Variable selection on large case-crossover data: application to a registry-based study of prescription drugs and road traffic crashes.
about
Sparse conditional logistic regression for analyzing large-scale matched data from epidemiological studies: a simple algorithmThe case-crossover design via penalized regression.Least absolute shrinkage and selection operator type methods for the identification of serum biomarkers of overweight and obesity: simulation and application.Prescription medicine use by pedestrians and the risk of injurious road traffic crashes: A case-crossover study.The national healthcare system claims databases in France, SNIIRAM and EGB: Powerful tools for pharmacoepidemiology.New opioid analgesic use and the risk of injurious single-vehicle crashes in drivers aged 50-80 years: A population-based matched case-control study.
P2860
Variable selection on large case-crossover data: application to a registry-based study of prescription drugs and road traffic crashes.
description
2013 nî lūn-bûn
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2013 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2013 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2013年の論文
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2013年論文
@yue
2013年論文
@zh-hant
2013年論文
@zh-hk
2013年論文
@zh-mo
2013年論文
@zh-tw
2013年论文
@wuu
name
Variable selection on large ca ...... rugs and road traffic crashes.
@ast
Variable selection on large ca ...... rugs and road traffic crashes.
@en
type
label
Variable selection on large ca ...... rugs and road traffic crashes.
@ast
Variable selection on large ca ...... rugs and road traffic crashes.
@en
prefLabel
Variable selection on large ca ...... rugs and road traffic crashes.
@ast
Variable selection on large ca ...... rugs and road traffic crashes.
@en
P2093
P2860
P356
P1476
Variable selection on large ca ...... rugs and road traffic crashes.
@en
P2093
CESIR research group
Frantz Thiessard
Hélène Pouyes
Ludivine Orriols
Marta Avalos
P2860
P304
P356
10.1002/PDS.3539
P577
2013-10-18T00:00:00Z