Issue Information
No abstract is available for this article. (Source: Statistics in Medicine)
Source: Statistics in Medicine - November 13, 2018 Category: Statistics Tags: ISSUE INFORMATION Source Type: research
A note on a naive regression ‐based test on the validity of an instrumental variable
Statistics in Medicine, Volume 37, Issue 28, Page 4330-4333, 10 December 2018. (Source: Statistics in Medicine)
Source: Statistics in Medicine - November 13, 2018 Category: Statistics Authors: Fei Wan Tags: LETTER TO THE EDITOR Source Type: research
ComPAS: A Bayesian drug combination platform trial design with adaptive shrinkage
Combining different treatment regimens provides an effective approach to induce a synergistic treatment effect and overcome resistance to monotherapy. The challenge is that, given the large number of existing monotherapies, the number of possible combinations is huge and new potentially more efficacious compounds may become available any time during drug development. To address this challenge, we propose a flexible Bayesian drug combination platform design with adaptive shrinkage (ComPAS), which allows for dropping futile combinations, graduating effective combinations, and adding new combinations during the course of the ...
Source: Statistics in Medicine - November 12, 2018 Category: Statistics Authors: Rui Tang,
Jing Shen,
Ying Yuan Tags: RESEARCH ARTICLE Source Type: research
A correlated Bayesian rank likelihood approach to multiple ROC curves for endometriosis
In analysis of diagnostic data with multiple tests, it is often the case that these tests are correlated. Modeling the correlation explicitly not only produces valid inference results but also enables borrowing of information. Motivated by the Physician Reliability Study (PRS) that investigated the diagnostic performance of physicians in diagnosing endometriosis, we construct a correlated modeling framework to estimate ROC curves and the associated area under the curves. This correlated approach is quite appealing for the PRS data set that suffers from the problem of small sample sizes, as it enables information borrowing ...
Source: Statistics in Medicine - November 12, 2018 Category: Statistics Authors: Zhen Chen,
Beom Seuk Hwang,
Sungduk Kim Tags: RESEARCH ARTICLE Source Type: research
Flexible longitudinal linear mixed models for multiple censored responses data
In biomedical studies and clinical trials, repeated measures are often subject to some upper and/or lower limits of detection. Hence, the responses are either left or right censored. A complication arises when more than one series of responses is repeatedly collected on each subject at irregular intervals over a period of time and the data exhibit tails heavier than the normal distribution. The multivariate censored linear mixed effect (MLMEC) model is a frequently used tool for a joint analysis of more than one series of longitudinal data. In this context, we develop a robust generalization of the MLMEC based on the scale...
Source: Statistics in Medicine - November 12, 2018 Category: Statistics Authors: Victor H. Lachos,
Larissa A. Matos,
Luis M. Castro,
Ming ‐Hui Chen Tags: RESEARCH ARTICLE Source Type: research
Identification of cancer omics commonality and difference via community fusion
The analysis of cancer omics data is a “classic” problem; however, it still remains challenging. Advancing from early studies that are mostly focused on a single type of cancer, some recent studies have analyzed data on multiple “related” cancer types/subtypes, examined their commonality and difference, and led to insightful find ings. In this article, we consider the analysis of multiple omics datasets, with each dataset on one type/subtype of “related” cancers. A Community Fusion (CoFu) approach is developed, which conducts marker selection and model building using a novel penalization technique, informativel...
Source: Statistics in Medicine - November 12, 2018 Category: Statistics Authors: Yifan Sun,
Yu Jiang,
Yang Li,
Shuangge Ma Tags: RESEARCH ARTICLE Source Type: research
Mediation analysis in a case ‐control study when the mediator is a censored variable
In this study, we propose an approach (denoted as MAC‐CC) to analyze the mediation model with a censored mediator given data from a case‐control study , based on the semiparametric accelerated failure time model along with a pseudo‐likelihood function. We adapted the measures for assessing the indirect and direct effects using counterfactual definitions. We conducted simulation studies to investigate the performance of MAC‐CC and compared it t o those of the naïve approach and the complete‐case approach. MAC‐CC accurately estimates the coefficients of different paths, the indirect effects, and the proportions ...
Source: Statistics in Medicine - November 12, 2018 Category: Statistics Authors: Jian Wang,
Jing Ning,
Sanjay Shete Tags: RESEARCH ARTICLE Source Type: research
Statistical modeling and prediction of clinical trial recruitment
We describe a novel, simulation‐based prediction method that is founded on a realistic model for the underlying processes of recruitment. The model reflec ts key features of enrollment such as the staggered initiation of new centers, heterogeneity in enrollment capacity, and declining accrual within centers. The model's first stage assumes that centers join the trial (ie, initiate accrual) according to an inhomogeneous Poisson process in discrete time . The second part assumes that each center's enrollment pattern reflects an early plateau followed by a slow decline, with a burst at the end of the trial following the ann...
Source: Statistics in Medicine - November 8, 2018 Category: Statistics Authors: Yu Lan,
Gong Tang,
Daniel F. Heitjan Tags: RESEARCH ARTICLE Source Type: research
Practical issues in using generalized estimating equations for inference on transitions in longitudinal data: What is being estimated?
Generalized estimating equations (GEEs) are commonly used to estimate transition models. When the Markov assumption does not hold but first ‐order transition probabilities are still of interest, the transition inference is sensitive to the choice of working correlation. In this paper, we consider a random process transition model as the true underlying data generating mechanism, which characterizes subject heterogeneity and complex de pendence structure of the outcome process in a very flexible way. We formally define two types of transition probabilities at the population level: “naive transition probabilities” that...
Source: Statistics in Medicine - November 8, 2018 Category: Statistics Authors: Joe Bible,
Paul S. Albert,
Bruce G. Simons ‐Morton,
Danping Liu Tags: FEATURED ARTICLE Source Type: research
Penalized variable selection for accelerated failure time models with random effects
Accelerated failure time (AFT) models allowing for random effects are linear mixed models under the log ‐transformation of survival time with censoring and describe dependence in correlated survival data. It is well known that the AFT models are useful alternatives to frailty models. To the best of our knowledge, however, there is no literature on variable selection methods for such AFT models. In t his paper, we propose a simple but unified variable‐selection procedure of fixed effects in the AFT random‐effect models using penalized h‐likelihood (HL). We consider four penalty functions (ie, least absolute shrinkag...
Source: Statistics in Medicine - November 8, 2018 Category: Statistics Authors: Eunyoung Park,
Il Do Ha Tags: RESEARCH ARTICLE Source Type: research
Practical issues in using generalized estimating equations for inference on transitions in longitudinal data: What is being estimated?
Generalized estimating equations (GEEs) are commonly used to estimate transition models. When the Markov assumption does not hold but first ‐order transition probabilities are still of interest, the transition inference is sensitive to the choice of working correlation. In this paper, we consider a random process transition model as the true underlying data generating mechanism, which characterizes subject heterogeneity and complex de pendence structure of the outcome process in a very flexible way. We formally define two types of transition probabilities at the population level: “naive transition probabilities” that...
Source: Statistics in Medicine - November 8, 2018 Category: Statistics Authors: Joe Bible,
Paul S. Albert,
Bruce G. Simons ‐Morton,
Danping Liu Tags: FEATURED ARTICLE Source Type: research
Penalized variable selection for accelerated failure time models with random effects
Accelerated failure time (AFT) models allowing for random effects are linear mixed models under the log ‐transformation of survival time with censoring and describe dependence in correlated survival data. It is well known that the AFT models are useful alternatives to frailty models. To the best of our knowledge, however, there is no literature on variable selection methods for such AFT models. In t his paper, we propose a simple but unified variable‐selection procedure of fixed effects in the AFT random‐effect models using penalized h‐likelihood (HL). We consider four penalty functions (ie, least absolute shrinkag...
Source: Statistics in Medicine - November 8, 2018 Category: Statistics Authors: Eunyoung Park,
Il Do Ha Tags: RESEARCH ARTICLE Source Type: research
Statistical modeling and prediction of clinical trial recruitment
We describe a novel, simulation‐based prediction method that is founded on a realistic model for the underlying processes of recruitment. The model reflec ts key features of enrollment such as the staggered initiation of new centers, heterogeneity in enrollment capacity, and declining accrual within centers. The model's first stage assumes that centers join the trial (ie, initiate accrual) according to an inhomogeneous Poisson process in discrete time . The second part assumes that each center's enrollment pattern reflects an early plateau followed by a slow decline, with a burst at the end of the trial following the ann...
Source: Statistics in Medicine - November 8, 2018 Category: Statistics Authors: Yu Lan,
Gong Tang,
Daniel F. Heitjan Tags: RESEARCH ARTICLE Source Type: research
Admissible multiarm stepped ‐wedge cluster randomized trial designs
Numerous publications have now addressed the principles of designing, analyzing, and reporting the results of stepped ‐wedge cluster randomized trials. In contrast, there is little research available pertaining to the design and analysis of multiarm stepped‐wedge cluster randomized trials, utilized to evaluate the effectiveness of multiple experimental interventions. In this paper, we address this by explaining how the required sample size in these multiarm trials can be ascertained when data are to be analyzed using a linear mixed model. We then go on to describe how the design of such trials can be optimized to balan...
Source: Statistics in Medicine - November 6, 2018 Category: Statistics Authors: Michael J. Grayling,
Adrian P. Mander,
James M. S. Wason Tags: RESEARCH ARTICLE Source Type: research
