Substantially inflated type I error rates if propensity score method is not fixed in advance

Naive application of permutation testing leads to inflated type I error rates.

Failure to account for family structure within populations or in complex mating designs via uninformed applications of permutation testing will lead to inflated type I error rates. Careful consideration of the design factors is essential since some situations allow several valid permutation strategies, and the choice that maximizes statistical power will not always be intuitive.

Remarks on the method of propensity score

Dear Editor, I read with great interest Donald Rubin’s paper ‘The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials’ (2007; 26(1):20–36) [1], as well as the Letter To The Editor by Ian Shrier (2008; 27(14):2740–2741) [2], and Author Reply by Don Rubin (2008; 27(14):2741–2742) [3]. Shrier’s Letter posed an important question th...

Remarks on the method of propensity score.

Dear Editor, I read with great interest Donald Rubin’s paper ‘The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials’ (2007; 26(1):20–36) [1], as well as the Letter To The Editor by Ian Shrier (2008; 27(14):2740–2741) [2], and Author Reply by Don Rubin (2008; 27(14):2741–2742) [3]. Shrier’s Letter posed an important question th...

A Randomization Method to Control the Type I Error Rates in Best Subset Regression

Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method

BACKGROUND Diabetes costs represent a large burden to both patients and the health care system. However, few studies that examine the economic consequences of diabetes have distinguished between the two major forms, type 1 and type 2 diabetes, despite differences in underlying pathologies. Combining the two diseases implies that there is no difference between the costs of type 1 and type 2 diab...