Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

about

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

Item

http://www.wikidata.org/entity/Q47249010

description

2017 nî lūn-bûn

@nan

2017年の論文

@ja

2017年学术文章

@wuu

2017年学术文章

@zh-cn

2017年学术文章

@zh-hans

2017年学术文章

@zh-my

2017年学术文章

@zh-sg

2017年學術文章

@yue

2017年學術文章

@zh

2017年學術文章

@zh-hant

name

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

@en

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

@nl

type

Item

label

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

@en

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

@nl

prefLabel

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

@en

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

@nl

P1476

Correcting Classifiers for Sample Selection Bias in Two-Phase Case-Control Studies.

@en

P2093

Christiane Fuchs

http://www.w3.org/2001/XMLSchema#string

Norbert Krautenbacher

http://www.w3.org/2001/XMLSchema#string

P2860

Using Inverse Probability Bootstrap Sampling to Eliminate Sample Induced Bias in Model Based Analysis of Unequal Probability Samples

Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach

ROCR: visualizing classifier performance in R

pROC: an open-source package for R and S+ to analyze and compare ROC curves

A simple method to adjust clinical prediction models to local circumstances.

Assessing risk prediction models in case-control studies using semiparametric and nonparametric methods.

An empirical comparison of respondent-driven sampling, time location sampling, and snowball sampling for behavioral surveillance in men who have sex with men, Fortaleza, Brazil.

Validation and updating of predictive logistic regression models: a study on sample size and shrinkage.

Baseline integrated behavioural and biological assessment among most at-risk populations in six high-prevalence states of India: design and implementation challenges.

Two-stage designs for gene-disease association studies with sample size constraints.

P31

scholarly article

P478

2017

http://www.w3.org/2001/XMLSchema#string

P50

Fabian J. Theis

P577

2017-09-24T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P921

bias

P932

5632994

http://www.w3.org/2001/XMLSchema#string