Accounting for Measurement Error and Misclassification in Variables ...

In multivariate regressions, even when the other variables (i.e., those not generated from data mining) are measured without error, the presence of a data mined ...

However, because prediction is almost always imperfect, variables generated from the first-stage data mining models inevitably contain ...

Accounting for Measurement Error and Misclassification in Variables ...

Therefore, coefficient estimates with errors are inconsistent. Page 5. Yang et al.: Accounting for Measurement Error in Data Mining Generated Variables.

Accounting for Measurement Error and Misclassification in Variables ...

observed levels of predictive performance in data mining models, in terms of precision and recall. Hence,. the errors we simulate and the biases we observe are ...

Accounting for Measurement Error and Misclassification in Variables ...

However, because prediction is almost always imperfect, variables generated from the first stage data mining models inevitably contain measurement error or ...

Accounting for Measurement Error and Misclassification in Variables ...

Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining · Mochen Yang · Gediminas ...

Mind the Gap: Accounting for Measurement Error and ... - EconPapers

Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining. Mochen Yang ([email protected]), ...

Mind the Gap: Accounting for Measurement Error and ... - Ex Libris

However, because prediction is almost always imperfect, variables generated from the first-stage data mining models inevitably contain measurement error or ...

Accounting for measurement error in biomarker data and ...

This task is usually carried out in two steps–clustering and risk factor assessment. However, two sources of measurement error arise in these problems. The ...

Mind the Gap: Accounting for Measurement Error and Misclassi

However, because prediction is almost always imperfect, variables generated from the first-stage data mining models inevitably contain measurement error or ...

Accounting for Measurement Error and Misclassification in Variables ...

This error should be taken into account in the estimation of the model, to avoid biased estimators. A general approach that exists in the literature is the ...

Accounting for measurement error: A critical but often overlooked ...

Part of the inevitable variability of these measurements is due to the finite consistency and read-out precision of the instrument used to measure the object, ...

Accounting for measurement error and misclassification in variables ...

Fingerprint. Dive into the research topics of 'Mind the gap: Accounting for measurement error and misclassification in variables generated via ...

The hidden challenges: Measurement error and misclassification of ...

In particular, measurement error can occur when the instruments or methods used to measure variables are imprecise or inaccurate, making the ...

Measurement Error and Misclassification in Orthopedics - YouTube

Measurement error refers to inaccurate measurement of continuous variables whereas misclassification refers to assigning subjects in the ...

Measurement Error in Dependent Variables: An Illustration within ...

Using simulation analyses of commonly-used accounting variables as well as a case-study analysis of Google ticker searches as a measure of investor attention, ...

Measurement error and misclassification in electronic medical records

Common statistics used to quantify misclassification for dichotomous variables include sensitivity, specificity, positive predictive value, and negative ...

Lecture Notes on Measurement Error

Measurement Error in Dummy Variables There is an interesting special ... misclassification of a dummy variable cannot lead to classical measurement er-.

STRATOS guidance document on measurement error and ...

Measurement error and misclassification of variables frequently occur in epi- demiology and involve variables important to public health. Their presence can.

STRATOS guidance document on measurement error and ...

Measurement error and misclassification of variables frequently occur in epidemiology and involve variables important to public health.