2003
DOI: 10.1002/hec.710
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An exploratory instrumental variable analysis of the outcomes of localized breast cancer treatments in a medicare population

Abstract: This study is motivated by the potential problem of using observational data to draw inferences about treatment outcomes when experimental data are not available. We compare two statistical approaches, ordinary least-squares (OLS) and instrumental variables (IV) regression analysis, to estimate the outcomes (three-year post-treatment survival) of three treatments for early stage breast cancer in elderly women: mastectomy (MST), breast conserving surgery with radiation therapy (BCSRT), and breast conserving sur… Show more

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Cited by 44 publications
(45 citation statements)
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“…38–40 However, finding an appropriate instrumental variable is often difficult, the estimates may vary depending on the instrument chosen, 41 and the estimates often lack precision. 42,43 Hence, further development of the method is warranted.…”
Section: Discussionmentioning
confidence: 99%
“…38–40 However, finding an appropriate instrumental variable is often difficult, the estimates may vary depending on the instrument chosen, 41 and the estimates often lack precision. 42,43 Hence, further development of the method is warranted.…”
Section: Discussionmentioning
confidence: 99%
“…7 One of the earliest applications of IV in the medical field is probably the research of Permutt and Hebel, 8 who estimated the effect of smoking of pregnant women on their child's birth weight, using an encouragement to stop smoking as the instrumental variable. More recent examples can be found in Beck et al, 9 Brooks et al, 10 Earle et al, 11 Hadley et al, 12 Leigh and Schembri, 13 McClellan, 14 and McIntosh. 15 However, it has been argued that the application of this method is limited because of its strong assumptions, making it difficult in practice to find a suitable instrumental variable.…”
mentioning
confidence: 97%
“…9,10 Its use has been increasing over the past 15 years in health services and medical care research. 16,[21][22][23][24][25] Because quasi-experimental and observational research designs are likely to dominate research on the effects of palliative care on patient, family and health system outcomes, palliative care researchers using these nonexperimental designs can strengthen the scientific rigor of their findings by using instrumental variable methods when possible. Palliative care patients and their families are challenging to study but their care is in desperate need of an improved evidence base to assure that the highest quality of care can be provided.…”
Section: Resultsmentioning
confidence: 99%