Sample size estimation for case ‐crossover studies
We present mathematical derivations to exp lain where some currently used methods fail and propose two new sample size estimation methods that provide a more accurate estimate of the true required sample size. (Source: Statistics in Medicine)
Source: Statistics in Medicine - November 5, 2018 Category: Statistics Authors: Sai Dharmarajan,
Joo ‐Yeon Lee,
Rima Izem Tags: RESEARCH ARTICLE Source Type: research
Sample size estimation for case ‐crossover studies
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - November 5, 2018 Category: Statistics Authors: Sai Dharmarajan,
Joo ‐Yeon Lee,
Rima Izem Source Type: research
Correction to “Latent class instrumental variables: A clinical and biostatistical perspective”
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 30, 2018 Category: Statistics Authors: Stuart G. Baker,
Barnett S. Kramer,
Karen S. Lindeman Tags: CORRECTION Source Type: research
Shared random parameter models: A legacy of the biostatistics program at the National Heart Lung and Blood Institute
This article will review the early contributions of the NHLBI biostatisticians on SRPMs for analyzing longitudinal data with dropout and demonstrate how these ideas have, more recently, been applied in these other areas of biostatistics. Rather than focus on technical details or specific analyses, this article presents a conceptual framework for SRPMs within a historical context. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 30, 2018 Category: Statistics Authors: Paul S. Albert Tags: SPECIAL ISSUE PAPER Source Type: research
Correction to “Latent class instrumental variables: A clinical and biostatistical perspective”
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 30, 2018 Category: Statistics Authors: Stuart G. Baker,
Barnett S. Kramer,
Karen S. Lindeman Source Type: research
Shared random parameter models: A legacy of the biostatistics program at the National Heart Lung and Blood Institute
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 30, 2018 Category: Statistics Authors: Paul S. Albert Source Type: research
A Bayesian regularized mediation analysis with multiple exposures
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 30, 2018 Category: Statistics Authors: Yu ‐Bo Wang,
Zhen Chen,
Jill M. Goldstein,
Germaine M. Buck Louis,
Stephen E. Gilman Source Type: research
A Bayesian regularized mediation analysis with multiple exposures
Mediation analysis assesses the effect of study exposures on an outcome both through and around specific mediators. While mediation analysis involving multiple mediators has been addressed in recent literature, the case of multiple exposures has received little attention. With the presence of multiple exposures, we consider regularizations that allow simultaneous effect selection and estimation while stabilizing model fit and accounting for model selection uncertainty. In the framework of linear structural ‐equation models, we analytically show that a two‐stage approach regularizing regression coefficients does not gua...
Source: Statistics in Medicine - October 29, 2018 Category: Statistics Authors: Yu ‐Bo Wang,
Zhen Chen,
Jill M. Goldstein,
Germaine M. Buck Louis,
Stephen E. Gilman Tags: RESEARCH ARTICLE Source Type: research
Issue Information
No abstract is available for this article. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 28, 2018 Category: Statistics Tags: ISSUE INFORMATION Source Type: research
State ‐level estimation of diabetes and prediabetes prevalence: Combining national and local survey data and clinical data
This article illustrates how to adjust and combine multiple data set s, namely, national surveys, state‐level surveys, claims data, and electronic health record data, to improve estimates of diabetes and prediabetes prevalence, along with the estimates of the method's accuracy. We demonstrate and validate the method using data from three jurisdictions (Alabama, Cal ifornia, and New York City). This method can be applied more generally to other areas and other data sources. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 28, 2018 Category: Statistics Authors: David A. Marker,
Russ Mardon,
Frank Jenkins,
Joanne Campione,
Jennifer Nooney,
Jane Li,
Sharon Saydeh,
Xuanping Zhang,
Sundar Shrestha,
Deborah Rolka Tags: RESEARCH ARTICLE Source Type: research
Sample size calculation for studies with grouped survival data
Grouped survival data arise often in studies where the disease status is assessed at regular visits to clinic. The time to the event of interest can only be determined to be between two adjacent visits or is right censored at one visit. In data analysis, replacing the survival time with the endpoint or midpoint of the grouping interval leads to biased estimators of the effect size in group comparisons. Prentice and Gloeckler developed a maximum likelihood estimator for the proportional hazards model with grouped survival data and the method has been widely applied. Previous work on sample size calculation for designing stu...
Source: Statistics in Medicine - October 28, 2018 Category: Statistics Authors: Zhiguo Li,
Xiaofei Wang,
Yuan Wu,
Kouros Owzar Tags: RESEARCH ARTICLE Source Type: research
Assessing the influence of treatment nonadherence on noninferiority trials using the tipping point approach
In noninferiority (NI) trials, an ongoing methodological challenge is how to handle in the analysis the subjects who are nonadherent to their assigned treatment. Some investigators perform the intent ‐to‐treat (ITT) as the primary analysis and the per‐protocol (PP) analysis as sensitivity analysis, whereas others do the reverse since ITT results may be anticonservative in the NI setting. But even when there is agreement between the ITT and PP approaches, NI of the experimental therapy to t he comparator is not guaranteed. We propose that a tipping point method be used to further assess the impact of nonadherence on t...
Source: Statistics in Medicine - October 28, 2018 Category: Statistics Authors: Mimi Kim,
Cuiling Wang,
Xiaonan Xue Tags: RESEARCH ARTICLE Source Type: research
Assessing the influence of treatment nonadherence on noninferiority trials using the tipping point approach
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 28, 2018 Category: Statistics Authors: Mimi Kim,
Cuiling Wang,
Xiaonan Xue Source Type: research
Issue Information
Statistics in Medicine,Volume 37, Issue 27, 30 November 2018. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 28, 2018 Category: Statistics Source Type: research
Modified power prior with multiple historical trials for binary endpoints
Including historical data may increase the power of the analysis of a current clinical trial and reduce the sample size of the study. Recently, several Bayesian methods for incorporating historical data have been proposed. One of the methods consists of specifying a so ‐called power prior whereby the historical likelihood is downweighted with a weight parameter. When the weight parameter is also estimated from the data, the modified power prior (MPP) is needed. This method has been used primarily when a single historical trial is available. We have adapted the M PP for incorporating multiple historical control arms into ...
Source: Statistics in Medicine - October 25, 2018 Category: Statistics Authors: Akalu Banbeta,
Joost Rosmalen,
David Dejardin,
Emmanuel Lesaffre Tags: RESEARCH ARTICLE Source Type: research
