Which reference class is evoked?

AbstractTwo distinct issues are sometimes confused in the base rate literature: Why do people make logical mistakes in the assessment of probabilities? and why do subjects not use base rates the way experimenters do? The latter problem may often reflect differences in an implicit reference class rather than a disinclination to update a base rate by Bayes' theorem. Also important are considerations concerning the interaction of several potentially relevant base rates.

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REFERENCE CLASSES AND MULTIPLE INHERITANCES

International Journal of Uncertainty Fuzziness and Knowledge-Based Systems ◽

10.1142/s0218488595000086 ◽

1995 ◽

Vol 03 (01) ◽

pp. 79-91 ◽

Cited By ~ 8

Author(s):

PEI WANG

Keyword(s):

Probability Theory ◽

Reference Class ◽

New Approach ◽

Class A ◽

Reasoning System ◽

Special Cases ◽

Reference Class Problem ◽

Reference Classes ◽

Better Than

The reference class problem in probability theory and the multiple inheritances (extensions) problem in non-monotonic logics are special cases of conflicting beliefs. One popular solution accepted in the two domains is the specificity principle. By analyzing an example, several factors beyond specificity are found to be relevant to the priority of a reference class. A new approach, Non-Axiomatic Reasoning System (NARS), is discussed, where these factors are all taken into account. It is argued that the solution provided by NARS is better than the solutions provided by probability theory and non-monotonic logics.

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A Stage-Theoretical Account of Diachronic Identity

Metaphysica ◽

10.1515/mp-2018-0016 ◽

2018 ◽

Vol 19 (2) ◽

pp. 259-272

Author(s):

H. E. Baber

Keyword(s):

Reference Class ◽

Ordinary Object ◽

Ordinary Objects ◽

Theoretical Account ◽

Reference Classes

Abstract Diachronic identity is understood as an identity holding between something existing at one time and something existing at another time. On the stage view, however, ordinary objects are instantaneous stages that do not exist at other times so diachronic identity is, at best, problematic. On account proposed here a name does not, as Sider and others suggest, denote a stage concurrent with its utterance. Rather, at any time, t, a name of an ordinary object designates a stage-at-t as its primary referent and refers indeterminately over it and all and only those stages counterpart-related to it—its reference class at t. At any time, t, a at t1 is the same object as b at t2 iff for every stage x counterpart-related to a’s stage-at t and every stage y counterpart-related to b’s stage-at-t, x=y. Diachronic identity statements, therefore, assert strict identities—between concurrent stages. Ordinarily names select the same reference classes at every time so, in ordinary cases, identity statements are not ‘occasional’. In fission cases names select different reference classes at different times. Where a becomes b and c, at any pre-fission time ‘a’, ‘b’, and ‘c’ have same the primary referent and so select the same reference class—therefore, before fission b is the same object as c. At any post-fission time ‘b’ and ‘c’ select different reference classes—so after fission b is not the same object as c. Identity is not occasional but, in extraordinary cases, identity statements are—because reference is.

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Personalizing Evidence for Shoulder Fracture Patients Using an Extended Instrumental Variable Causal Forest Algorithm

10.22541/au.163251723.37240855/v1 ◽

2021 ◽

Author(s):

John M. Brooks ◽

Cole G. Chapman ◽

Sarah Floyd ◽

Brian K. Chen ◽

Charles A. Thigpen ◽

...

Keyword(s):

Instrumental Variable ◽

Day Treatment ◽

Early Surgery ◽

Fee For Service ◽

Medicare Beneficiaries ◽

Reference Class ◽

Shoulder Fracture ◽

Population Classification ◽

Reference Classes ◽

Surgery Rates

Objective: To assess the ability of an extended Instrumental Variable Causal Forest Algorithm (IV-CFA) to provide personalized evidence of early surgery effects on benefits and detriments for elderly shoulder fracture patients. Data Sources/Study Setting: Population of 72,751 fee-for-service Medicare beneficiaries with proximal humerus fractures (PHFs) in 2011 who survived a 60-day treatment window after an index PHF and were continuously Medicare fee-for-service eligible over the period 12 months prior to index to the minimum of 12 months after index or death. Study Design: IV-CFA estimated early surgery effects on both beneficial and detrimental outcomes for each patient in the study population. Classification and regression trees (CART) were applied to these estimates to create patient reference classes. Two-stage least squares (2SLS) estimators were applied to patients in each reference class to scrutinize the estimates relative to the known 2SLS properties. Principal Findings: This approach uncovered distinct reference classes of elderly PHF patients with respect to early surgery effects on benefit and detriment. Older, frailer patients with more comorbidities, and lower utilizers of healthcare were less likely to gain benefit and more likely to have detriment from early surgery. Reference classes were characterized by the appropriateness of early surgery rates with respect to benefit and detriment. Conclusions: Extended IV-CFA provides an illuminating method to uncover reference classes of patients based on treatment effects using observational data with a strong instrumental variable. This study isolated reference classes of new PHF patients in which changes in early surgery rates would improve patient outcomes. The inability to measure fracture complexity in Medicare claims means providers will need to discuss the appropriateness of these estimates to patients within a reference class in context of this missing information.

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Fallacy and controversy about base rates

Behavioral and Brain Sciences ◽

10.1017/s0140525x00041339 ◽

1996 ◽

Vol 19 (1) ◽

pp. 31-32 ◽

Cited By ~ 3

Author(s):

Isaac Levi

Keyword(s):

Base Rate ◽

Probability Judgment ◽

Reference Class ◽

Probability Judgments ◽

Base Rates ◽

Target Article ◽

Class Information ◽

The Difference ◽

Indeterminate Probability

AbstractKoehler's target article attempts a balanced view of the relevance of knowledge of base rates to judgments of subjective or credal probability, but he is not sensitive enough to the difference between requiring and permitting the equation of probability judgments with base rates, the interaction between precision of base rate and reference class information, and the possibility of indeterminate probability judgment.

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Personalizing Evidence for Shoulder Fracture Patients Using an Extended Instrumental Variable Causal Forest Algorithm

10.22541/au.163251723.37240855/v2 ◽

2021 ◽

Author(s):

John M. Brooks ◽

Cole G. Chapman ◽

Sarah Floyd ◽

Brian K. Chen ◽

Charles A. Thigpen ◽

...

Keyword(s):

Instrumental Variable ◽

Day Treatment ◽

Early Surgery ◽

Fee For Service ◽

Medicare Beneficiaries ◽

Reference Class ◽

Shoulder Fracture ◽

Population Classification ◽

Reference Classes ◽

Surgery Rates

Objective: To assess the ability of an extended Instrumental Variable Causal Forest Algorithm (IV-CFA) to provide personalized evidence of early surgery effects on benefits and detriments for elderly shoulder fracture patients. Data Sources/Study Setting: Population of 72,751 fee-for-service Medicare beneficiaries with proximal humerus fractures (PHFs) in 2011 who survived a 60-day treatment window after an index PHF and were continuously Medicare fee-for-service eligible over the period 12 months prior to index to the minimum of 12 months after index or death. Study Design: IV-CFA estimated early surgery effects on both beneficial and detrimental outcomes for each patient in the study population. Classification and regression trees (CART) were applied to these estimates to create patient reference classes. Two-stage least squares (2SLS) estimators were applied to patients in each reference class to scrutinize the estimates relative to the known 2SLS properties. Principal Findings: This approach uncovered distinct reference classes of elderly PHF patients with respect to early surgery effects on benefit and detriment. Older, frailer patients with more comorbidities, and lower utilizers of healthcare were less likely to gain benefit and more likely to have detriment from early surgery. Reference classes were characterized by the appropriateness of early surgery rates with respect to benefit and detriment. Conclusions: Extended IV-CFA provides an illuminating method to uncover reference classes of patients based on treatment effects using observational data with a strong instrumental variable. This study isolated reference classes of new PHF patients in which changes in early surgery rates would improve patient outcomes. The inability to measure fracture complexity in Medicare claims means providers will need to discuss the appropriateness of these estimates to patients within a reference class in context of this missing information.

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Improving Understanding of Diagnostic Test Outcomes

Medical Decision Making ◽

10.1177/0272989x18758293 ◽

2018 ◽

Vol 38 (5) ◽

pp. 573-583 ◽

Cited By ~ 2

Author(s):

Alaina N. Talboy ◽

Sandra L. Schneider

Keyword(s):

Diagnostic Test ◽

Test Method ◽

Congruent Condition ◽

Visual Aids ◽

Reference Class ◽

Medical Test ◽

Diagnostic Values ◽

Reference Classes ◽

The Impact ◽

Test Outcomes

Background. Understanding diagnostic test outcomes requires determining the positive predictive value (PPV) of the test, which most laypeople and medical professionals struggle to do. Despite advances found with frequency formats and visual aids, less than 40% of people can typically identify this value. This study tests the impact of using congruent reference classes in problem-question pairings, evaluates the role of numeracy, and assesses how diagnostic value estimates affect the reported likelihood to use the test. Method. A 3 × 2, Pairing (congruent test-focus, congruent condition-focus, incongruent) × Response Format (frequency, percentage) mixed design experiment was conducted, in which participants answered diagnostic questions about 7 medical problems presented in a format focusing either on the reference class of those who test positive or those who have the condition. Answer accuracy, numeracy, and ratings of likelihood to use estimates were assessed. Results. Focusing on the congruent test reference class allowed 87% of participants to consistently identify the PPV, and focusing on the congruent condition reference class led 63% of participants to consistently identify the sensitivity (SEN). Aligning reference classes was especially beneficial for those with lower numeracy, increasing accuracy on problems from 21% for incongruent pairings to 66% for congruent pairings. Ratings of likelihood to use the test were closely tied to participants’ estimates of diagnostic values, regardless of the accuracy of those estimates. Conclusions. Although often overlooked, a straightforward mapping of reference classes from the relevant diagnostic information to the question of interest reduces confusion and substantially increases accuracy in estimates of diagnostic values. These findings can be used to strengthen training in the assessment of uncertainties associated with medical test results.

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More Accurate Learning of k-DNF Reference Classes

Proceedings of the AAAI Conference on Artificial Intelligence ◽

10.1609/aaai.v34i04.5864 ◽

2020 ◽

Vol 34 (04) ◽

pp. 4385-4393

Author(s):

Brendan Juba ◽

Hengxuan Li

Keyword(s):

Machine Learning ◽

Predictive Power ◽

Data Distribution ◽

Error Rates ◽

Query Point ◽

Reference Class ◽

Reference Classes ◽

Suitable Reference ◽

The Given ◽

New Algorithms

In machine learning, predictors trained on a given data distribution are usually guaranteed to perform well for further examples from the same distribution on average. This often may involve disregarding or diminishing the predictive power on atypical examples; or, in more extreme cases, a data distribution may be composed of a mixture of individually “atypical” heterogeneous populations, and the kind of simple predictors we can train may find it difficult to fit all of these populations simultaneously. In such cases, we may wish to make predictions for an atypical point by selecting a suitable reference class for that point: a subset of the data that is “more similar” to the given query point in an appropriate sense. Closely related tasks also arise in applications such as diagnosis or explaining the output of classifiers. We present new algorithms for computing k-DNF reference classes and establish much stronger approximation guarantees for their error rates.

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