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Enhancing the Power of Genetic Association Studies through the Use of Silver Standard Cases Derived from Electronic Medical Records. e63481
by
McCormick, Wayne
, McDavid, Andrew
, Newton, Katherine M
, Crane, Paul K
, Harrison, Robert
, Hart, Eugene
, Kukull, Walter A
, Weston, Noah
, Ehrlich, Kelly
, Crosslin, David R
in
Data processing
2013
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Enhancing the Power of Genetic Association Studies through the Use of Silver Standard Cases Derived from Electronic Medical Records. e63481
by
McCormick, Wayne
, McDavid, Andrew
, Newton, Katherine M
, Crane, Paul K
, Harrison, Robert
, Hart, Eugene
, Kukull, Walter A
, Weston, Noah
, Ehrlich, Kelly
, Crosslin, David R
in
Data processing
2013
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Do you wish to request the book?
Enhancing the Power of Genetic Association Studies through the Use of Silver Standard Cases Derived from Electronic Medical Records. e63481
by
McCormick, Wayne
, McDavid, Andrew
, Newton, Katherine M
, Crane, Paul K
, Harrison, Robert
, Hart, Eugene
, Kukull, Walter A
, Weston, Noah
, Ehrlich, Kelly
, Crosslin, David R
in
Data processing
2013
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Enhancing the Power of Genetic Association Studies through the Use of Silver Standard Cases Derived from Electronic Medical Records. e63481
Journal Article
Enhancing the Power of Genetic Association Studies through the Use of Silver Standard Cases Derived from Electronic Medical Records. e63481
2013
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Overview
The feasibility of using imperfectly phenotyped \"silver standard\" samples identified from electronic medical record diagnoses is considered in genetic association studies when these samples might be combined with an existing set of samples phenotyped with a gold standard technique. An analytic expression is derived for the power of a chi-square test of independence using either research-quality case/control samples alone, or augmented with silver standard data. The subset of the parameter space where inclusion of silver standard samples increases statistical power is identified. A case study of dementia subjects identified from electronic medical records from the Electronic Medical Records and Genomics (eMERGE) network, combined with subjects from two studies specifically targeting dementia, verifies these results.
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