Organizing and Analyzing the Activity Data in NHANES View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-09

AUTHORS

Andrew Leroux, Junrui Di, Ekaterina Smirnova, Elizabeth J Mcguffey, Quy Cao, Elham Bayatmokhtari, Lucia Tabacu, Vadim Zipunnikov, Jacek K Urbanek, Ciprian Crainiceanu

ABSTRACT

The NHANES study contains objectively measured physical activity data collected using hip-worn accelerometers from multiple cohorts. However, using the accelerometry data has proven daunting because (1) currently, there are no agreed-upon standard protocols for data storage and analysis; (2) data exhibit heterogeneous patterns of missingness due to varying degrees of adherence to wear-time protocols; (3) sampling weights need to be carefully adjusted and accounted for in individual analyses; (4) there is a lack of reproducible software that transforms the data from its published format into analytic form; and (5) the high dimensional nature of accelerometry data complicates analyses. Here, we provide a framework for processing, storing, and analyzing the NHANES accelerometry data for the 2003–2004 and 2005–2006 surveys. We also provide an NHANES data package in R, to help disseminate high-quality, processed activity data combined with mortality and demographic information. Thus, we provide the tools to transition from “available data online” to “easily accessible and usable data”, which substantially reduces the large upfront costs of initiating studies of association between physical activity and human health outcomes using NHANES. We apply these tools in an analysis showing that accelerometry features have the potential to predict 5-year all-cause mortality better than known risk factors such as age, cigarette smoking, and various comorbidities. More... »

PAGES

1-26

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12561-018-09229-9

DOI

http://dx.doi.org/10.1007/s12561-018-09229-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112038452


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": "Johns Hopkins University", 
          "id": "https://www.grid.ac/institutes/grid.21107.35", 
          "name": [
            "Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Leroux", 
        "givenName": "Andrew", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Johns Hopkins University", 
          "id": "https://www.grid.ac/institutes/grid.21107.35", 
          "name": [
            "Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Di", 
        "givenName": "Junrui", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Montana", 
          "id": "https://www.grid.ac/institutes/grid.253613.0", 
          "name": [
            "Department of Biostatistics, Virginia Commonwealth University, Richmond, USA", 
            "Department of Mathematical Sciences, University of Montana, Missoula, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Smirnova", 
        "givenName": "Ekaterina", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "United States Naval Academy", 
          "id": "https://www.grid.ac/institutes/grid.265465.6", 
          "name": [
            "Department of Mathematics, United States Naval Academy, Annapolis, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Mcguffey", 
        "givenName": "Elizabeth J", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Montana", 
          "id": "https://www.grid.ac/institutes/grid.253613.0", 
          "name": [
            "Department of Mathematical Sciences, University of Montana, Missoula, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Cao", 
        "givenName": "Quy", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "University of Montana", 
          "id": "https://www.grid.ac/institutes/grid.253613.0", 
          "name": [
            "Department of Mathematical Sciences, University of Montana, Missoula, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Bayatmokhtari", 
        "givenName": "Elham", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Old Dominion University", 
          "id": "https://www.grid.ac/institutes/grid.261368.8", 
          "name": [
            "Department of Mathematics and Statistics, Old Dominion University, Norfolk, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Tabacu", 
        "givenName": "Lucia", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Johns Hopkins University", 
          "id": "https://www.grid.ac/institutes/grid.21107.35", 
          "name": [
            "Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Zipunnikov", 
        "givenName": "Vadim", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Johns Hopkins University", 
          "id": "https://www.grid.ac/institutes/grid.21107.35", 
          "name": [
            "Division of Geriatric Medicine and Gerontology, Department of Medicine, Center on Aging and Health, School of Medicine, Johns Hopkins University, Baltimore, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Urbanek", 
        "givenName": "Jacek K", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Johns Hopkins University", 
          "id": "https://www.grid.ac/institutes/grid.21107.35", 
          "name": [
            "Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Crainiceanu", 
        "givenName": "Ciprian", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/s11222-014-9485-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014988299", 
          "https://doi.org/10.1007/s11222-014-9485-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s11222-014-9485-x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1014988299", 
          "https://doi.org/10.1007/s11222-014-9485-x"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ypmed.2014.02.003", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1016369565"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1249/mss.0b013e31815a51b3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024501743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1249/mss.0b013e31815a51b3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024501743"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/biom.12236", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025232595"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.pmedr.2015.02.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026958083"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/gerona/glt199", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029224617"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pmed.1001779", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1033632930"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0000000000000075", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034917057"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1097/ede.0000000000000075", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034917057"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0089574", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040388203"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1159/000444802", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048607112"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/08-aoas206", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049728879"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/1471082x14565526", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053857459"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1177/1471082x14565526", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053857459"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/01621459.2016.1180986", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1058306546"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/jssam/smu021", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059833519"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1198/jcgs.2011.10122", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064201133"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/15-aoas879", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064395102"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1503/jpn.130247", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067426763"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1503/jpn.130247", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067426763"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4088/jcp.14m09106", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072206227"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1078592544", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/gerona/glw331", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1083905847"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/182337", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091916288"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/182337", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091916288"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1101/182337", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1091916288"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.ypmed.2017.10.028", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1092438865"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/9780470580066", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098662364"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/9780470580066", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1098662364"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-02-09", 
    "datePublishedReg": "2019-02-09", 
    "description": "The NHANES study contains objectively measured physical activity data collected using hip-worn accelerometers from multiple cohorts. However, using the accelerometry data has proven daunting because (1) currently, there are no agreed-upon standard protocols for data storage and analysis; (2) data exhibit heterogeneous patterns of missingness due to varying degrees of adherence to wear-time protocols; (3) sampling weights need to be carefully adjusted and accounted for in individual analyses; (4) there is a lack of reproducible software that transforms the data from its published format into analytic form; and (5) the high dimensional nature of accelerometry data complicates analyses. Here, we provide a framework for processing, storing, and analyzing the NHANES accelerometry data for the 2003\u20132004 and 2005\u20132006 surveys. We also provide an NHANES data package in R, to help disseminate high-quality, processed activity data combined with mortality and demographic information. Thus, we provide the tools to transition from \u201cavailable data online\u201d to \u201ceasily accessible and usable data\u201d, which substantially reduces the large upfront costs of initiating studies of association between physical activity and human health outcomes using NHANES. We apply these tools in an analysis showing that accelerometry features have the potential to predict 5-year all-cause mortality better than known risk factors such as age, cigarette smoking, and various comorbidities.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12561-018-09229-9", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.3806038", 
        "type": "MonetaryGrant"
      }, 
      {
        "id": "sg:grant.2562178", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1041137", 
        "issn": [
          "1867-1764", 
          "1867-1772"
        ], 
        "name": "Statistics in Biosciences", 
        "type": "Periodical"
      }
    ], 
    "name": "Organizing and Analyzing the Activity Data in NHANES", 
    "pagination": "1-26", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "07931b734cca9c51c6aaec2b55e6e3ef1612cdca0f770595db4b2b15367a01af"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12561-018-09229-9"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112038452"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12561-018-09229-9", 
      "https://app.dimensions.ai/details/publication/pub.1112038452"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T09:04", 
    "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/v90/0000000333_0000000333/records_41738_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs12561-018-09229-9"
  }
]
 

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/s12561-018-09229-9'

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/s12561-018-09229-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12561-018-09229-9'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12561-018-09229-9'


 

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

192 TRIPLES      21 PREDICATES      47 URIs      16 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12561-018-09229-9 schema:about anzsrc-for:11
2 anzsrc-for:1117
3 schema:author N85b72fd0aa3e4b61af028612bd401ce2
4 schema:citation sg:pub.10.1007/s11222-014-9485-x
5 https://app.dimensions.ai/details/publication/pub.1078592544
6 https://doi.org/10.1002/9780470580066
7 https://doi.org/10.1016/j.pmedr.2015.02.007
8 https://doi.org/10.1016/j.ypmed.2014.02.003
9 https://doi.org/10.1016/j.ypmed.2017.10.028
10 https://doi.org/10.1080/01621459.2016.1180986
11 https://doi.org/10.1093/gerona/glt199
12 https://doi.org/10.1093/gerona/glw331
13 https://doi.org/10.1093/jssam/smu021
14 https://doi.org/10.1097/ede.0000000000000075
15 https://doi.org/10.1101/182337
16 https://doi.org/10.1111/biom.12236
17 https://doi.org/10.1159/000444802
18 https://doi.org/10.1177/1471082x14565526
19 https://doi.org/10.1198/jcgs.2011.10122
20 https://doi.org/10.1214/08-aoas206
21 https://doi.org/10.1214/15-aoas879
22 https://doi.org/10.1249/mss.0b013e31815a51b3
23 https://doi.org/10.1371/journal.pmed.1001779
24 https://doi.org/10.1371/journal.pone.0089574
25 https://doi.org/10.1503/jpn.130247
26 https://doi.org/10.4088/jcp.14m09106
27 schema:datePublished 2019-02-09
28 schema:datePublishedReg 2019-02-09
29 schema:description The NHANES study contains objectively measured physical activity data collected using hip-worn accelerometers from multiple cohorts. However, using the accelerometry data has proven daunting because (1) currently, there are no agreed-upon standard protocols for data storage and analysis; (2) data exhibit heterogeneous patterns of missingness due to varying degrees of adherence to wear-time protocols; (3) sampling weights need to be carefully adjusted and accounted for in individual analyses; (4) there is a lack of reproducible software that transforms the data from its published format into analytic form; and (5) the high dimensional nature of accelerometry data complicates analyses. Here, we provide a framework for processing, storing, and analyzing the NHANES accelerometry data for the 2003–2004 and 2005–2006 surveys. We also provide an NHANES data package in R, to help disseminate high-quality, processed activity data combined with mortality and demographic information. Thus, we provide the tools to transition from “available data online” to “easily accessible and usable data”, which substantially reduces the large upfront costs of initiating studies of association between physical activity and human health outcomes using NHANES. We apply these tools in an analysis showing that accelerometry features have the potential to predict 5-year all-cause mortality better than known risk factors such as age, cigarette smoking, and various comorbidities.
30 schema:genre research_article
31 schema:inLanguage en
32 schema:isAccessibleForFree false
33 schema:isPartOf sg:journal.1041137
34 schema:name Organizing and Analyzing the Activity Data in NHANES
35 schema:pagination 1-26
36 schema:productId N6313bf9862984effab4f97fd4cfe86a6
37 N97a4255e3d9c43baa9a85fa0ceb2397a
38 N9c6762f1f304474db99226a76097d16b
39 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112038452
40 https://doi.org/10.1007/s12561-018-09229-9
41 schema:sdDatePublished 2019-04-11T09:04
42 schema:sdLicense https://scigraph.springernature.com/explorer/license/
43 schema:sdPublisher N9c17809290a34917aa86780e8ac990bb
44 schema:url https://link.springer.com/10.1007%2Fs12561-018-09229-9
45 sgo:license sg:explorer/license/
46 sgo:sdDataset articles
47 rdf:type schema:ScholarlyArticle
48 N1bfc5bba9c5b45ffb8d1a653d630244f schema:affiliation https://www.grid.ac/institutes/grid.253613.0
49 schema:familyName Smirnova
50 schema:givenName Ekaterina
51 rdf:type schema:Person
52 N1c00da3655eb41c88c9ac9317e931499 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
53 schema:familyName Urbanek
54 schema:givenName Jacek K
55 rdf:type schema:Person
56 N1f32fb6c66934aee9ca246bfd904711e rdf:first Ne5f5924af1fe4fc1817ca3d1180b8e87
57 rdf:rest Ncd726e8f01f14e8395b786a8441728e9
58 N1fdd1651e5e84ae5863a88f122e858e0 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
59 schema:familyName Zipunnikov
60 schema:givenName Vadim
61 rdf:type schema:Person
62 N33a7ee1c86624bea90603422e9c05977 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
63 schema:familyName Leroux
64 schema:givenName Andrew
65 rdf:type schema:Person
66 N513e9841d3d44308b416fc4c7c666e15 rdf:first N6440806abeb84e95979294877ebedc11
67 rdf:rest rdf:nil
68 N56d0767b51da462dba9fe89ac931f5d5 schema:affiliation https://www.grid.ac/institutes/grid.265465.6
69 schema:familyName Mcguffey
70 schema:givenName Elizabeth J
71 rdf:type schema:Person
72 N59ce140820e84ee8897bcd4134f6b593 rdf:first N1fdd1651e5e84ae5863a88f122e858e0
73 rdf:rest Ne35ae5eb7f6441a58d78daa5368d5585
74 N6313bf9862984effab4f97fd4cfe86a6 schema:name doi
75 schema:value 10.1007/s12561-018-09229-9
76 rdf:type schema:PropertyValue
77 N6440806abeb84e95979294877ebedc11 schema:affiliation https://www.grid.ac/institutes/grid.21107.35
78 schema:familyName Crainiceanu
79 schema:givenName Ciprian
80 rdf:type schema:Person
81 N6d3fd0bd58b84aff83a954e0aaf7dc2c schema:affiliation https://www.grid.ac/institutes/grid.21107.35
82 schema:familyName Di
83 schema:givenName Junrui
84 rdf:type schema:Person
85 N85b72fd0aa3e4b61af028612bd401ce2 rdf:first N33a7ee1c86624bea90603422e9c05977
86 rdf:rest Ne5c11a4510a948a4b5fb3c724257654e
87 N90f92b8c024b48228b6b49e00878f1e6 rdf:first N56d0767b51da462dba9fe89ac931f5d5
88 rdf:rest Nf340452a57da4addb7190369ee02c3b9
89 N97a4255e3d9c43baa9a85fa0ceb2397a schema:name readcube_id
90 schema:value 07931b734cca9c51c6aaec2b55e6e3ef1612cdca0f770595db4b2b15367a01af
91 rdf:type schema:PropertyValue
92 N97f517218c1042be9f1dc96ec00a8a69 rdf:first N1bfc5bba9c5b45ffb8d1a653d630244f
93 rdf:rest N90f92b8c024b48228b6b49e00878f1e6
94 N9c17809290a34917aa86780e8ac990bb schema:name Springer Nature - SN SciGraph project
95 rdf:type schema:Organization
96 N9c6762f1f304474db99226a76097d16b schema:name dimensions_id
97 schema:value pub.1112038452
98 rdf:type schema:PropertyValue
99 Nc18a3144525e4538a3ffde94bf7099bd schema:affiliation https://www.grid.ac/institutes/grid.253613.0
100 schema:familyName Cao
101 schema:givenName Quy
102 rdf:type schema:Person
103 Ncd726e8f01f14e8395b786a8441728e9 rdf:first Ne7c7cf73c6704f259fb9409c0989aab5
104 rdf:rest N59ce140820e84ee8897bcd4134f6b593
105 Ne35ae5eb7f6441a58d78daa5368d5585 rdf:first N1c00da3655eb41c88c9ac9317e931499
106 rdf:rest N513e9841d3d44308b416fc4c7c666e15
107 Ne5c11a4510a948a4b5fb3c724257654e rdf:first N6d3fd0bd58b84aff83a954e0aaf7dc2c
108 rdf:rest N97f517218c1042be9f1dc96ec00a8a69
109 Ne5f5924af1fe4fc1817ca3d1180b8e87 schema:affiliation https://www.grid.ac/institutes/grid.253613.0
110 schema:familyName Bayatmokhtari
111 schema:givenName Elham
112 rdf:type schema:Person
113 Ne7c7cf73c6704f259fb9409c0989aab5 schema:affiliation https://www.grid.ac/institutes/grid.261368.8
114 schema:familyName Tabacu
115 schema:givenName Lucia
116 rdf:type schema:Person
117 Nf340452a57da4addb7190369ee02c3b9 rdf:first Nc18a3144525e4538a3ffde94bf7099bd
118 rdf:rest N1f32fb6c66934aee9ca246bfd904711e
119 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
120 schema:name Medical and Health Sciences
121 rdf:type schema:DefinedTerm
122 anzsrc-for:1117 schema:inDefinedTermSet anzsrc-for:
123 schema:name Public Health and Health Services
124 rdf:type schema:DefinedTerm
125 sg:grant.2562178 http://pending.schema.org/fundedItem sg:pub.10.1007/s12561-018-09229-9
126 rdf:type schema:MonetaryGrant
127 sg:grant.3806038 http://pending.schema.org/fundedItem sg:pub.10.1007/s12561-018-09229-9
128 rdf:type schema:MonetaryGrant
129 sg:journal.1041137 schema:issn 1867-1764
130 1867-1772
131 schema:name Statistics in Biosciences
132 rdf:type schema:Periodical
133 sg:pub.10.1007/s11222-014-9485-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1014988299
134 https://doi.org/10.1007/s11222-014-9485-x
135 rdf:type schema:CreativeWork
136 https://app.dimensions.ai/details/publication/pub.1078592544 schema:CreativeWork
137 https://doi.org/10.1002/9780470580066 schema:sameAs https://app.dimensions.ai/details/publication/pub.1098662364
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1016/j.pmedr.2015.02.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026958083
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1016/j.ypmed.2014.02.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016369565
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1016/j.ypmed.2017.10.028 schema:sameAs https://app.dimensions.ai/details/publication/pub.1092438865
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1080/01621459.2016.1180986 schema:sameAs https://app.dimensions.ai/details/publication/pub.1058306546
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1093/gerona/glt199 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029224617
148 rdf:type schema:CreativeWork
149 https://doi.org/10.1093/gerona/glw331 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083905847
150 rdf:type schema:CreativeWork
151 https://doi.org/10.1093/jssam/smu021 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059833519
152 rdf:type schema:CreativeWork
153 https://doi.org/10.1097/ede.0000000000000075 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034917057
154 rdf:type schema:CreativeWork
155 https://doi.org/10.1101/182337 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091916288
156 rdf:type schema:CreativeWork
157 https://doi.org/10.1111/biom.12236 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025232595
158 rdf:type schema:CreativeWork
159 https://doi.org/10.1159/000444802 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048607112
160 rdf:type schema:CreativeWork
161 https://doi.org/10.1177/1471082x14565526 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053857459
162 rdf:type schema:CreativeWork
163 https://doi.org/10.1198/jcgs.2011.10122 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064201133
164 rdf:type schema:CreativeWork
165 https://doi.org/10.1214/08-aoas206 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049728879
166 rdf:type schema:CreativeWork
167 https://doi.org/10.1214/15-aoas879 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064395102
168 rdf:type schema:CreativeWork
169 https://doi.org/10.1249/mss.0b013e31815a51b3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024501743
170 rdf:type schema:CreativeWork
171 https://doi.org/10.1371/journal.pmed.1001779 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033632930
172 rdf:type schema:CreativeWork
173 https://doi.org/10.1371/journal.pone.0089574 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040388203
174 rdf:type schema:CreativeWork
175 https://doi.org/10.1503/jpn.130247 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067426763
176 rdf:type schema:CreativeWork
177 https://doi.org/10.4088/jcp.14m09106 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072206227
178 rdf:type schema:CreativeWork
179 https://www.grid.ac/institutes/grid.21107.35 schema:alternateName Johns Hopkins University
180 schema:name Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
181 Division of Geriatric Medicine and Gerontology, Department of Medicine, Center on Aging and Health, School of Medicine, Johns Hopkins University, Baltimore, USA
182 rdf:type schema:Organization
183 https://www.grid.ac/institutes/grid.253613.0 schema:alternateName University of Montana
184 schema:name Department of Biostatistics, Virginia Commonwealth University, Richmond, USA
185 Department of Mathematical Sciences, University of Montana, Missoula, USA
186 rdf:type schema:Organization
187 https://www.grid.ac/institutes/grid.261368.8 schema:alternateName Old Dominion University
188 schema:name Department of Mathematics and Statistics, Old Dominion University, Norfolk, USA
189 rdf:type schema:Organization
190 https://www.grid.ac/institutes/grid.265465.6 schema:alternateName United States Naval Academy
191 schema:name Department of Mathematics, United States Naval Academy, Annapolis, USA
192 rdf:type schema:Organization
 




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


...