{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Si Y"],"funding":["NIDA NIH HHS"],"pagination":["e1916"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9464329"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["31(3)"],"pubmed_abstract":["<h4>Objectives</h4>Longitudinal survey data allow for the estimation of developmental trajectories of substance use from adolescence to young adulthood, but these estimates may be subject to attrition bias. Moreover, there is a lack of consensus regarding the most effective statistical methodology to adjust for sample selection and attrition bias when estimating these trajectories. Our objective is to develop specific recommendations regarding adjustment approaches for attrition in longitudinal surveys in practice.<h4>Methods</h4>Analyzing data from the national U.S. Monitoring the Future panel study following four cohorts of individuals from modal ages 18 to 29/30, we systematically compare alternative approaches to analyzing longitudinal data with a wide range of substance use outcomes, "],"journal":["International journal of methods in psychiatric research"],"pubmed_title":["An empirical evaluation of alternative approaches to adjusting for attrition when analyzing longitudinal survey data on young adults' substance use trajectories."],"pmcid":["PMC9464329"],"funding_grant_id":["R01 DA001411","R01 DA016575","R01 DA031160"],"pubmed_authors":["West BT","Terry-McElrath YM","Patrick ME","Si Y","Schulenberg JE","Kloska DD","Veliz P","McCabe SE"],"additional_accession":[]},"is_claimable":false,"name":"An empirical evaluation of alternative approaches to adjusting for attrition when analyzing longitudinal survey data on young adults' substance use trajectories.","description":"<h4>Objectives</h4>Longitudinal survey data allow for the estimation of developmental trajectories of substance use from adolescence to young adulthood, but these estimates may be subject to attrition bias. Moreover, there is a lack of consensus regarding the most effective statistical methodology to adjust for sample selection and attrition bias when estimating these trajectories. Our objective is to develop specific recommendations regarding adjustment approaches for attrition in longitudinal surveys in practice.<h4>Methods</h4>Analyzing data from the national U.S. Monitoring the Future panel study following four cohorts of individuals from modal ages 18 to 29/30, we systematically compare alternative approaches to analyzing longitudinal data with a wide range of substance use outcomes, ","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Sep","modification":"2025-04-22T03:32:09.474Z","creation":"2024-10-14T17:46:47.328Z"},"accession":"S-EPMC9464329","cross_references":{"pubmed":["35582963"],"doi":["10.1002/mpr.1916"]}}