{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T23:29:13Z","timestamp":1790810953373,"version":"4.1.0"},"reference-count":24,"publisher":"Springer Science and Business Media LLC","issue":"1","content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Health Qual Life Outcomes"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                        <jats:title>Background<\/jats:title>\n                        <jats:p>The objective of this study was to demonstrate the use of the Heckman two-step method to assess and correct for bias due to missing health related quality of life (HRQL) surveys in a clinical study of acute coronary syndrome (ACS) patients.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Methods<\/jats:title>\n                        <jats:p>We analyzed data from 2,733 veterans with a confirmed diagnosis of acute coronary syndromes (ACS), including either acute myocardial infarction or unstable angina. HRQL outcomes were assessed by the Short-Form 36 (SF-36) health status survey which was mailed to all patients who were alive 7 months following ACS discharge. We created multivariable models of 7-month post-ACS physical and mental health status using data only from the 1,660 survey respondents. Then, using the Heckman method, we modeled survey non-response and incorporated this into our initial models to assess and correct for potential bias. We used logistic and ordinary least squares regression to estimate the multivariable selection models.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Results<\/jats:title>\n                        <jats:p>We found that our model of 7-month mental health status was biased due to survey non-response, while the model for physical health status was not. A history of alcohol or substance abuse was no longer significantly associated with mental health status after controlling for bias due to non-response. Furthermore, the magnitude of the parameter estimates for several of the other predictor variables in the MCS model changed after accounting for bias due to survey non-response.<\/jats:p>\n                     <\/jats:sec><jats:sec>\n                        <jats:title>Conclusion<\/jats:title>\n                        <jats:p>Recognition and correction of bias due to survey non-response changed the factors that we concluded were associated with HRQL seven months following hospital admission for ACS as well as the magnitude of some associations. We conclude that the Heckman two-step method may be a valuable tool in the assessment and correction of selection bias in clinical studies of HRQL.<\/jats:p>\n                     <\/jats:sec>","DOI":"10.1186\/1477-7525-2-49","type":"journal-article","created":{"date-parts":[[2004,9,22]],"date-time":"2004-09-22T06:23:20Z","timestamp":1095834200000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Assessing response bias from missing quality of life data: The Heckman method"],"prefix":"10.1186","volume":"2","author":[{"given":"Anne E","family":"Sales","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mary E","family":"Plomondon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David J","family":"Magid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John A","family":"Spertus","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John S","family":"Rumsfeld","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2004,9,16]]},"reference":[{"key":"130_CR1","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1002\/(SICI)1097-0258(19980315\/15)17:5\/7<667::AID-SIM813>3.0.CO;2-6","volume":"17","author":"D Fairclough","year":"1998","unstructured":"Fairclough D, Peterson H, Chang V: Why are missing quality of life data a problem in clinical trials of cancer therapy?\n                           Stat Med 1998, 17: 667\u2013677. 10.1002\/(SICI)1097-0258(19980315\/15)17:5\/7<667::AID-SIM813>3.3.CO;2-Y","journal-title":"Stat Med"},{"key":"130_CR2","doi-asserted-by":"crossref","DOI":"10.1201\/9781420035438","volume-title":"Design and Analysis of Quality of Life Studies in Clinical Trials","author":"D Fairclough","year":"2002","unstructured":"Fairclough D: Design and Analysis of Quality of Life Studies in Clinical Trials. Boca Raton, FL: Chapman and Hall\/CRC Press 2002."},{"key":"130_CR3","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1002\/(SICI)1097-0258(19980315\/15)17:5\/7<781::AID-SIM821>3.0.CO;2-O","volume":"17","author":"D Fairclough","year":"1998","unstructured":"Fairclough D, Peterson H, Cella D, Bonomi P: Comparison of several model-based methods for analysing incomplete quality of life data in cancer clinical trials.\n                           Stat Med 1998, 17: 781\u2013796. 10.1002\/(SICI)1097-0258(19980315\/15)17:5\/7<781::AID-SIM821>3.3.CO;2-F","journal-title":"Stat Med"},{"key":"130_CR4","doi-asserted-by":"publisher","DOI":"10.1002\/9781119013563","volume-title":"Statistical analysis with missing data","author":"R Little","year":"2002","unstructured":"Little R, Rubin D: Statistical analysis with missing data. 2002."},{"key":"130_CR5","first-page":"65","volume":"4","author":"J Heckman","year":"1981","unstructured":"Heckman J, MaCurdy T: New methods for estimating labor supply functions: A survey.\n                           Research in labor economics 1981, 4: 65\u2013102.","journal-title":"Research in labor economics"},{"key":"130_CR6","first-page":"1918","volume-title":"In: Handbook of Econometrics","author":"J Heckman","year":"1986","unstructured":"Heckman J, MaCurdy T: Labor econometrics.\n                           In: Handbook of Econometrics\n                           (Edited by: Griliches ZIM). 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