Misspecification of within-area exposure distribution in ecological Poisson models View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2009-09

AUTHORS

Léa Fortunato, Chantal Guihenneuc-Jouyaux, Margot Tirmarche, Dominique Laurier, Denis Hémon

ABSTRACT

Ecological studies enable investigation of geographic variations in exposure to environmental variables, across groups, in relation to health outcomes measured on a geographic scale. Such studies are subject to ecological biases, including pure specification bias which arises when a nonlinear individual exposure-risk model is assumed to apply at the area level. Introduction of the within-area variance of exposure should induce a marked reduction in this source of ecological bias. Assuming several measurements per area of exposure and no confounding risk factors, we study the model including the within-area exposure variability when Gaussian within-area exposure distribution is assumed. The robustness is assessed when the within-area exposure distribution is misspecified. Two underlying exposure distributions are studied: the Gamma distribution and an unimodal mixture of two Gaussian distributions. In case of strong ecological association, this model can reduce the bias and improve the precision of the individual parameter estimates when the within-area exposure means and variances are correlated. These different models are applied to analyze the ecological association between radon concentration and childhood acute leukemia in France. More... »

PAGES

341-353

References to SciGraph publications

  • 1991-03. Bayesian image restoration, with two applications in spatial statistics in ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
  • 2002. Modeling the Impact of Traffic-Related Air Pollution on Childhood Respiratory Illness in CASE STUDIES IN BAYESIAN STATISTICS VOLUME V
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10651-007-0053-9

    DOI

    http://dx.doi.org/10.1007/s10651-007-0053-9

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1024863208


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1117", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Public Health and Health Services", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of Paris-Sud", 
              "id": "https://www.grid.ac/institutes/grid.5842.b", 
              "name": [
                "INSERM, U754, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France", 
                "Universit\u00e9 Paris Sud, IFR69, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Fortunato", 
            "givenName": "L\u00e9a", 
            "id": "sg:person.01372332430.17", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01372332430.17"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Paris Descartes University", 
              "id": "https://www.grid.ac/institutes/grid.10992.33", 
              "name": [
                "INSERM, U754, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France", 
                "Universit\u00e9 Paris Sud, IFR69, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France", 
                "CNRS UMR 8145, UFR Biom\u00e9dicale, Universit\u00e9 Paris 5, 45 rue des Saint-P\u00e8res, 75006, Paris, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Guihenneuc-Jouyaux", 
            "givenName": "Chantal", 
            "id": "sg:person.01061575735.45", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061575735.45"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "IRSN/DRPH/SRBE/LEPID, BP17, 92262, Fontenay-aux-Roses, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Tirmarche", 
            "givenName": "Margot", 
            "id": "sg:person.0577714655.93", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0577714655.93"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "IRSN/DRPH/SRBE/LEPID, BP17, 92262, Fontenay-aux-Roses, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Laurier", 
            "givenName": "Dominique", 
            "id": "sg:person.01253741655.94", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01253741655.94"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Paris-Sud", 
              "id": "https://www.grid.ac/institutes/grid.5842.b", 
              "name": [
                "INSERM, U754, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France", 
                "Universit\u00e9 Paris Sud, IFR69, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France"
              ], 
              "type": "Organization"
            }, 
            "familyName": "H\u00e9mon", 
            "givenName": "Denis", 
            "id": "sg:person.01204334072.81", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01204334072.81"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1097/00008469-200504000-00011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003563596"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/00008469-200504000-00011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003563596"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/00008469-200504000-00011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1003563596"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/1541-0420.00002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004305597"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/1467-9876.00113", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010198926"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4613-0035-9_3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016488509", 
              "https://doi.org/10.1007/978-1-4613-0035-9_3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-1-4613-0035-9_3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016488509", 
              "https://doi.org/10.1007/978-1-4613-0035-9_3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1111/j.0006-341x.2000.00013.x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1021065249"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/00008469-200404000-00002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031128444"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1097/00008469-200404000-00002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031128444"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00116466", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041821886", 
              "https://doi.org/10.1007/bf00116466"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/bf00116466", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041821886", 
              "https://doi.org/10.1007/bf00116466"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/env.571", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041885712"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/(sici)1097-0258(19980930)17:18<2045::aid-sim943>3.0.co;2-p", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044376229"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/sim.4780110907", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050544466"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/ije/16.1.111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1059673583"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/rpd/nch463", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060015664"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1191/0962280205sm388oa", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064155236"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1191/0962280205sm388oa", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064155236"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1198/016214502388618870", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1064197954"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.2307/2532003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1069977432"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2009-09", 
        "datePublishedReg": "2009-09-01", 
        "description": "Ecological studies enable investigation of geographic variations in exposure to environmental variables, across groups, in relation to health outcomes measured on a geographic scale. Such studies are subject to ecological biases, including pure specification bias which arises when a nonlinear individual exposure-risk model is assumed to apply at the area level. Introduction of the within-area variance of exposure should induce a marked reduction in this source of ecological bias. Assuming several measurements per area of exposure and no confounding risk factors, we study the model including the within-area exposure variability when Gaussian within-area exposure distribution is assumed. The robustness is assessed when the within-area exposure distribution is misspecified. Two underlying exposure distributions are studied: the Gamma distribution and an unimodal mixture of two Gaussian distributions. In case of strong ecological association, this model can reduce the bias and improve the precision of the individual parameter estimates when the within-area exposure means and variances are correlated. These different models are applied to analyze the ecological association between radon concentration and childhood acute leukemia in France.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s10651-007-0053-9", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1356907", 
            "issn": [
              "1573-3009", 
              "1352-8505"
            ], 
            "name": "Environmental and Ecological Statistics", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "3", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "16"
          }
        ], 
        "name": "Misspecification of within-area exposure distribution in ecological Poisson models", 
        "pagination": "341-353", 
        "productId": [
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s10651-007-0053-9"
            ]
          }, 
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "7672f026e2e1a40dc85b00f1a00f5bf807b0033c971c0a382118ca4224ad6158"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1024863208"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s10651-007-0053-9", 
          "https://app.dimensions.ai/details/publication/pub.1024863208"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-15T09:12", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000376_0000000376/records_56159_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1007%2Fs10651-007-0053-9"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s10651-007-0053-9'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s10651-007-0053-9'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s10651-007-0053-9'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s10651-007-0053-9'


     

    This table displays all metadata directly associated to this object as RDF triples.

    146 TRIPLES      21 PREDICATES      42 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s10651-007-0053-9 schema:about anzsrc-for:11
    2 anzsrc-for:1117
    3 schema:author N4f7b9222521d4541bfbae32ea0b5b5b4
    4 schema:citation sg:pub.10.1007/978-1-4613-0035-9_3
    5 sg:pub.10.1007/bf00116466
    6 https://doi.org/10.1002/(sici)1097-0258(19980930)17:18<2045::aid-sim943>3.0.co;2-p
    7 https://doi.org/10.1002/env.571
    8 https://doi.org/10.1002/sim.4780110907
    9 https://doi.org/10.1093/ije/16.1.111
    10 https://doi.org/10.1093/rpd/nch463
    11 https://doi.org/10.1097/00008469-200404000-00002
    12 https://doi.org/10.1097/00008469-200504000-00011
    13 https://doi.org/10.1111/1467-9876.00113
    14 https://doi.org/10.1111/1541-0420.00002
    15 https://doi.org/10.1111/j.0006-341x.2000.00013.x
    16 https://doi.org/10.1191/0962280205sm388oa
    17 https://doi.org/10.1198/016214502388618870
    18 https://doi.org/10.2307/2532003
    19 schema:datePublished 2009-09
    20 schema:datePublishedReg 2009-09-01
    21 schema:description Ecological studies enable investigation of geographic variations in exposure to environmental variables, across groups, in relation to health outcomes measured on a geographic scale. Such studies are subject to ecological biases, including pure specification bias which arises when a nonlinear individual exposure-risk model is assumed to apply at the area level. Introduction of the within-area variance of exposure should induce a marked reduction in this source of ecological bias. Assuming several measurements per area of exposure and no confounding risk factors, we study the model including the within-area exposure variability when Gaussian within-area exposure distribution is assumed. The robustness is assessed when the within-area exposure distribution is misspecified. Two underlying exposure distributions are studied: the Gamma distribution and an unimodal mixture of two Gaussian distributions. In case of strong ecological association, this model can reduce the bias and improve the precision of the individual parameter estimates when the within-area exposure means and variances are correlated. These different models are applied to analyze the ecological association between radon concentration and childhood acute leukemia in France.
    22 schema:genre research_article
    23 schema:inLanguage en
    24 schema:isAccessibleForFree true
    25 schema:isPartOf Naac1fb33681741dbb24cf9e7577cf558
    26 Nb1920ab945de4c7f8d5dc8f91863ac1d
    27 sg:journal.1356907
    28 schema:name Misspecification of within-area exposure distribution in ecological Poisson models
    29 schema:pagination 341-353
    30 schema:productId N41d5d77f688d4e61ba7e53d034aa6c8a
    31 Na8e1bd5146444f29965a9a145e5eb322
    32 Nfe1ca38a5a8a4f42bff9063ca66b9e3a
    33 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024863208
    34 https://doi.org/10.1007/s10651-007-0053-9
    35 schema:sdDatePublished 2019-04-15T09:12
    36 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    37 schema:sdPublisher N9de8e3e2b89149048d14bb4e7114e4c8
    38 schema:url http://link.springer.com/10.1007%2Fs10651-007-0053-9
    39 sgo:license sg:explorer/license/
    40 sgo:sdDataset articles
    41 rdf:type schema:ScholarlyArticle
    42 N3de1c616931e45609fcbfcdf7a43bae6 schema:name IRSN/DRPH/SRBE/LEPID, BP17, 92262, Fontenay-aux-Roses, France
    43 rdf:type schema:Organization
    44 N41d5d77f688d4e61ba7e53d034aa6c8a schema:name dimensions_id
    45 schema:value pub.1024863208
    46 rdf:type schema:PropertyValue
    47 N4f7b9222521d4541bfbae32ea0b5b5b4 rdf:first sg:person.01372332430.17
    48 rdf:rest N73e582816d354ce685473af1ecc25224
    49 N73e582816d354ce685473af1ecc25224 rdf:first sg:person.01061575735.45
    50 rdf:rest Nc420a4566f4a4536903066a38fedbe6b
    51 N9463e49845c7427aa881cca791d86ddb rdf:first sg:person.01253741655.94
    52 rdf:rest Na869c4c2d9b14d0d92a81f006c0b1730
    53 N9de8e3e2b89149048d14bb4e7114e4c8 schema:name Springer Nature - SN SciGraph project
    54 rdf:type schema:Organization
    55 Na869c4c2d9b14d0d92a81f006c0b1730 rdf:first sg:person.01204334072.81
    56 rdf:rest rdf:nil
    57 Na8e1bd5146444f29965a9a145e5eb322 schema:name doi
    58 schema:value 10.1007/s10651-007-0053-9
    59 rdf:type schema:PropertyValue
    60 Naac1fb33681741dbb24cf9e7577cf558 schema:volumeNumber 16
    61 rdf:type schema:PublicationVolume
    62 Nb1920ab945de4c7f8d5dc8f91863ac1d schema:issueNumber 3
    63 rdf:type schema:PublicationIssue
    64 Nc420a4566f4a4536903066a38fedbe6b rdf:first sg:person.0577714655.93
    65 rdf:rest N9463e49845c7427aa881cca791d86ddb
    66 Nd8934717a2e6494fb74c179e228ef5a1 schema:name IRSN/DRPH/SRBE/LEPID, BP17, 92262, Fontenay-aux-Roses, France
    67 rdf:type schema:Organization
    68 Nfe1ca38a5a8a4f42bff9063ca66b9e3a schema:name readcube_id
    69 schema:value 7672f026e2e1a40dc85b00f1a00f5bf807b0033c971c0a382118ca4224ad6158
    70 rdf:type schema:PropertyValue
    71 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    72 schema:name Medical and Health Sciences
    73 rdf:type schema:DefinedTerm
    74 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
    75 schema:name Public Health and Health Services
    76 rdf:type schema:DefinedTerm
    77 sg:journal.1356907 schema:issn 1352-8505
    78 1573-3009
    79 schema:name Environmental and Ecological Statistics
    80 rdf:type schema:Periodical
    81 sg:person.01061575735.45 schema:affiliation https://www.grid.ac/institutes/grid.10992.33
    82 schema:familyName Guihenneuc-Jouyaux
    83 schema:givenName Chantal
    84 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061575735.45
    85 rdf:type schema:Person
    86 sg:person.01204334072.81 schema:affiliation https://www.grid.ac/institutes/grid.5842.b
    87 schema:familyName Hémon
    88 schema:givenName Denis
    89 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01204334072.81
    90 rdf:type schema:Person
    91 sg:person.01253741655.94 schema:affiliation N3de1c616931e45609fcbfcdf7a43bae6
    92 schema:familyName Laurier
    93 schema:givenName Dominique
    94 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01253741655.94
    95 rdf:type schema:Person
    96 sg:person.01372332430.17 schema:affiliation https://www.grid.ac/institutes/grid.5842.b
    97 schema:familyName Fortunato
    98 schema:givenName Léa
    99 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01372332430.17
    100 rdf:type schema:Person
    101 sg:person.0577714655.93 schema:affiliation Nd8934717a2e6494fb74c179e228ef5a1
    102 schema:familyName Tirmarche
    103 schema:givenName Margot
    104 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0577714655.93
    105 rdf:type schema:Person
    106 sg:pub.10.1007/978-1-4613-0035-9_3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016488509
    107 https://doi.org/10.1007/978-1-4613-0035-9_3
    108 rdf:type schema:CreativeWork
    109 sg:pub.10.1007/bf00116466 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041821886
    110 https://doi.org/10.1007/bf00116466
    111 rdf:type schema:CreativeWork
    112 https://doi.org/10.1002/(sici)1097-0258(19980930)17:18<2045::aid-sim943>3.0.co;2-p schema:sameAs https://app.dimensions.ai/details/publication/pub.1044376229
    113 rdf:type schema:CreativeWork
    114 https://doi.org/10.1002/env.571 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041885712
    115 rdf:type schema:CreativeWork
    116 https://doi.org/10.1002/sim.4780110907 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050544466
    117 rdf:type schema:CreativeWork
    118 https://doi.org/10.1093/ije/16.1.111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059673583
    119 rdf:type schema:CreativeWork
    120 https://doi.org/10.1093/rpd/nch463 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060015664
    121 rdf:type schema:CreativeWork
    122 https://doi.org/10.1097/00008469-200404000-00002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031128444
    123 rdf:type schema:CreativeWork
    124 https://doi.org/10.1097/00008469-200504000-00011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003563596
    125 rdf:type schema:CreativeWork
    126 https://doi.org/10.1111/1467-9876.00113 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010198926
    127 rdf:type schema:CreativeWork
    128 https://doi.org/10.1111/1541-0420.00002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004305597
    129 rdf:type schema:CreativeWork
    130 https://doi.org/10.1111/j.0006-341x.2000.00013.x schema:sameAs https://app.dimensions.ai/details/publication/pub.1021065249
    131 rdf:type schema:CreativeWork
    132 https://doi.org/10.1191/0962280205sm388oa schema:sameAs https://app.dimensions.ai/details/publication/pub.1064155236
    133 rdf:type schema:CreativeWork
    134 https://doi.org/10.1198/016214502388618870 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064197954
    135 rdf:type schema:CreativeWork
    136 https://doi.org/10.2307/2532003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1069977432
    137 rdf:type schema:CreativeWork
    138 https://www.grid.ac/institutes/grid.10992.33 schema:alternateName Paris Descartes University
    139 schema:name CNRS UMR 8145, UFR Biomédicale, Université Paris 5, 45 rue des Saint-Pères, 75006, Paris, France
    140 INSERM, U754, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France
    141 Université Paris Sud, IFR69, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France
    142 rdf:type schema:Organization
    143 https://www.grid.ac/institutes/grid.5842.b schema:alternateName University of Paris-Sud
    144 schema:name INSERM, U754, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France
    145 Université Paris Sud, IFR69, 16 av Paul Vaillant-Couturier, 94807, Villejuif cedex, France
    146 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...