Lisa Calvocoressi, PhD
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Senior Lecturer
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Dr. Calvocoressi is best known for her work in obsessive-compulsive disorder. She conducted pioneering work in understanding the role of the family in OCD and developed the original Family Accommodation Scale. There are now several versions of the scale, which have been translated into multiple languages and are used worldwide in research and clinical practice. The scale examines the ways in which relatives may participate in OCD behaviors along with the diagnosed family member or may modify their work or social functioning to accommodate the OCD. Dr. Calvocoressi is currently overseeing a large psychometric study of the self-rated version of the scale. She and her colleagues are also developing a measure to examine relatives' motivations for engaging in accommodating behaviors.
Dr. Calvocoressi oversees the MS program in biostatistics; she co-teaches the graduate biostatistics capstone course, Statistical Practice; and, she is the director of the Young Scholars Program and Internship in Biostatistics and Clinical Research, a program for gifted and talented high school students.
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Biostatistics
Senior LecturerPrimaryBiostatistics
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Education & Training
- PhD
- Yale University School of Medicine (2003)
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Family Accommodation in Obsessive-Compulsive Disorder
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Elizabeth Claus, PhD, MD
Benjamin Johnson
Beth Anne Jones, PhD, MPH
Lingeng Lu, MD, PhD
Michael Rowe, PhD
Veronika Shabanova, PhD
Meningioma
Mammography
Obsessive-Compulsive Disorder
Publications
2024
Choosing Between the Bi-Factor and Second-Order Factor Models: A Direct Test Using Latent Variable Modeling
Raykov T, Calvocoressi L, Schumacker R. Choosing Between the Bi-Factor and Second-Order Factor Models: A Direct Test Using Latent Variable Modeling. Measurement Interdisciplinary Research And Perspectives 2024, 22: 31-50. DOI: 10.1080/15366367.2023.2173547.Peer-Reviewed Original ResearchCitationsAltmetric
2023
A Note on Comparing the Bifactor and Second-Order Factor Models: Is the Bayesian Information Criterion a Routinely Dependable Index for Model Selection?
Raykov T, DiStefano C, Calvocoressi L. A Note on Comparing the Bifactor and Second-Order Factor Models: Is the Bayesian Information Criterion a Routinely Dependable Index for Model Selection? Educational And Psychological Measurement 2023, 84: 271-288. PMID: 38898876, PMCID: PMC11185100, DOI: 10.1177/00131644231166348.Peer-Reviewed Original ResearchCitations
2022
On Effect Size Measures for Nested Measurement Models
Raykov T, DiStefano C, Calvocoressi L, Volker M. On Effect Size Measures for Nested Measurement Models. Educational And Psychological Measurement 2022, 82: 1225-1246. PMID: 36325123, PMCID: PMC9619317, DOI: 10.1177/00131644211066845.Peer-Reviewed Original ResearchCitationsAltmetricConceptsEffect size measuresNumerical examplesFactor analysis modelParameter restrictionsLinear combinationTerms of fitExplicit relationshipObserved variablesManifest variablesSize measuresEffect size indexConfirmatory factor analysis modelMeasurement modelPopular softwareModelSample sizeAnalysis modelVariablesPleiotropic MLLT10 variation confers risk of meningioma and estrogen-mediated cancers
Walsh KM, Zhang C, Calvocoressi L, Hansen HM, Berchuck A, Schildkraut JM, Bondy ML, Wrensch M, Wiemels JL, Claus EB. Pleiotropic MLLT10 variation confers risk of meningioma and estrogen-mediated cancers. Neuro-Oncology Advances 2022, 4: vdac044. PMID: 35702670, PMCID: PMC9187056, DOI: 10.1093/noajnl/vdac044.Peer-Reviewed Original ResearchCitationsAltmetricConceptsRisk of meningiomaOvarian cancerBreast cancerER- breast cancerEstrogen receptor statusBody mass indexFemale breast cancerRisk of tumorsReceptor statusMass indexEstrogenic mechanismsHormonal factorsGenome-wide association studiesMeningiomasNormal meningesCancerMinor alleleCase-control datasetUK BiobankExpression quantitative trait lociMeningesRiskTumorsBreastAdiposity traits
2021
Translation and Cross-Cultural Adaptation of the Family Accommodation Scale for Obsessive-Compulsive Disorder Into Chinese.
Liao Z, You C, Chen Y, Yan L, Zhang J, Li F, Calvocoressi L, Ding L. Translation and Cross-Cultural Adaptation of the Family Accommodation Scale for Obsessive-Compulsive Disorder Into Chinese. Journal Of Cognitive Psychotherapy 2021, 35: 41-52. PMID: 33397786, DOI: 10.1891/jcpsy-d-20-00020.Peer-Reviewed Original ResearchCitationsConceptsCross-cultural adaptationOriginal English scaleLanguage adjustmentEnglish scaleFamily Accommodation ScaleConceptual equivalenceEnglish versionCultural adaptationPilot administrationChinese scaleChinese versionTranslationSteps of translationDifferent education levelsMinor editsChineseAccommodation ScalePretest stageVersionDifferent socioeconomic statusAccommodationPeopleEditsAdaptationFamily members
2020
Model Selection and Average Proportion Explained Variance in Exploratory Factor Analysis
Raykov T, Calvocoressi L. Model Selection and Average Proportion Explained Variance in Exploratory Factor Analysis. Educational And Psychological Measurement 2020, 81: 1203-1220. PMID: 34565821, PMCID: PMC8451025, DOI: 10.1177/0013164420963162.Peer-Reviewed Original ResearchCitationsAltmetricQuality and Publication of Emergency Medicine Trials Registered in ClinicalTrials.gov
Calvocoressi L, Reynolds J, Johnson B, Warzoha MM, Carroll M, Vaca FE, Post L, Dziura J. Quality and Publication of Emergency Medicine Trials Registered in ClinicalTrials.gov. Western Journal Of Emergency Medicine 2020, 21: 295-303. PMID: 32191186, PMCID: PMC7081876, DOI: 10.5811/westjem.2019.12.44096.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsClinical trialsEM trialsKaplan-Meier curvesLog-rank testNational clinical trialClinical trial researchChi-square testEM studiesTrial qualityInterventional trialsPeer-reviewed journalsMedicine trialsNeurological conditionsLarger sample sizeTrial researchStudy characteristicsStudy periodTrialsNational InstituteSubspecialty areasBlindingPeriodic assessmentDescriptive statisticsHigher proportionIndustry funding
2019
Social media partnerships with patient organizations for neuro-oncology patient recruitment
Claus EB, Feliciano J, Benz LS, Calvocoressi L. Social media partnerships with patient organizations for neuro-oncology patient recruitment. Neuro-Oncology Practice 2019, 7: 143-151. PMID: 32626583, PMCID: PMC7318861, DOI: 10.1093/nop/npz049.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsCitationsAltmetricConceptsNeuro-oncology patientsPatient organizationsNational Cancer Institute's SurveillanceEnd Results (SEER) dataTumor RegistryPathology reportsTreatment responsePatient recruitmentEpidemiologic studiesNeuro-oncologyPatientsYale University SchoolSaliva specimenSuccessful enrollmentEnrollment methodsDisease etiologyAssociation websitesRegistryPublic healthUniversity SchoolParticipant populationResult dataSurveillanceOnline questionnaireParticipantsMendelian randomization provides support for obesity as a risk factor for meningioma
Takahashi H, Cornish AJ, Sud A, Law PJ, Disney-Hogg L, Calvocoressi L, Lu L, Hansen HM, Smirnov I, Walsh KM, Schramm J, Hoffmann P, Nöthen MM, Jöckel KH, Schildkraut JM, Simon M, Bondy M, Wrensch M, Wiemels JL, Claus EB, Turnbull C, Houlston RS. Mendelian randomization provides support for obesity as a risk factor for meningioma. Scientific Reports 2019, 9: 309. PMID: 30670737, PMCID: PMC6343031, DOI: 10.1038/s41598-018-36186-6.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsRisk of meningiomaMeningioma riskObesity-related traitsLipoprotein cholesterolBlood pressureRisk factorsOdds ratioLow-density lipoprotein cholesterolHigh-density lipoprotein cholesterolMendelian randomizationCause of meningiomaGenetic instrumentsDiastolic blood pressureEpidemiological observational studiesSystolic blood pressureBody mass indexBody fat percentageWaist circumferenceTotal cholesterolMass indexObservational studyMeningioma patientsMeningiomasBasal metabolic rateObesity
2018
Validation of the International Guide for Monitoring Child Development demonstrates good sensitivity and specificity in four diverse countries
Ertem IO, Krishnamurthy V, Mulaudzi MC, Sguassero Y, Bilik B, Srinivasan R, Balta H, Gulumser O, Gan G, Calvocoressi L, Johnson B, Shabanova V, Forsyth B. Validation of the International Guide for Monitoring Child Development demonstrates good sensitivity and specificity in four diverse countries. Acta Paediatrica 2018, 108: 1074-1086. PMID: 30472813, PMCID: PMC6520130, DOI: 10.1111/apa.14661.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and Concepts
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- February 22, 2023
YSPH biostatistician part of award-winning Yale team
- November 05, 2021Source: Yale Daily News
FDA and the School of Medicine collaborate to promote diversity in clinical trials
- September 28, 2020
Biostatistics Leadership Allows YCAS to Improve Clinical Investigations
- April 10, 2012
Non-cancerous Brain Tumors Linked to Frequent Dental X-rays
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