Copula selection models for non ‐Gaussian outcomes that are missing not at random
Missing not at random (MNAR) data pose key challenges for statistical inference because the substantive model of interest is typically not identifiable without imposing further (eg, distributional) assumptions. Selection models have been routinely used for handling MNAR by jointly modeling the outcome and selection variables and typically assuming that these follow a bivariate normal distribution. Recent studies have advocated parametric selection approaches, for example, estimated by multiple imputation and maximum likelihood, that are more robust to departures from the normality assumption compared with those assuming th...
Source: Statistics in Medicine - October 8, 2018 Category: Statistics Authors: Manuel Gomes,
Rosalba Radice,
Jose Camarena Brenes,
Giampiero Marra Tags: RESEARCH ARTICLE Source Type: research
What makes a biostatistician?
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 8, 2018 Category: Statistics Authors: Antonia Zapf,
Marianne Huebner,
Geraldine Rauch,
Meinhard Kieser Source Type: research
What makes a biostatistician?
Biostatisticians play an important role in medical research. They are co ‐responsible for an appropriate and efficient study design, they are involved in monitoring the study conduct, they plan and perform the data analysis, and they are involved in interpreting and publishing the results. However, how are the biostatisticians prepared for their tasks and responsibilit ies? Graduate programs in biostatistics are being offered, but some practicing biostatisticians completed their studies in a mathematical or epidemiological program, or obtained their degree in subject‐specific fields (such as medicine or biology). There...
Source: Statistics in Medicine - October 7, 2018 Category: Statistics Authors: Antonia Zapf,
Marianne Huebner,
Geraldine Rauch,
Meinhard Kieser Tags: TUTORIAL IN BIOSTATISTICS Source Type: research
Issue Information
Statistics in Medicine,Volume 37, Issue 24, 30 October 2018. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 5, 2018 Category: Statistics Source Type: research
Meta ‐analysis of non‐linear exposure‐outcome relationships using individual participant data: A comparison of two methods
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 4, 2018 Category: Statistics Authors: Ian R. White,
Stephen Kaptoge,
Patrick Royston,
Willi Sauerbrei,
The Emerging Risk Factors Collaboration Source Type: research
Design and monitoring of survival trials in complex scenarios
This paper proposes an approach to design and monitor survival trials accounting for complex scenarios such as delayed treatment effect, treatment dilution, and treatment crossover. These scenarios often lead to non ‐proportional hazards, making study design and monitoring more difficult. We demonstrate that, with event times following piecewise exponential distributions, the log‐rank statistic as well as its variance‐covariance structure can be easily computed, which greatly simplifies study design and m onitoring. As the number of pieces in the exponential distributions can be arbitrary, this approach can handle a ...
Source: Statistics in Medicine - October 3, 2018 Category: Statistics Authors: Xiaodong Luo,
Xuezhou Mao,
Xun Chen,
Junshan Qiu,
Steven Bai,
Hui Quan Tags: RESEARCH ARTICLE Source Type: research
Meta ‐analysis of non‐linear exposure‐outcome relationships using individual participant data: A comparison of two methods
Non ‐linear exposure‐outcome relationships such as between body mass index (BMI) and mortality are common. They are best explored as continuous functions using individual participant data from multiple studies. We explore two two‐stage methods for meta‐analysis of such relationships, where the c onfounder‐adjusted relationship is first estimated in a non‐linear regression model in each study, then combined across studies. The “metacurve” approach combines the estimated curves using multiple meta‐analyses of the relative effect between a given exposure level and a reference level. The “mvmeta” approach...
Source: Statistics in Medicine - October 3, 2018 Category: Statistics Authors: Ian R. White,
Stephen Kaptoge,
Patrick Royston,
Willi Sauerbrei,
The Emerging Risk Factors Collaboration Tags: RESEARCH ARTICLE Source Type: research
Design and monitoring of survival trials in complex scenarios
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 3, 2018 Category: Statistics Authors: Xiaodong Luo,
Xuezhou Mao,
Xun Chen,
Junshan Qiu,
Steven Bai,
Hui Quan Source Type: research
Matched or unmatched analyses with propensity ‐score–matched data?
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - October 2, 2018 Category: Statistics Authors: Fei Wan Source Type: research
Matched or unmatched analyses with propensity ‐score–matched data?
Propensity ‐score matching has been used widely in observational studies to balance confounders across treatment groups. However, whether matched‐pairs analyses should be used as a primary approach is still in debate. We compared the statistical power and type 1 error rate for four commonly used methods of analyzing propensity‐score–matched samples with continuous outcomes: (1) an unadjusted mixed‐effects model, (2) an unadjusted generalized estimating method, (3) simple linear regression, and (4) multiple linear regression. Multiple linear regression had the highest statistical power among the four competing met...
Source: Statistics in Medicine - October 1, 2018 Category: Statistics Authors: Fei Wan Tags: RESEARCH ARTICLE Source Type: research
Assessment of effect size and power for survival analysis through a binary surrogate endpoint in clinical trials
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - September 28, 2018 Category: Statistics Authors: Judah Abberbock,
Stewart Anderson,
Priya Rastogi,
Gong Tang Source Type: research
Can a multiple ascending dose study serve as an informative proof ‐of‐concept study?
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - September 28, 2018 Category: Statistics Authors: Yongming Qu Source Type: research
Judgment post ‐stratification in finite mixture modeling: An example in estimating the prevalence of osteoporosis
Statistics in Medicine, EarlyView. (Source: Statistics in Medicine)
Source: Statistics in Medicine - September 28, 2018 Category: Statistics Authors: Sedigheh Omidvar,
Mohammad Jafari Jozani,
Nader Nematollahi Source Type: research
Assessment of effect size and power for survival analysis through a binary surrogate endpoint in clinical trials
A strategy for early ‐stage breast cancer trials in recent years consists of a neoadjuvant trial with pathological complete response (pCR) at time of surgery as the efficacy endpoint, followed by the collection of long‐term data to show efficacy in survival. To calculate an appropriate sample size to detect a surviv al difference based upon pCR data, it is necessary to relate the effect size in pCR with the effect size in survival. Here, we propose an exponential mixture model for survival time with parameters for the neoadjuvant pCR rates and an estimated benefit of achieving pCR to determine the treatment eff ect siz...
Source: Statistics in Medicine - September 27, 2018 Category: Statistics Authors: Judah Abberbock,
Stewart Anderson,
Priya Rastogi,
Gong Tang Tags: RESEARCH ARTICLE Source Type: research
Can a multiple ascending dose study serve as an informative proof ‐of‐concept study?
Drug development is a long, complex, and costly process. The majority of the cost arises from Phase 2 and Phase 3 clinical development. Reducing Phase 2 and Phase 3 failure rates would greatly reduce the average drug development cost. Obtaining more informative data on a candidate drug's efficacy and safety prior to moving to Phase 2 will improve Phase 2 success and, hence, reduce the overall development cost. While, typically, multiple ascending dose (MAD) study focuses on safety, this article proposes a model ‐based MAD design that not only can provide the desired safety information but also can provide informative eff...
Source: Statistics in Medicine - September 27, 2018 Category: Statistics Authors: Yongming Qu Tags: RESEARCH ARTICLE Source Type: research
