|Journal||Circulation: Cardiovascular Quality Outcomes|
|Authors||Normand, Sharon-Lise T.|
|Link to Publication|
This issue contains 2 articles in our planned Statistical Primer on Methods or Interpretation Series. The goals of our series are to (1) familiarize cardiovascular outcomes researchers with design and analytic problems encountered in outcomes research, (2) point to potential solutions, and (3) introduce modern analytic approaches. The series’ inaugural article discussed approaches for handling missing data—approaches that have existed for several decades but have not been fully embraced by outcomes researchers. The second article focused on the “landmark analysis, an analytic approach in which patients having treatment-censoring events before a “landmark” time are excluded from analysis. In this issue, Teixeira-Pinto and Mauri address the problem of multiple outcomes, and Kwok and Lewis discuss the use of Bayesian hierarchical models.