{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T12:24:22Z","timestamp":1768479862473,"version":"3.49.0"},"reference-count":58,"publisher":"Informa UK Limited","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>In this article, we demonstrate the potential of machine learning approaches as inductive analytic tools for expanding our current evidence base for policy making and practice that affects people with intellectual and developmental disabilities (IDD). Using data from the National Core Indicators In-Person Survey (NCI-IPS), a nationally validated annual survey of more than 20,000 nationally representative people with IDD, we fit a series of classification tree and random forest models to predict individuals' employment status and day activity participation as a function of their responses to all other items on the 2017\u20132018 NCI-IPS. The most accurate model, a random forest classifier, predicted employment outcomes of adults with IDD with an accuracy of 89 percent on the testing sample, and 80 percent on the holdout sample. The most important variable in this prediction was whether or not community employment was a goal in this person's service plan. These results suggest the potential machine learning tools to examine other valued outcomes used in evidence-based policy making to support people with IDD.<\/jats:p>","DOI":"10.1352\/1944-7558-126.6.477","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T13:12:58Z","timestamp":1635340378000},"page":"477-491","source":"Crossref","is-referenced-by-count":8,"title":["Using Machine Learning to Predict Patterns of Employment and Day Program Participation"],"prefix":"10.1080","volume":"126","author":[{"given":"Michael D.","family":"Broda","sequence":"first","affiliation":[{"name":"Michael D. Broda, Matthew Bogenschutz, Parthenia Dinora, Seb M. Prohn, Sarah Lineberry, and Erica Ross, Virginia Commonwealth University."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew","family":"Bogenschutz","sequence":"additional","affiliation":[{"name":"Michael D. Broda, Matthew Bogenschutz, Parthenia Dinora, Seb M. Prohn, Sarah Lineberry, and Erica Ross, Virginia Commonwealth University."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Parthenia","family":"Dinora","sequence":"additional","affiliation":[{"name":"Michael D. Broda, Matthew Bogenschutz, Parthenia Dinora, Seb M. Prohn, Sarah Lineberry, and Erica Ross, Virginia Commonwealth University."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seb M.","family":"Prohn","sequence":"additional","affiliation":[{"name":"Michael D. Broda, Matthew Bogenschutz, Parthenia Dinora, Seb M. Prohn, Sarah Lineberry, and Erica Ross, Virginia Commonwealth University."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah","family":"Lineberry","sequence":"additional","affiliation":[{"name":"Michael D. Broda, Matthew Bogenschutz, Parthenia Dinora, Seb M. Prohn, Sarah Lineberry, and Erica Ross, Virginia Commonwealth University."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erica","family":"Ross","sequence":"additional","affiliation":[{"name":"Michael D. Broda, Matthew Bogenschutz, Parthenia Dinora, Seb M. Prohn, Sarah Lineberry, and Erica Ross, Virginia Commonwealth University."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"301","published-online":{"date-parts":[[2021,10,26]]},"reference":[{"key":"2021102717123080100_i1944-7558-126-6-477-AmericansWithDisabilitiesActof1","unstructured":"Americans With Disabilities Act of 1990, Pub. L. No. 101-336, 104 Stat. 328 (1990)."},{"key":"2021102717123080100_i1944-7558-126-6-477-NoAuthors1","unstructured":"Association of People Supporting Employment First.\n          (n.d.).\n\t\t\t\t\tAPSE fact sheet: Employment First.\n\t\t\t\t\thttps:\/\/www.apse.org\/wp-content\/uploads\/docs\/Employment%20First%20-%20Legislator%20Fact%20Sheet.pdf"},{"key":"2021102717123080100_i1944-7558-126-6-477-AssociationofPeopleSupportingEmploymentFirst1","unstructured":"Association of People Supporting Employment First.\n          (2020).\n\t\t\t\t\tEmployment First map.\n\t\t\t\t\thttps:\/\/apse.org\/employment-first-map"},{"key":"2021102717123080100_i1944-7558-126-6-477-Baker1","doi-asserted-by":"crossref","unstructured":"Baker,\n              R. S.,\n             &\n\t\t\t\t\t\tInventado,P. S.\n          (2014).\n\t\t\t\t\tEducational data mining and learning analytics.\n\t\t\t\t\tInLarussonJ.A. &\n\t\t\t\t\t\tWhiteB.,(Eds.),Learning analytics: From research to practice(pp.61\u2013\n\t\t\t\t\t75).\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-1-4614-3305-7_4"},{"key":"2021102717123080100_i1944-7558-126-6-477-Berk1","doi-asserted-by":"crossref","unstructured":"Berk,\n              R.\n            \n          \n          (2019).\n\t\t\t\t\tMachine learning risk assessments in criminal justice settings.\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-3-030-02272-3"},{"key":"2021102717123080100_i1944-7558-126-6-477-Bertoncelli1","doi-asserted-by":"crossref","unstructured":"Bertoncelli,\n              C. M.,\n            \n            \n              Altamura,\n              P.,\n            \n            \n              Vieira,\n              E. R.,\n            \n            \n              Bertoncelli,\n              D.,\n             &\n\t\t\t\t\t\tSolla,F.\n          (2019).\n\t\t\t\t\tUsing artificial intelligence to identify factors associated with autism spectrum disorder in adolescents with cerebral palsy.\n\t\t\t\t\tNeuropediatrics, 50(3),\n\t\t\t\t\t178\u2013\n\t\t\t\t\t187.\n\t\t\t\t\thttp:\/\/doi.org\/10.1055\/s-0039-1685525","DOI":"10.1055\/s-0039-1685525"},{"key":"2021102717123080100_i1944-7558-126-6-477-Beyer1","doi-asserted-by":"crossref","unstructured":"Beyer,\n              S.,\n            \n            \n              Brown,\n              T.,\n            \n            \n              Akandi,\n              R.,\n             &\n\t\t\t\t\t\tRapley,M.\n          (2010).\n\t\t\t\t\tA comparison of quality of life outcomes for people with intellectual disabilities in supported employment, day services and employment enterprises.\n\t\t\t\t\tJournal of Applied Research in Intellectual Disabilities, 23(3),\n\t\t\t\t\t290\u2013\n\t\t\t\t\t295.\n\t\t\t\t\thttps:\/\/doi.org\/10.1111\/j.1468-3148.2009.00534.x","DOI":"10.1111\/j.1468-3148.2009.00534.x"},{"key":"2021102717123080100_i1944-7558-126-6-477-BishopFitzpatrick1","doi-asserted-by":"crossref","unstructured":"Bishop-Fitzpatrick,\n              L.,\n            \n            \n              Movaghar,\n              A.,\n            \n            \n              Greenberg,\n              J. S.,\n            \n            \n              Page,\n              D.,\n            \n            \n              DeWalt,\n              L. S.,\n            \n            \n              Brilliant,\n              M. G.,\n             &\n\t\t\t\t\t\tMailick,M.\n          (2018).\n\t\t\t\t\tUsing machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.\n\t\t\t\t\tAutism Research, 11,\n\t\t\t\t\t1120\u2013\n\t\t\t\t\t1128.\n\t\t\t\t\thttps:\/\/doi.org\/10.1002\/aur.1960","DOI":"10.1002\/aur.1960"},{"key":"2021102717123080100_i1944-7558-126-6-477-Bonardi1","unstructured":"Bonardi,\n              A.,\n            \n            \n              Krahn,\n              G.,\n            \n            \n              Morris,\n              A.,\n             &\n\t\t\t\t\t\tthe National Workgroup on State and Local Health Data\n          (2019).\n\t\t\t\t\tEnriching our knowledge: State and local data to inform health surveillance of the population with intellectual and developmental disabilities.\n\t\t\t\t\tAdministration on Intellectual and Developmental Disabilities.https:\/\/doi-org.proxy.library.vcu.edu\/10.1352\/1934-9556-57.5.390"},{"key":"2021102717123080100_i1944-7558-126-6-477-Breiman1","doi-asserted-by":"crossref","unstructured":"Breiman,\n              L.\n            \n          \n          (2001a).\n\t\t\t\t\tRandom forests.\n\t\t\t\t\tMachine Learning,\n\t\t\t\t\t45(1),\n\t\t\t\t\t5\u2013\n\t\t\t\t\t32.\n\t\t\t\t\thttp:\/\/dx.doi.org\/10.1023\/A:1010933404324","DOI":"10.1023\/A:1010933404324"},{"key":"2021102717123080100_i1944-7558-126-6-477-Breiman2","doi-asserted-by":"crossref","unstructured":"Breiman,\n              L.\n            \n          \n          (2001b).\n\t\t\t\t\tStatistical modeling: The two cultures (with comments and a rejoinder by the author).\n\t\t\t\t\tStatistical Science, 16(3),\n\t\t\t\t\t199\u2013\n\t\t\t\t\t231.\n\t\t\t\t\thttp:\/\/dx.doi.org\/10.1214\/ss\/1009213726","DOI":"10.1214\/ss\/1009213726"},{"key":"2021102717123080100_i1944-7558-126-6-477-Bush1","doi-asserted-by":"crossref","unstructured":"Bush,\n              K. L.,\n             &\n\t\t\t\t\t\tTass\u00e9,M. J.\n          (2017).\n\t\t\t\t\tEmployment and choice-making for adults with intellectual disability, autism, and Down syndrome.\n\t\t\t\t\tResearch in Developmental Disabilities,\n\t\t\t\t\t65,\n\t\t\t\t\t23\u2013\n\t\t\t\t\t34.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.ridd.2017.04.004","DOI":"10.1016\/j.ridd.2017.04.004"},{"key":"2021102717123080100_i1944-7558-126-6-477-Butterworth1","doi-asserted-by":"crossref","unstructured":"Butterworth,\n              J.,\n            \n            \n              Hiersteiner,\n              D.,\n            \n            \n              Engler,\n              J.,\n            \n            \n              Bershadsky,\n              J.,\n             &\n\t\t\t\t\t\tBradley,V.\n          (2015).\n\t\t\t\t\tNational Core Indicators\u00a9: Data on the current state of employment of adults with IDD and suggestions for policy development.\n\t\t\t\t\tJournal of Vocational Rehabilitation, 42(3),\n\t\t\t\t\t209\u2013\n\t\t\t\t\t220.\n\t\t\t\t\thttps:\/\/doi.org\/10.3233\/JVR-150741","DOI":"10.3233\/JVR-150741"},{"key":"2021102717123080100_i1944-7558-126-6-477-Carter1","doi-asserted-by":"crossref","unstructured":"Carter,\n              E. W.,\n            \n            \n              Austin,\n              D.,\n             &\n\t\t\t\t\t\tTrainor,A. A.\n          (2012).\n\t\t\t\t\tPredictors of postschool employment outcomes for young adults with severe disabilities.\n\t\t\t\t\tJournal of Disability Policy Studies, 23(1),\n\t\t\t\t\t50\u2013\n\t\t\t\t\t63.\n\t\t\t\t\thttps:\/\/doi.org\/10.1177\/1044207311414680","DOI":"10.1177\/1044207311414680"},{"key":"2021102717123080100_i1944-7558-126-6-477-Chan1","doi-asserted-by":"crossref","unstructured":"Chan,\n              W.,\n            \n            \n              Smith,\n              L. E.,\n            \n            \n              Hong,\n              J.,\n            \n            \n              Greenberg,\n              J. S.,\n            \n            \n              Lounds Taylor,\n              J.\n             &\n\t\t\t\t\t\tMailick,M. R.\n          (2018).\n\t\t\t\t\tFactors associated with sustained community employment among adults with autism and co-occurring intellectual disability.\n\t\t\t\t\tAutism, 22(7),\n\t\t\t\t\t794\u2013\n\t\t\t\t\t803.\n\t\t\t\t\thttps:\/\/doi.org\/10.1177\/1362361317703760","DOI":"10.1177\/1362361317703760"},{"key":"2021102717123080100_i1944-7558-126-6-477-Chung1","doi-asserted-by":"crossref","unstructured":"Chung,\n              J. Y.,\n             &\n\t\t\t\t\t\tLee,S.\n          (2019).\n\t\t\t\t\tDropout early warning systems for high school students using machine learning.\n\t\t\t\t\tChildren and Youth Services Review, 96,\n\t\t\t\t\t346\u2013\n\t\t\t\t\t353.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.childyouth.2018.11.030","DOI":"10.1016\/j.childyouth.2018.11.030"},{"key":"2021102717123080100_i1944-7558-126-6-477-Chawla1","doi-asserted-by":"crossref","unstructured":"Chawla,\n              N. V.,\n            \n            \n              Bowyer,\n              K. W.,\n            \n            \n              Hall,\n              L. O.,\n             &\n\t\t\t\t\t\tKegelmeyer,W. P.\n          (2002).\n\t\t\t\t\tSMOTE: Synthetic minority over-sampling technique.\n\t\t\t\t\tThe Journal of Artificial Intelligence Research,\n\t\t\t\t\t16,\n\t\t\t\t\t321\u2013\n\t\t\t\t\t357.\n\t\t\t\t\thttps:\/\/doi.org\/10.1613\/jair.953","DOI":"10.1613\/jair.953"},{"key":"2021102717123080100_i1944-7558-126-6-477-Dinora1","doi-asserted-by":"crossref","unstructured":"Dinora,\n              P.,\n            \n            \n              Bogenschutz,\n              M.,\n             &\n\t\t\t\t\t\tBroda,M.\n          (2020).\n\t\t\t\t\tIdentifying predictors for enhanced outcomes for people with intellectual and developmental disabilities.\n\t\t\t\t\tIntellectual and Developmental Disabilities,\n\t\t\t\t\t58(2),\n\t\t\t\t\t139\u2013\n\t\t\t\t\t157.\n\t\t\t\t\thttps:\/\/doi.org\/10.1352\/1934-9556-58.2.139","DOI":"10.1352\/1934-9556-58.2.139"},{"key":"2021102717123080100_i1944-7558-126-6-477-Gromping1","doi-asserted-by":"crossref","unstructured":"Gr\u00f6mping,\n              U.\n            \n          \n          (2009).\n\t\t\t\t\tVariable importance assessment in regression: Linear regression versus random forest.\n\t\t\t\t\tThe American Statistician,\n\t\t\t\t\t63(4),\n\t\t\t\t\t308\u2013\n\t\t\t\t\t319.\n\t\t\t\t\thttp:\/\/dx.doi.org\/10.1198\/tast.2009.08199","DOI":"10.1198\/tast.2009.08199"},{"key":"2021102717123080100_i1944-7558-126-6-477-Havercamp1","unstructured":"Havercamp,\n              S.\n            \n          \n          (2019).\n\t\t\t\t\tImproving data collected on people with intellectual and developmental disabilities.\n\t\t\t\t\thttps:\/\/thehill.com\/opinion\/healthcare\/465524-improving-data-on-people-with-intellectual-and-developmental-disabilities"},{"key":"2021102717123080100_i1944-7558-126-6-477-Havercamp2","doi-asserted-by":"crossref","unstructured":"Havercamp,\n              S. M.,\n            \n            \n              Krahn,\n              G. L.,\n            \n            \n              Larson,\n              S. A.,\n            \n            \n              Fujiura,\n              G.,\n            \n            \n              Goode,\n              T. D.,\n            \n            \n              Kornblau,\n              B. L.,\n             &\n\t\t\t\t\t\tNational Health Surveillance for IDD Workgroup.\n\t\t\t\t\t(2019).\n\t\t\t\t\tIdentifying people with intellectual and developmental disabilities in national population surveys.\n\t\t\t\t\tIntellectual and Developmental Disabilities, 57(5),\n\t\t\t\t\t376\u2013\n\t\t\t\t\t389.\n\t\t\t\t\thttps:\/\/doi.org\/10.1352\/1934-9556-57.5.376","DOI":"10.1352\/1934-9556-57.5.376"},{"key":"2021102717123080100_i1944-7558-126-6-477-Hoff1","unstructured":"Hoff,\n              D.,\n             &\n\t\t\t\t\t\tHolz,N.\n          (2020).\n\t\t\t\t\tEmployment and employment supports: A guide to ensuring informed choice for individuals with disabilities.\n\t\t\t\t\tInstitute on Community Inclusion Tools for Inclusion, 31.\n\t\t\t\t\thttps:\/\/archive.communityinclusion.org\/pdf\/TO31_F.pdf"},{"key":"2021102717123080100_i1944-7558-126-6-477-HSRINASDDDS1","unstructured":"Human Services Research Institute & National Association of State Directors of Developmental Disability Services.\n          (2018).\n\t\t\t\t\tIn-Person survey 2017-2018: Final report.\n\t\t\t\t\thttps:\/\/www.nationalcoreindicators.org\/upload\/core-indicators\/17-18_IPS_National_Report_PART_I_update_CA_entitlement.pdf"},{"key":"2021102717123080100_i1944-7558-126-6-477-Hyde1","doi-asserted-by":"crossref","unstructured":"Hyde,\n              K. K.,\n            \n            \n              Novack,\n              M. N.,\n            \n            \n              LaHaye,\n              N.,\n            \n            \n              Parlett-Pelleriti,\n              C.,\n            \n            \n              Anden,\n              R.,\n            \n            \n              Dixon,\n              D. R.,\n             &\n\t\t\t\t\t\tLinstead,E.\n          (2019).\n\t\t\t\t\tApplications of supervised machine learning in autism spectrum disorder research: A review.\n\t\t\t\t\tReview Journal of Autism and Developmental Disorders, 6,\n\t\t\t\t\t128\u2013\n\t\t\t\t\t146.\n\t\t\t\t\thttp:\/\/doi.org\/10.1007\/s40489-019-00158-x","DOI":"10.1007\/s40489-019-00158-x"},{"key":"2021102717123080100_i1944-7558-126-6-477-James1","doi-asserted-by":"crossref","unstructured":"James,\n              G.,\n            \n            \n              Witten,\n              D.,\n            \n            \n              Hastie,\n              T.,\n             &\n\t\t\t\t\t\tTibshirani,R.\n          (2013).\n\t\t\t\t\tAn introduction to statistical learning (Vol. 112).\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-1-4614-7138-7"},{"key":"2021102717123080100_i1944-7558-126-6-477-Kavakiotis1","doi-asserted-by":"crossref","unstructured":"Kavakiotis,\n              I.,\n            \n            \n              Tsave,\n              O.,\n            \n            \n              Salifoglou,\n              A.,\n            \n            \n              Maglaveras,\n              N.,\n            \n            \n              Vlahavas,\n              I.,\n             &\n\t\t\t\t\t\tChouvarda,I.\n          (2017).\n\t\t\t\t\tMachine learning and data mining methods in diabetes research.\n\t\t\t\t\tComputational and Structural Biotechnology Journal, 15,\n\t\t\t\t\t104\u2013\n\t\t\t\t\t116.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.csbj.2016.12.005","DOI":"10.1016\/j.csbj.2016.12.005"},{"key":"2021102717123080100_i1944-7558-126-6-477-Kaya1","doi-asserted-by":"crossref","unstructured":"Kaya,\n              C.\n            \n          \n          (2018).\n\t\t\t\t\tDemographic variables, vocational rehabilitation services, and employment outcomes for transition-age youth with intellectual disabilities.\n\t\t\t\t\tJournal of Policy and Practice in Intellectual Disabilities, 15(3),\n\t\t\t\t\t226\u2013\n\t\t\t\t\t236.\n\t\t\t\t\thttps:\/\/doi.org\/10.1111\/jppi.12249","DOI":"10.1111\/jppi.12249"},{"key":"2021102717123080100_i1944-7558-126-6-477-Kuhn1","doi-asserted-by":"crossref","unstructured":"Kuhn,\n              M.,\n             &\n\t\t\t\t\t\tJohnson,K.\n          (2013).\n\t\t\t\t\tApplied predictive modeling.\n\t\t\t\t\tSpringer.","DOI":"10.1007\/978-1-4614-6849-3"},{"key":"2021102717123080100_i1944-7558-126-6-477-Kuhn2","unstructured":"Kuhn,\n              M.,\n             &\n\t\t\t\t\t\tWickham,H.\n          (2020).\n\t\t\t\t\tTidymodels: A collection of packages for modeling and machine learning using tidyverse principles.\n\t\t\t\t\thttps:\/\/www.tidymodels.org"},{"key":"2021102717123080100_i1944-7558-126-6-477-Lin1","doi-asserted-by":"crossref","unstructured":"Lin,\n              E.,\n            \n            \n              Balogh,\n              R.,\n            \n            \n              Cobigo,\n              V.,\n            \n            \n              Ouellette-Kuntz,\n              H.,\n            \n            \n              Wilton,\n              A.,\n             &\n\t\t\t\t\t\tLunsky,Y.\n          (2013).\n\t\t\t\t\tUsing administrative health data to identify individuals with intellectual and developmental disabilities: A comparison of algorithms.\n\t\t\t\t\tJournal of Intellectual Disability Research, 57(5),\n\t\t\t\t\t462\u2013\n\t\t\t\t\t477.\n\t\t\t\t\thttp:\/\/doi.org\/10.1111\/jir.12002","DOI":"10.1111\/jir.12002"},{"key":"2021102717123080100_i1944-7558-126-6-477-Loh1","doi-asserted-by":"crossref","unstructured":"Loh,\n              W. Y.\n            \n          \n          (2014).\n\t\t\t\t\tFifty years of classification and regression trees.\n\t\t\t\t\tInternational Statistical Review,\n\t\t\t\t\t82(3),\n\t\t\t\t\t329\u2013\n\t\t\t\t\t348.\n\t\t\t\t\thttps:\/\/doi.org\/10.1111\/insr.12016","DOI":"10.1111\/insr.12016"},{"key":"2021102717123080100_i1944-7558-126-6-477-Maenner1","doi-asserted-by":"crossref","unstructured":"Maenner,\n              M. J.,\n            \n            \n              Yeargin-Allsopp,\n              M.,\n            \n            \n              Van Naarden Braun,\n              K.,\n            \n            \n              Christensen,\n              D. L.,\n             &\n\t\t\t\t\t\tAchieve,L. A.\n          (2016).\n\t\t\t\t\tDevelopment of a machine learning algorithm for the surveillance of autism spectrum disorder.\n\t\t\t\t\tPLoS ONE, 11(12), e0168224.http:\/\/doi.org\/journal.pone.0168224","DOI":"10.1371\/journal.pone.0168224"},{"key":"2021102717123080100_i1944-7558-126-6-477-MedicaidProgram1","unstructured":"Medicaid Program; State Plan Home and Community-Based Services, 5-Year Period for Waivers, Provider Payment Reassignment, and Home and Community-Based Setting Requirements for Community First Choice and Home and Community-Based Services (HCBS) Waivers, 79 Fed. Reg. 2948\n          (2014).\n\t\t\t\t\thttps:\/\/www.federalregister.gov\/documents\/2014\/01\/16\/2014-00487\/medicaid-program-state-plan-home-and-community-based-services-5-year-period-for-waivers-provider"},{"key":"2021102717123080100_i1944-7558-126-6-477-Miller1","unstructured":"Miller,\n              K. D.,\n            \n            \n              Schleien,\n              S. J.,\n            \n            \n              Rider,\n              C.,\n            \n            \n              Hall,\n              C.,\n            \n            \n              Roche,\n              M.,\n             &\n\t\t\t\t\t\tWorsley,J.\n          (2002).\n\t\t\t\t\tInclusive volunteering: Benefits to participants and community.\n\t\t\t\t\tTherapeutic Recreation Journal,\n\t\t\t\t\t36(3),\n\t\t\t\t\t247\u2013\n\t\t\t\t\t259."},{"key":"2021102717123080100_i1944-7558-126-6-477-Molinaro1","doi-asserted-by":"crossref","unstructured":"Molinaro,\n              A. M.,\n            \n            \n              Simon,\n              R.,\n             &\n\t\t\t\t\t\tPfeiffer,R. M.\n          (2005).\n\t\t\t\t\tPrediction error estimation: A comparison of resampling methods.\n\t\t\t\t\tBioinformatics, 21(15),\n\t\t\t\t\t3301\u2013\n\t\t\t\t\t3307.\n\t\t\t\t\thttp:\/\/dx.doi.org\/10.1093\/bioinformatics\/bti499","DOI":"10.1093\/bioinformatics\/bti499"},{"key":"2021102717123080100_i1944-7558-126-6-477-Murdoch1","doi-asserted-by":"crossref","unstructured":"Murdoch,\n              W. J.,\n            \n            \n              Singh,\n              C.,\n            \n            \n              Kumbier,\n              K.,\n            \n            \n              Abbasi-Asl,\n              R.,\n             &\n\t\t\t\t\t\tYu,B.\n          (2019).\n\t\t\t\t\tDefinitions, methods, and applications in interpretable machine learning.\n\t\t\t\t\tProceedings of the National Academy of Sciences of the United States of America,\n\t\t\t\t\t116(44),\n\t\t\t\t\t22071\u2013\n\t\t\t\t\t22080.\n\t\t\t\t\thttps:\/\/doi.org\/10.1073\/pnas.1900654116","DOI":"10.1073\/pnas.1900654116"},{"key":"2021102717123080100_i1944-7558-126-6-477-Nord1","doi-asserted-by":"crossref","unstructured":"Nord,\n              D.,\n            \n            \n              Grossi,\n              T.,\n             &\n\t\t\t\t\t\tAndresen,J.\n          (2020).\n\t\t\t\t\tEmployment equity for people with IDD across the lifespan: The effects of state funding.\n\t\t\t\t\tIntellectual and Developmental Disabilities, 58(4),\n\t\t\t\t\t288\u2013\n\t\t\t\t\t300.\n\t\t\t\t\thttps:\/\/doi.org\/10.1352\/1934-9556-58.4.288","DOI":"10.1352\/1934-9556-58.4.288"},{"key":"2021102717123080100_i1944-7558-126-6-477-Nord2","doi-asserted-by":"crossref","unstructured":"Nord,\n              D.,\n            \n            \n              Hamre,\n              K.,\n            \n            \n              Pettingell,\n              S.,\n             &\n\t\t\t\t\t\tMagiera,L.\n          (2018).\n\t\t\t\t\tEmployment goals and settings: Effects of individual and systemic factors.\n\t\t\t\t\tResearch and Practice for Persons with Severe Disabilities, 43(3),\n\t\t\t\t\t194\u2013\n\t\t\t\t\t206.\n\t\t\t\t\thttps:\/\/doi.org\/10.1177\/1540796918785352","DOI":"10.1177\/1540796918785352"},{"key":"2021102717123080100_i1944-7558-126-6-477-Park1","doi-asserted-by":"crossref","unstructured":"Park,\n              J.,\n             &\n\t\t\t\t\t\tBouck,E.\n          (2018).\n\t\t\t\t\tIn-school service predictors of employment for individuals with intellectual disability.\n\t\t\t\t\tResearch in Developmental Disabilities, 77,\n\t\t\t\t\t68\u2013\n\t\t\t\t\t75.\n\t\t\t\t\thttps:\/\/doi.org\/10.1016\/j.ridd.2018.03.014","DOI":"10.1016\/j.ridd.2018.03.014"},{"key":"2021102717123080100_i1944-7558-126-6-477-RCoreTeam1","unstructured":"R Core Team.\n          (2020).\n\t\t\t\t\tR: A language and environment for statistical computing.\n\t\t\t\t\tR Foundation for Statistical Computing,\n\t\t\t\t\tVienna, Austria.\n\t\t\t\t\tURL https:\/\/www.R-project.org\/."},{"key":"2021102717123080100_i1944-7558-126-6-477-RStudioTeam1","unstructured":"RStudio Team.\n          (2020).\n\t\t\t\t\tRStudio: Integrated development for R [Computer software].\n\t\t\t\t\tRStudio,\n\t\t\t\t\tInc.\n\t\t\t\t\thttp:\/\/www.rstudio.com"},{"key":"2021102717123080100_i1944-7558-126-6-477-Rudin1","doi-asserted-by":"crossref","unstructured":"Rudin,\n              C.,\n             &\n\t\t\t\t\t\tUstun,B.\n          (2019).\n\t\t\t\t\tOptimizing scoring systems: Toward trust in machine learning for healthcare and criminal justice.\n\t\t\t\t\tInforms Journal on Applied Analytics, 48(5),\n\t\t\t\t\t449\u2013\n\t\t\t\t\t466.\n\t\t\t\t\thttps:\/\/doi.org\/10.1287\/inte.2018.0957","DOI":"10.1287\/inte.2018.0957"},{"key":"2021102717123080100_i1944-7558-126-6-477-Sannicandro1","doi-asserted-by":"crossref","unstructured":"Sannicandro,\n              T.,\n            \n            \n              Parish,\n              S. L.,\n            \n            \n              Fournier,\n              S.,\n            \n            \n              Mitra,\n              M.,\n             &\n\t\t\t\t\t\tPaiewonsky,M.\n          (2018).\n\t\t\t\t\tEmployment, income, and SSI effects of postsecondary education for people with intellectual disability.\n\t\t\t\t\tAmerican Journal on Intellectual and Developmental Disabilities, 123(5),\n\t\t\t\t\t412\u2013\n\t\t\t\t\t425.\n\t\t\t\t\thttp:\/\/doi.org\/10.1352\/1944-7558-123.5.412","DOI":"10.1352\/1944-7558-123.5.412"},{"key":"2021102717123080100_i1944-7558-126-6-477-Santiago1","doi-asserted-by":"crossref","unstructured":"Santiago,\n              A.M.\n             &\n\t\t\t\t\t\tSmith,R.\n          (2019).\n\t\t\t\t\tWhat can \u201cbig data\u201d methods offer human services research on organizations and communities?Human Service Organizations: Management, Leadership & Governance, 43(4),\n\t\t\t\t\t344\u2013\n\t\t\t\t\t356.\n\t\t\t\t\thttp:\/\/doi.org\/10.1080\/23303131.2019.1674756","DOI":"10.1080\/23303131.2019.1674756"},{"key":"2021102717123080100_i1944-7558-126-6-477-Shogren1","doi-asserted-by":"crossref","unstructured":"Shogren,\n              K. A.,\n             &\n\t\t\t\t\t\tShaw,L. A.\n          (2016).\n\t\t\t\t\tThe role of autonomy, self-realization, and psychological empowerment in predicting outcomes for youth with disabilities.\n\t\t\t\t\tRemedial and Special Education, 37(1),\n\t\t\t\t\t55\u2013\n\t\t\t\t\t62.\n\t\t\t\t\thttp:\/\/doi.org\/10.1177\/0741932515585003","DOI":"10.1177\/0741932515585003"},{"key":"2021102717123080100_i1944-7558-126-6-477-Simonsen1","doi-asserted-by":"crossref","unstructured":"Simonsen,\n              M. L.,\n             &\n\t\t\t\t\t\tNeubert,D. A.\n          (2013).\n\t\t\t\t\tTransitioning youth with intellectual and other developmental disabilities: Predicting community employment outcomes.\n\t\t\t\t\tCareer Development and Transition for Exceptional Individuals, 36(3),\n\t\t\t\t\t188\u2013\n\t\t\t\t\t198.\n\t\t\t\t\thttp:\/\/doi.org\/10.1177\/2165143412469399","DOI":"10.1177\/2165143412469399"},{"key":"2021102717123080100_i1944-7558-126-6-477-Strobl1","doi-asserted-by":"crossref","unstructured":"Strobl,\n              C.,\n            \n            \n              Malley,\n              J.,\n             &\n\t\t\t\t\t\tTutz,G.\n          (2009).\n\t\t\t\t\tAn introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests.\n\t\t\t\t\tPsychological Methods,\n\t\t\t\t\t14(4),\n\t\t\t\t\t323.\n\t\t\t\t\thttp:\/\/dx.doi.org\/10.1037\/a0016973","DOI":"10.1037\/a0016973"},{"key":"2021102717123080100_i1944-7558-126-6-477-Thabtah1","doi-asserted-by":"crossref","unstructured":"Thabtah,\n              F.,\n             &\n\t\t\t\t\t\tPeebles,D.\n          (2020).\n\t\t\t\t\tA new machine learning model based on induction of rules for autism detection.\n\t\t\t\t\tHealth Informatics Journal, 26(1),\n\t\t\t\t\t264\u2013\n\t\t\t\t\t286.\n\t\t\t\t\thttps:\/\/doi.org\/10.1177\/1460458218824711","DOI":"10.1177\/1460458218824711"},{"key":"2021102717123080100_i1944-7558-126-6-477-Therneau1","unstructured":"Therneau,\n              T.,\n             &\n\t\t\t\t\t\tAtkinson,B.\n          (2018\n          \n            ). rpart: Recursive partitioning and regression trees\n          \n          [R package version 4.1-13].\n          \n            https:\/\/CRAN.R-project.org\/package=rpart"},{"key":"2021102717123080100_i1944-7558-126-6-477-Trembath1","doi-asserted-by":"crossref","unstructured":"Trembath,\n              D.,\n            \n            \n              Balandin,\n              S.,\n            \n            \n              Stancliffe,\n              R. J.,\n             &\n\t\t\t\t\t\tTogher,L.\n          (2010).\n\t\t\t\t\tEmployment and volunteering for adults with intellectual disability.\n\t\t\t\t\tJournal of Policy and Practice in Intellectual Disabilities,\n\t\t\t\t\t7(4),\n\t\t\t\t\t235\u2013\n\t\t\t\t\t238.\n\t\t\t\t\thttps:\/\/doi.org\/10.1111\/j.1741-1130.2010.00271.x","DOI":"10.1111\/j.1741-1130.2010.00271.x"},{"key":"2021102717123080100_i1944-7558-126-6-477-Trewin1","unstructured":"Trewin,\n              S.\n            \n          \n          (2018).\n\t\t\t\t\tAI fairness for people with disabilities.\n\t\t\t\t\thttps:\/\/arxiv.org\/abs\/1811.10670"},{"key":"2021102717123080100_i1944-7558-126-6-477-NoAuthors2","unstructured":"U.S. Department of Labor. (n.d.).\n          \n            Employment First\n          .\n\t\t\t\t\thttps:\/\/www.dol.gov\/agencies\/odep\/initiatives\/employment-first"},{"key":"2021102717123080100_i1944-7558-126-6-477-Veale1","doi-asserted-by":"crossref","unstructured":"Veale,\n              M.,\n             &\n\t\t\t\t\t\tBinns,R.\n          (2017).\n\t\t\t\t\tFairer machine learning in the real world: Mitigating discrimination without collecting sensitive data.\n\t\t\t\t\tBig Data & Society, 4(2),\n\t\t\t\t\t1\u2013\n\t\t\t\t\t17.\n\t\t\t\t\thttps:\/\/doi.org\/10.1177\/2053951717743530","DOI":"10.1177\/2053951717743530"},{"key":"2021102717123080100_i1944-7558-126-6-477-Wagner1","doi-asserted-by":"crossref","unstructured":"Wagner,\n              J. B.,\n            \n            \n              Kim,\n              M.,\n             &\n\t\t\t\t\t\tTass\u00e9,M. J.\n          (2019).\n\t\t\t\t\tTechnology tools: Increasing our reach in national surveillance of intellectual and developmental disabilities.\n\t\t\t\t\tIntellectual and Developmental Disabilities, 57(5),\n\t\t\t\t\t463\u2013\n\t\t\t\t\t475.\n\t\t\t\t\thttps:\/\/doi.org\/10.1352\/1934-9556-57.5.463","DOI":"10.1352\/1934-9556-57.5.463"},{"key":"2021102717123080100_i1944-7558-126-6-477-Wicki1","doi-asserted-by":"crossref","unstructured":"Wicki,\n              M. T.,\n             &\n\t\t\t\t\t\tMeier,S.\n          (2016).\n\t\t\t\t\tSupporting volunteering activities by adults with intellectual disabilities: An explorative qualitative study.\n\t\t\t\t\tJournal of Policy and Practice in Intellectual Disabilities, 13(4),\n\t\t\t\t\t320\u2013\n\t\t\t\t\t326.\n\t\t\t\t\thttps:\/\/doi.org\/10.1111\/jppi.12207","DOI":"10.1111\/jppi.12207"},{"key":"2021102717123080100_i1944-7558-126-6-477-Winsor1","unstructured":"Winsor,\n              J.,\n            \n            \n              Timmons,\n              J.,\n            \n            \n              Butterworth,\n              J.,\n            \n            \n              Migliore,\n              A.,\n            \n            \n              Domin,\n              D.,\n            \n            \n              Zalewska,\n              A.,\n             &\n\t\t\t\t\t\tShepard,J.\n          (2019).\n\t\t\t\t\tStateData: The national report on employment services and outcomes.\n\t\t\t\t\tUniversity of Massachusetts Boston,\n\t\t\t\t\tInstitute for Community Inclusion."},{"key":"2021102717123080100_i1944-7558-126-6-477-Wright1","doi-asserted-by":"crossref","unstructured":"Wright,\n              M. N.,\n             &\n\t\t\t\t\t\tZiegler,A.\n          (2017).\n\t\t\t\t\tRanger: A fast implementation of random forests for high dimensional data in C++ and R.\n\t\t\t\t\tJournal of Statistical Software, 77(1),\n\t\t\t\t\t1\u2013\n\t\t\t\t\t17.\n\t\t\t\t\thttp:\/\/doi.org\/10.18637\/jss.v077.i01","DOI":"10.18637\/jss.v077.i01"},{"key":"2021102717123080100_i1944-7558-126-6-477-Ziegler1","doi-asserted-by":"crossref","unstructured":"Ziegler,\n              A.,\n             &\n\t\t\t\t\t\tK\u00f6nig,I. R.\n          (2014).\n\t\t\t\t\tMining data with random forests: Current options for real-world applications.\n\t\t\t\t\tWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery,\n\t\t\t\t\t4(1),\n\t\t\t\t\t55\u2013\n\t\t\t\t\t63.\n\t\t\t\t\thttp:\/\/doi.org\/10.1002\/widm.1114","DOI":"10.1002\/widm.1114"}],"container-title":["American Journal on Intellectual and Developmental Disabilities"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/meridian.allenpress.com\/ajidd\/article-pdf\/126\/6\/477\/2942761\/i1944-7558-126-6-477.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"http:\/\/meridian.allenpress.com\/ajidd\/article-pdf\/126\/6\/477\/2942761\/i1944-7558-126-6-477.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T16:34:56Z","timestamp":1768322096000},"score":1,"resource":{"primary":{"URL":"https:\/\/meridian.allenpress.com\/ajidd\/article\/126\/6\/477\/472451\/Using-Machine-Learning-to-Predict-Patterns-of"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10,26]]},"references-count":58,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2021,10,26]]},"published-print":{"date-parts":[[2021,11,1]]}},"URL":"https:\/\/doi.org\/10.1352\/1944-7558-126.6.477","relation":{},"ISSN":["1944-7558","1944-7515"],"issn-type":[{"value":"1944-7558","type":"electronic"},{"value":"1944-7515","type":"print"}],"subject":[],"published":{"date-parts":[[2021,10,26]]}}}