Reducing Bias in a Propensity Score Matched-Pair Sample Using Greedy Matching Techniques

By Lori S. Parsons. 2001

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Propensity Score Analysis: Recent Debate and Discussion (2020, methodology): “For the three methods considered by King and Nielsen (2019), researchers often must choose between inexact matching and incomplete matching (Guo & Fraser, 2015; Parsons, 2001).”
Evaluating the effects of farm programmes: results from propensity score matching (2009, methodology): “A Greedy algorithm employing calliper pair matching without replacement is applied (Parson, 2001).”
Perioperative beta-blocker therapy and mortality after major noncardiac surgery. (2005, unknown): “002 Nonteaching 91,323 (76) 166,140 (77) Teaching 28,309 (24) 50,150 (23) No.”
Thoracoscopic lobectomy is associated with lower morbidity than open lobectomy: a propensity-matched analysis from the STS database. (2010, methodology): “Patients were then matched using a Greedy 5 to 1 digit matching algorithm.(17) Missing values in Zubrod score, American Society of Anesthesiologists Risk Scale, and clinical status were kept as separate levels.”
Propensity score matching strategies for evaluating substance abuse services for child welfare clients (2006, methodology): “In practice, Rosenbaum and Rubin (1985) suggest using the logit of the estimated propensity score to match (i.”