require knowing the error distribution, and the error distribution requires a validation study that is `expensive`
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limitations[1]0.95the tagger's words
limitationsAND THE VALIDATION CHAIN BOTTOMS OUT ON ANOTHER MEASUREMENT: laboratory measurements are the recommended standard for validating self-report, and they are `often subject to measurement errors` - `in a validation study to estimate sodium intake using a 24-hour urinary excretion method, the estimated sodium intake tended to be lower than the true amount`. There is no step in the chain that touches the true value, and the paper says so about its own recommended remedy
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limitations[2]0.95the tagger's words
limitationsAND CONFIRMATION BIAS IS THE ONE WITH NO ADJUSTMENT METHOD AT ALL: the remedies offered are independent checks, blinding, and `specific education and training programs`, and the conclusion is `it is important to accept that bias is a part of investigations. Quantifying this inevitable bias and its potential sources must be part of well-developed conclusions.` The paper's title promises adjustment methods; for the third of its three biases there are none
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limitations[3]0.95the tagger's words
controlsvalidating a self-reporting instrument against laboratory measurements (internal) or medical records and family report (external) before using it
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eliminates: social desirability bias in answers about drug use, income, diet or violence · outcome: partial
controls[0]0.95the tagger's words
controlsrequiring the validation sample to be randomly selected
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eliminates: a correction factor that applies only to the group it was derived from · outcome: held
controls[1]0.95the tagger's words
controlschoosing a short recall period, stratifying it by how many events a participant had, and using memory aids and diaries
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eliminates: recall error scaling with the length of the period being remembered · outcome: partial
controls[2]0.95the tagger's words
controlsblinding or masking, single or double, and independent checks across laboratories
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eliminates: confirmation bias in any step that requires human judgment · outcome: partial
controls[3]0.95the tagger's words
conceptsBias
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also in: Bias
concepts[0]0.95the paper's words
conceptsany systematic error in the design, conduct, or analysis of a study
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concepts[1]0.95the paper's words
conceptsselection bias
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concepts[2]0.95the paper's words
conceptsinformation bias
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concepts[3]0.95the paper's words
conceptsmeasurement error
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concepts[4]0.95the paper's words
conceptsmeasurement bias
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concepts[5]0.95the paper's words
conceptsconfirmation bias
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concepts[6]0.95the paper's words
conceptsobserver bias
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also in: observer bias
concepts[7]0.95the paper's words
conceptsrandom sampling
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concepts[8]0.95the paper's words
conceptsmeasurement error variability
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concepts[9]0.95the paper's words
conceptsAn analysis that ignores the effect of measurement error on the results
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concepts[10]0.85the paper's words
conceptsa naïve analysis
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concepts[11]0.85the paper's words
conceptscases
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also in: cases
concepts[12]0.95the paper's words
conceptshealthy controls
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concepts[13]0.95the paper's words
conceptsThe size of the difference between the observed rates of exposure to risk factors in cases and controls
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concepts[14]0.95the paper's words
conceptsthe observed odds ratio
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concepts[15]0.95the paper's words
senses`bias` - `any systematic error in the design, conduct, or analysis of a study`; split by WHERE it enters into `selection bias` and `information bias`
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senses[0]0.95the tagger's words
senses`information bias` - `otherwise known as misclassification`; error originating in `the approach that is utilized to obtain or confirm study measurements`
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senses[1]0.95the tagger's words
senses`measurement error` = `instrumental error` = `measurement imprecision` = `measurement bias` - four names presented as interchangeable in one sentence, with no criterion for choosing between them
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senses[2]0.95the tagger's words
senses`confirmation bias` - `otherwise known as confirmatory, ascertainment, or observer bias`: `a decision is made according to the subject's preconceptions, beliefs, or preferences`
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senses[3]0.95the tagger's words
senses`naive analysis` - `An analysis that ignores the effect of measurement error on the results`. A name given to the default practice so that it can be argued against
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senses[4]0.85the tagger's words
senses`systematic` vs `random` error - systematic deviations are `either consistently higher or lower than the true values`; random ones are `not consistent`, follow a distribution, and are called `multiplicative or non-gaussian` when proportional to the measurement
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senses[5]0.95the tagger's words
claim_relationsextends → the existing bias literature, which the paper says has discussed types of bias while 'the problem of bias is still frequently ignored in practice'
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claim_relations[0]0.95the tagger's words
claim_relationscritiques → the naive analysis - the standard practice of ignoring measurement error, which yields 'inconsistent (or biased) and/or inefficient estimators'
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claim_relations[1]0.85the tagger's words
claim_relationscritiques → the use of case-control studies for anything beyond hypothesis generation, given that 'bias often accompanies results from case-control studies'
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claim_relations[2]0.95the tagger's words
claim_relationsextends → forensic toxicology, named as the one field with 'the most theoretical understanding of measurement bias', from which medical research is asked to learn
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claim_relations[3]0.95the tagger's words
concept_edgesmeasurement error —same-as→ measurement bias
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the relation itself is separately evidenced · strength of the relation: 0.9 · note: 'If these errors…' Four names, and they are not obviously synonyms: instrumental error names a source, imprecision names a property of the instrument, and measurement bias names what the error does to the estimate. Tagged as the paper states it, and the un-sorted list is recorded as a limitation · the relation stated: measurement error, instrumental error, measurement imprecision and measurement bias are offered as names for one thing, in one sentence, with no test for telling them apart
concept_edges[0]0.95the tagger's words
concept_edgesconfirmation bias —same-as→ observer bias
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the relation itself is separately evidenced · strength of the relation: 0.9 · note: 'Placing emphasis…' The second four-name list in one review. In ordinary use 'observer bias' is the observer's expectation affecting a measurement and 'confirmation bias' is a search strategy over evidence; here they are one entry · the relation stated: confirmation, confirmatory, ascertainment and observer bias are given as names for deciding according to one's preconceptions
concept_edges[1]0.95the tagger's words
concept_edgesBias —operationalised-as→ any systematic error in the design, conduct, or analysis of a study
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the relation itself is separately evidenced · strength of the relation: 0.95 · note: 'Bias can be defined…' Systematic is doing all the work - the definition excludes random error by construction, and the paper then spends its longest section on random measurement error, which is systematic in its effect on an estimate · the relation stated: bias is defined as systematic error anywhere in a study, which is what allows the split by point of entry rather than by effect
concept_edges[2]0.95the tagger's words
concept_edgesselection bias —distinct-from→ information bias
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the relation itself is separately evidenced · strength of the relation: 0.95 · note: 'In health studies…' A clean two-way split with a stated criterion, which is more than most of the taxonomies in this corpus manage · the relation stated: the two sources are the approach to choosing subjects and the approach to measuring them - a partition by point of entry, not by consequence
concept_edges[3]0.95the tagger's words
concept_edgesrandom sampling —distinct-from→ measurement error variability
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the relation itself is separately evidenced · strength of the relation: 0.95 · note: 'However, RANDOM…' The warning is printed because the conflation is common, and the cost is specific: the confidence interval looks complete and covers one of two error sources · the relation stated: sampling variability is handled by standard statistical methods and measurement error uncertainty is not, so treating them as one hides the second
concept_edges[4]0.95the tagger's words
concept_edgesAn analysis that ignores the effect of measurement error on the results —same-as→ a naïve analysis
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the relation itself is separately evidenced · strength of the relation: 0.9 · note: 'An analysis that…' Naming the default is how an omission becomes visible. Compare carroll2007's 'thinness' for missing fidelity data: both fields coined a word for a thing that is not there · the relation stated: the ordinary analysis, done without accounting for measurement error, is given a name - and the name is the argument
concept_edges[5]0.85the tagger's words
concept_edgescases —contrasted-with→ healthy controls
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the relation itself is separately evidenced · strength of the relation: 0.95 · note: 'study, CASES…' The bias is not noise; it has a sign that follows from the design, which is why the paper can say what it does to the odds ratio · the relation stated: cases recall exposure more readily than controls, so the same true history is reported at different rates on the two sides of the comparison
concept_edges[6]0.95the tagger's words
concept_edgesThe size of the difference between the observed rates of exposure to risk factors in cases and controls —causes→ the observed odds ratio
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the relation itself is separately evidenced · strength of the relation: 0.95 · note: 'The size of the difference…' A named error class traced all the way to the published statistic - three steps, each stated, which is what makes recall bias adjustable rather than merely deplorable · the relation stated: the recall asymmetry inflates the observed exposure difference, and the inflated difference raises the odds ratio the study reports
concept_edges[7]0.95the tagger's words
content_tagssuch errors are often called measurement error, instrumental error, measurement imprecision or measurement bias
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content_tags.findings[0]0.95the tagger's words
content_tagsconfirmation bias is also called confirmatory, ascertainment or observer bias
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content_tags.findings[1]0.95the tagger's words
content_tagsAND A DISTINCTION THE FIELD IS WARNED NOT TO COLLAPSE: `random sampling should not be confused with measurement error variability ... [standard methods] do not account for uncertainty due to measurement error`
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content_tags.findings[2]0.95the tagger's words
content_tagsAND A NAME FOR THE DEFAULT PRACTICE: `An analysis that ignores the effect of measurement error ... can be referred to as a naive analysis`
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content_tags.findings[3]0.85the tagger's words
content_tagsAND RECALL BIAS HAS A SIGN: cases `more likely to recall exposure ... than healthy controls`, so the difference `will consequently be inflated, and, in turn, the observed odds ratio would also increase`
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content_tags.findings[4]0.95the tagger's words
content_tagsAND ONE FIELD DOES ADJUST FOR IT: measurement error bias is `rarely ... adjusted for ... except in the field of forensic medicine`, where it is `particularly relevant for their type of research`
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content_tags.findings[5]0.95the tagger's words
content_tagsAND A STUDY DESIGN IS ASSIGNED A PERMITTED USE: `case-control studies can be conducted in order to generate a research hypothesis, but not to evaluate prognoses or treatment effects`
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content_tags.findings[6]0.95the tagger's words
content_tagsAND SELF-REPORT AGREES WITH THE RECORD FOR SOME DISEASES AND NOT OTHERS: high agreement for `diabetes, hypertension, myocardial infarction, and stroke but not for heart failure`
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content_tags.findings[7]0.95the tagger's words
content_tagsAND BIAS CAN BE DELIBERATE: `Often bias is unintentionally introduced into a study by researchers, making it difficult to recognize, but it can also be introduced intentionally. Thus, bias remains a very sensitive issue to address and discuss openly`
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content_tags.findings[8]0.95the tagger's words
content_tags`any systematic error in the design, conduct, or analysis of a study`, split into `selection bias` and `INFORMATION BIAS` by where the error enters
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also in: bias
content_tags.definitions[0]0.95the tagger's words
content_tags`otherwise known as misclassification` - it `originates from the approach that is utilized to obtain or confirm study measurements`
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content_tags.definitions[1]0.95the tagger's words
content_tagsfour names in one sentence for `observed measurements [that] will differ from the actual values`, with no criterion offered for choosing between them
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content_tags.definitions[2]0.95the tagger's words
content_tags`otherwise known as confirmatory, ascertainment, or observer bias` - `a decision is made according to the subject's preconceptions, beliefs, or preferences`
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content_tags.definitions[3]0.95the tagger's words
content_tags`An analysis that ignores the effect of measurement error on the results` - a name for the default practice
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content_tags.definitions[4]0.85the tagger's words
content_tags`the often-marginalized measurement error bias` is the paper's own description of the second
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content_tags.quantities[1]0.95the tagger's words
content_tags`The size of the difference ... will consequently be inflated`
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content_tags.quantities[2]0.95the tagger's words
content_tagsself-report is validated against laboratory measurement; laboratory measurement is `often subject to measurement errors`; a 24-hour urinary excretion validation of sodium intake `tended to be lower than the true amount`. Every step compares one instrument with another, and the paper says so about its own recommended remedy
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content_tags.statistics[0]0.95the tagger's words
content_tags`Commonly used statistical methods can address the sampling variability during data analysis, but they do not account for uncertainty due to measurement error.` A confidence interval computed the usual way looks complete and covers one of two error sources
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content_tags.statistics[1]0.95the tagger's words
content_tags`the observed measurements deviate from true values in a consistent manner` - correctable by calibration against a reference measurement
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
content_tags.variables[0]0.95the tagger's words
content_tags`the deviation ... is not consistent`, follows a distribution, and when proportional to the measured amount is `referred to as multiplicative or non-gaussian errors`
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also in: random error
content_tags.variables[1]0.95the tagger's words
content_tagsthe variable the reviewer can actually set - `a short recall period is preferable to a long one, particularly when asking participants about routine or frequent events`
Quotation withheld — this record is not cleared for redistribution. The sentence is in the paper at the link above.
also in: recall period
content_tags.variables[2]0.95the tagger's words

Interpretive choices

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What was deliberately not tagged, and why, is recorded per paper by the tagger. Where a paper has no such record, this page says so rather than implying that nothing was declined.

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