(Q30594336)

25 June 2017

title

EMLasso: logistic lasso with missing data (English)

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25 June 2017

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O Thas

2

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author name string

N Sabbe

series ordinal

1

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25 June 2017

J-P Ottoy

series ordinal

3

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25 June 2017

language of work or name

English

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publication date

25 February 2013

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25 June 2017

published in

Statistics in Medicine

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25 June 2017

volume

32

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25 June 2017

issue

18

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25 June 2017

page(s)

3143-3157

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Development of a multicomponent prediction model for acute esophagitis in lung cancer patients receiving chemoradiotherapy.

25 June 2017

cites work

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A logistic regression model for predicting axillary lymph node metastases in early breast carcinoma patients

21 January 2018

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21 January 2018

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DNA methylation patterns in blood of patients with colorectal cancer and adenomatous colorectal polyps

21 January 2018

1 reference

Monte Carlo EM for missing covariates in parametric regression models.

21 January 2018

1 reference

MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes

21 January 2018

1 reference

A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase

21 January 2018

1 reference

A new multipoint method for genome-wide association studies by imputation of genotypes

21 January 2018

1 reference

Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering

21 January 2018

1 reference

Adaptive Rejection Sampling for Gibbs Sampling

21 January 2018

1 reference

Genome-wide association analysis by lasso penalized logistic regression

21 January 2018

1 reference

21 January 2018

Identifiers

DOI

10.1002/SIM.5760

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25 June 2017

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