Semiparametric methods for evaluating risk prediction markers in case-control studies.
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Partial summary measures of the predictiveness curveThe potential of genes and other markers to inform about risk.Assessing risk prediction models in case-control studies using semiparametric and nonparametric methods.Semiparametric methods for evaluating the covariate-specific predictiveness of continuous markers in matched case-control studiesExtensions of net reclassification improvement calculations to measure usefulness of new biomarkers.Estimating improvement in prediction with matched case-control designsIdentification of sparse neural functional connectivity using penalized likelihood estimation and basis functions.A parametric ROC model-based approach for evaluating the predictiveness of continuous markers in case-control studies.LOGISTIC REGRESSION ANALYSIS WITH STANDARDIZED MARKERS.More Accurate Oral Cancer Screening with Fewer Salivary Biomarkers.
P2860
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P2860
Semiparametric methods for evaluating risk prediction markers in case-control studies.
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
2009年论文
@zh
2009年论文
@zh-cn
name
Semiparametric methods for evaluating risk prediction markers in case-control studies.
@ast
Semiparametric methods for evaluating risk prediction markers in case-control studies.
@en
type
label
Semiparametric methods for evaluating risk prediction markers in case-control studies.
@ast
Semiparametric methods for evaluating risk prediction markers in case-control studies.
@en
prefLabel
Semiparametric methods for evaluating risk prediction markers in case-control studies.
@ast
Semiparametric methods for evaluating risk prediction markers in case-control studies.
@en
P2860
P356
P1433
P1476
Semiparametric methods for evaluating risk prediction markers in case-control studies.
@en
P2093
Margaret Sullivan Pepe
Ying Huang
P2860
P304
P356
10.1093/BIOMET/ASP040
P407
P577
2009-10-12T00:00:00Z