Published in Statistics in medicine
Longitudinal targeted maximum likelihood estimation (LTMLE) has very rarely been used to estimate dynamic treatment effects in the context of time-dependent confounding affected by prior treatment when faced with long follow-up times, multiple time-varying confounders, and complex associational relationships simultaneously. Reasons for this include...
Published in Statistics in medicine
A stepped wedge cluster randomized trial is a type of longitudinal cluster design that sequentially switches clusters to intervention over time until all clusters are treated. While the traditional posttest-only parallel design requires adjustment for a single intraclass correlation coefficient, the stepped wedge design allows multiple outcome meas...
Published in Statistics in medicine
While the gold standard for clinical trials is to blind all parties-participants, researchers, and evaluators-to treatment assignment, this is not always a possibility. When some or all of the above individuals know the treatment assignment, this leaves the study open to the introduction of postrandomization biases. In the Strategies to Reduce Inju...
Published in Statistics in medicine
Cumulative sum (CUSUM) plots and methods have wide-ranging applications in healthcare. We review and discuss some issues related to the analysis of surgical learning curve (LC) data with a focus on three types of CUSUM statistical approaches. The underlying assumptions, benefits, and weaknesses of each approach are given. Our primary conclusion is ...
Published in Statistics in medicine
Dynamic treatment regimes (DTRs) adaptively prescribe treatments based on patients' intermediate responses and evolving health status over multiple treatment stages. Data from sequential multiple assignment randomization trials (SMARTs) are recommended to be used for learning DTRs. However, due to re-randomization of the same patients over multiple...
Published in Statistics in medicine
Estimable functions play an important role in learning about certain aspects of the impact of ages, periods, and cohorts in age-period-cohort multiple classification (APCMC) models. The advantage of these estimates is that they are unbiased estimates of, for example, the deviations of age, period, and cohort effects from their linear trends, or cha...
Published in Statistics in medicine
In this article, we review and evaluate a number of methods used in the design and analysis of small three-arm parallel cluster randomized trials. We conduct a simulation-based study to evaluate restricted randomization methods including covariate-constrained randomization and a novel method for matched-group cluster randomization. We also evaluate...
Published in Statistics in medicine
Maximum approximate Bernstein likelihood estimates of the baseline density function and the regression coefficients in the proportional hazard regression models based on interval-censored event time data result in smooth estimates of the survival functions which enjoys an almost n1/2 -rate of convergence faster than the n1/3 -rate for the existing ...
Published in Statistics in medicine
Recurrent events arise frequently in biomedical research, where the subject may experience the same type of events more than once. The Andersen-Gill (AG) model has become increasingly popular in the analysis of recurrent events particularly when the event rate is not constant over time. We propose a procedure for calculating the power and sample si...
Published in Statistics in medicine
Although all clinical trials are designed and monitored using more than one endpoint, methods are needed to assure that decision criteria are chosen to reflect the clinically relevant tradeoffs that assure the trial's scientific integrity. This article presents a framework for the design and monitoring clinical trials in a bivariate outcome space. ...
