title: Comment: Analyzing propensity score matched count data.
abstract: We offer an explanation to the simulation result of Austin (2009) regarding rate ratios, and argue that unmatched analysis of propensity score matched count data results in conservative statistical inferences on the rate ratios.
authors.affiliation: Department of Quantitative Health Sciences, Cleveland Clinic, 9500 Euclid Ave. JJN3, Cleveland, Ohio, USA. lil2@ccf.org
authors.forename: Liang
authors.initials: L
authors.lastname: Li
mesh_terms: D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D009010:Monte Carlo Method; D057216:Propensity Score; D016016:Proportional Hazards Models; D012107:Research Design; D015983:Selection Bias