{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T20:39:35Z","timestamp":1774557575047,"version":"3.50.1"},"reference-count":21,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T00:00:00Z","timestamp":1715299200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100005246","name":"Institute of Education Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005246","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["bpspsychub.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Brit J Math &amp;amp; Statis"],"published-print":{"date-parts":[[2025,2]]},"abstract":"<jats:p>Oral reading fluency (ORF) assessments are commonly used to screen at\u2010risk readers and evaluate interventions' effectiveness as curriculum\u2010based measurements. Similar to the standard practice in item response theory (IRT), calibrated passage parameter estimates are currently used as if they were population values in model\u2010based ORF scoring. However, calibration errors that are unaccounted for may bias ORF score estimates and, in particular, lead to underestimated standard errors (SEs) of ORF scores. Therefore, we consider an approach that incorporates the calibration errors in latent variable scores. We further derive the SEs of ORF scores based on the delta method to incorporate the calibration uncertainty. We conduct a simulation study to evaluate the recovery of point estimates and SEs of latent variable scores and ORF scores in various simulated conditions. Results suggest that ignoring calibration errors leads to underestimated latent variable score SEs and ORF score SEs, especially when the calibration sample is small.<\/jats:p>","DOI":"10.1111\/bmsp.12348","type":"journal-article","created":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T05:05:30Z","timestamp":1715317530000},"page":"44-60","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Incorporating calibration errors in oral reading fluency scoring"],"prefix":"10.1111","volume":"78","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3248-7859","authenticated-orcid":false,"given":"Xin","family":"Qiao","sequence":"first","affiliation":[{"name":"University of South Florida  Tampa Florida USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9570-1464","authenticated-orcid":false,"given":"Akihito","family":"Kamata","sequence":"additional","affiliation":[{"name":"Southern Methodist University  Dallas Texas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1995-6817","authenticated-orcid":false,"given":"Cornelis","family":"Potgieter","sequence":"additional","affiliation":[{"name":"Texas Christian University  Fort Worth Texas USA"},{"name":"University of Johannesburg  Johannesburg South\u00a0Africa"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2024,5,10]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1977.tb01600.x"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1207\/S1532799XSSR0503_3"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1177\/074193258800900206"},{"key":"e_1_2_10_5_1","unstructured":"Hasbrouck J. &Tindal G.(2017).An update to compiled orf norms. 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