{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T01:21:20Z","timestamp":1787016080078,"version":"build-2736575974"},"reference-count":15,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2018,7,17]],"date-time":"2018-07-17T00:00:00Z","timestamp":1531785600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["P30ES017885"],"award-info":[{"award-number":["P30ES017885"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["P42ES017198"],"award-info":[{"award-number":["P42ES017198"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["R01ES018872"],"award-info":[{"award-number":["R01ES018872"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000066","name":"National Institute of Environmental Health Sciences","doi-asserted-by":"publisher","award":["ZIA103321"],"award-info":[{"award-number":["ZIA103321"]}],"id":[{"id":"10.13039\/100000066","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Paediatric Perinatal Epid"],"published-print":{"date-parts":[[2018,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>\n                      Ultrasound measures are valuable for epidemiologic studies of risk factors for growth restriction. Longitudinal measurements enable investigation of rates of change and identification of windows where growth is impacted more acutely. However, missing data can be problematic in these studies, limiting sample size, ability to characterise windows of vulnerability, and in some instances creating bias. We sought to compare a parametric linear mixed model (\n                      <jats:styled-content style=\"fixed-case\">LMM<\/jats:styled-content>\n                      ) approach to multiple imputation in this setting with multiple imputation by chained equation (\n                      <jats:styled-content style=\"fixed-case\">MICE<\/jats:styled-content>\n                      ) methodology.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Ultrasound scans performed for clinical purposes were abstracted from women in the\n                      <jats:styled-content style=\"fixed-case\">LIFECODES<\/jats:styled-content>\n                      birth cohort (n\u00a0=\u00a01003) if they were close in time to three study visits (median 18, 26, and 35\u00a0weeks\u2019 gestation). We created imputed datasets using\n                      <jats:styled-content style=\"fixed-case\">LMM<\/jats:styled-content>\n                      and\n                      <jats:styled-content style=\"fixed-case\">MICE<\/jats:styled-content>\n                      and calculated associations between demographic factors and ultrasound parameters cross\u2010sectionally and longitudinally. Results were compared with a complete\u2010case analysis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Most participants had ultrasounds at 18\u00a0weeks\u2019 gestation, and ~50% had measurements at 26 and 35\u00a0weeks; 100% had birthweight. Associations between demographic factors and ultrasound measures were similar in magnitude, but more precise, when either imputed datasets were used, compared with a complete\u2010case analysis, in both the cross\u2010sectional or longitudinal analyses.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>\n                      <jats:styled-content style=\"fixed-case\">MICE<\/jats:styled-content>\n                      , though ignoring the non\u2010linear features of the trajectory and within subject correlation, is able to provide reasonable imputation of foetal growth data when compared to\n                      <jats:styled-content style=\"fixed-case\">LMM<\/jats:styled-content>\n                      . Because it simultaneously imputes missing covariate data and does not require specification of variance structure as in\n                      <jats:styled-content style=\"fixed-case\">LMM<\/jats:styled-content>\n                      ,\n                      <jats:styled-content style=\"fixed-case\">MICE<\/jats:styled-content>\n                      may be preferable for imputation in this setting.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/ppe.12486","type":"journal-article","created":{"date-parts":[[2018,7,18]],"date-time":"2018-07-18T18:10:57Z","timestamp":1531937457000},"page":"469-473","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Foetal ultrasound measurement imputations based on growth curves versus multiple imputation chained equation (\n                    <scp>MICE<\/scp>\n                    )"],"prefix":"10.1111","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8467-3250","authenticated-orcid":false,"given":"Kelly K.","family":"Ferguson","sequence":"first","affiliation":[{"name":"Epidemiology Branch National Institute of Environmental Health Sciences  Research Triangle Park NC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youfei","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Biostatistics School of Public Health University of Michigan  Ann\u00a0Arbor MI USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David E.","family":"Cantonwine","sequence":"additional","affiliation":[{"name":"Division of Maternal\u2010Fetal Medicine Brigham and Women's Hospital Harvard Medical School  Boston MA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas F.","family":"McElrath","sequence":"additional","affiliation":[{"name":"Division of Maternal\u2010Fetal Medicine Brigham and Women's Hospital Harvard Medical School  Boston MA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John D.","family":"Meeker","sequence":"additional","affiliation":[{"name":"Department of Environmental Health Sciences School of Public Health University of Michigan  Ann Arbor MI USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bhramar","family":"Mukherjee","sequence":"additional","affiliation":[{"name":"Department of Biostatistics School of Public Health University of Michigan  Ann\u00a0Arbor MI USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2018,7,17]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1289\/ehp.0901228"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1093\/ije\/dyx161"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/ppe.12276"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0020-7292(02)80002-9"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.6926"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v045.i03"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0146532"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.181.1.1887021"},{"key":"e_1_2_7_10_1","unstructured":"PinheiroJ BD DebRoyS SarkarD;R Core Team.nlme: linear and nonlinear mixed effects models.2017; R package version 3.1\u2010131 https:\/\/CRAN.R-project.org\/package=nlme. 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