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Statistics in Medicine

Xiaoqi Li, Yong Chen, Ruosha Li
We consider recurrent events of the same type that occur during alternating restraint and non-restraint time periods. This research is motivated by a study on juvenile recidivism, where the probationers were followed for re-offenses during alternating placement periods and free-time periods. During the placement periods, the probationers were under a restricted environment with direct supervision of the probation officers. During the free-time periods, the probationers were released to home and not under direct supervision...
October 18, 2016: Statistics in Medicine
Sean Yiu, Brian Tom
Multistate processes provide a convenient framework when interest lies in characterising the transition intensities between a set of defined states. If, however, there is an unobserved event of interest (not known if and when the event occurs), which when it occurs stops future transitions in the multistate process from occurring, then drawing inference from the joint multistate and event process can be problematic. In health studies, a particular example of this could be resolution, where a resolved patient can no longer experience any further symptoms, and this is explored here for illustration...
October 17, 2016: Statistics in Medicine
Danielle L Burke, Joie Ensor, Richard D Riley
Meta-analysis using individual participant data (IPD) obtains and synthesises the raw, participant-level data from a set of relevant studies. The IPD approach is becoming an increasingly popular tool as an alternative to traditional aggregate data meta-analysis, especially as it avoids reliance on published results and provides an opportunity to investigate individual-level interactions, such as treatment-effect modifiers. There are two statistical approaches for conducting an IPD meta-analysis: one-stage and two-stage...
October 16, 2016: Statistics in Medicine
Agus Salim, Bénédicte Delcoigne, Krystyn Villaflores, Woon-Puay Koh, Jian-Min Yuan, Rob M van Dam, Marie Reilly
Using both simulated and real datasets, we compared two approaches for estimating absolute risk from nested case-control (NCC) data and demonstrated the feasibility of using the NCC design for estimating absolute risk. In contrast to previously published results, we successfully demonstrated not only that data from a matched NCC study can be used to unbiasedly estimate absolute risk but also that matched studies give better statistical efficiency and classify subjects into more appropriate risk categories. Our result has implications for studies that aim to develop or validate risk prediction models...
October 13, 2016: Statistics in Medicine
Sammy Chebon, Christel Faes, Frank Cools, Helena Geys
Statistical analysis of count data typically starts with a Poisson regression. However, in many real-life applications, it is observed that the variation in the counts is larger than the mean, and one needs to deal with the problem of overdispersion in the counts. Several factors may contribute to overdispersion: (1) unobserved heterogeneity due to missing covariates, (2) correlation between observations (such as in longitudinal studies), and (3) the occurrence of many zeros (more than expected from the Poisson distribution)...
October 13, 2016: Statistics in Medicine
Michael J Sweeting, Jessica K Barrett, Simon G Thompson, Angela M Wood
Many prediction models have been developed for the risk assessment and the prevention of cardiovascular disease in primary care. Recent efforts have focused on improving the accuracy of these prediction models by adding novel biomarkers to a common set of baseline risk predictors. Few have considered incorporating repeated measures of the common risk predictors. Through application to the Atherosclerosis Risk in Communities study and simulations, we compare models that use simple summary measures of the repeat information on systolic blood pressure, such as (i) baseline only; (ii) last observation carried forward; and (iii) cumulative mean, against more complex methods that model the repeat information using (iv) ordinary regression calibration; (v) risk-set regression calibration; and (vi) joint longitudinal and survival models...
October 11, 2016: Statistics in Medicine
Zhuoyu Wang, Nandini Dendukuri, Lawrence Joseph
When two imperfect diagnostic tests are carried out on the same subject, their results may be correlated even after conditioning on the true disease status. While past work has focused on the consequences of ignoring conditional dependence, the degree to which conditional dependence can be induced has not been systematically studied. We examine this issue in detail by introducing a hypothetical missing covariate that affects the sensitivities of two imperfect dichotomous tests. We consider four forms for this covariate, normal, uniform, dichotomous and trichotomous...
October 11, 2016: Statistics in Medicine
Christopher Partlett, Richard D Riley
A random effects meta-analysis combines the results of several independent studies to summarise the evidence about a particular measure of interest, such as a treatment effect. The approach allows for unexplained between-study heterogeneity in the true treatment effect by incorporating random study effects about the overall mean. The variance of the mean effect estimate is conventionally calculated by assuming that the between study variance is known; however, it has been demonstrated that this approach may be inappropriate, especially when there are few studies...
October 7, 2016: Statistics in Medicine
Adrien Ickowicz, Ross Sparks
Length of hospital stay (LOS) is an important indicator of the hospital activity and management of health care. The skewness in the distribution of LOS poses problems in statistical modelling because it fails to adequately follow the usual traditional distribution of positive variables such as the log-normal distribution. We present in this paper a model using the convolution of two distributions, a technique well known in the signal processing community. The specificity of that model is that the variable of interest is considered to be the resulting sum of two random variables with different distributions...
October 5, 2016: Statistics in Medicine
Michael J Pencina, Jason P Fine, Ralph B D'Agostino
Discrimination slope, defined as the slope of a linear regression of predicted probabilities of event derived from a prognostic model on the binary event status, has recently gained popularity as a measure of model performance. It is as a building block for the integrated discrimination improvement that equals the difference in discrimination slopes between the two models being compared. Several authors have pointed out that it does not make sense to apply the integrated discrimination improvement and discrimination slope when working with mis-calibrated models, whereas others have raised concerns about the ability of improving discrimination slope without adding new information...
October 3, 2016: Statistics in Medicine
Katy E Morgan, Andrew B Forbes, Ruth H Keogh, Vipul Jairath, Brennan C Kahan
In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design...
September 28, 2016: Statistics in Medicine
Severin Guy Mahiané, Oliver Laeyendecker
The study considers the problem of estimating incidence of a non remissible infection (or disease) with possibly differential mortality using data from a(several) cross-sectional prevalence survey(s). Fitting segmented polynomial models is proposed to estimate the incidence as a function of age, using the maximum likelihood method. The approach allows automatic search for optimal position of knots, and model selection is performed using the Akaike information criterion. The method is applied to simulated data and to estimate HIV incidence among men in Zimbabwe using data from both the NIMH Project Accept (HPTN 043) and Zimbabwe Demographic Health Surveys (2005-2006)...
September 26, 2016: Statistics in Medicine
Reza Ramezan, Paul Marriott, Shojaeddin Chenouri
This paper introduces the Skellam process with resetting. Resetting is a modification that accommodates the modeling of neural spike trains. We show this as a biologically plausible model, which codes the information content of neural spike trains with three, potentially, time-varying functions. We show that the interspike interval distribution under this model follows a mixture of gamma distributions, a flexible class covering a wide range of commonly used models. Through simulation studies and the analyses of connected retinal ganglion and lateral geniculate nucleus cells, we evaluate the performance of this model...
September 26, 2016: Statistics in Medicine
Yuan Huang, Jin Liu, Huangdi Yi, Ben-Chang Shia, Shuangge Ma
In profiling studies, the analysis of a single dataset often leads to unsatisfactory results because of the small sample size. Multi-dataset analysis utilizes information of multiple independent datasets and outperforms single-dataset analysis. Among the available multi-dataset analysis methods, integrative analysis methods aggregate and analyze raw data and outperform meta-analysis methods, which analyze multiple datasets separately and then pool summary statistics. In this study, we conduct integrative analysis and marker selection under the heterogeneity structure, which allows different datasets to have overlapping but not necessarily identical sets of markers...
September 25, 2016: Statistics in Medicine
A Lawrence Gould, William B Wang
The development of drugs and biologicals whose mechanisms of action may extend beyond their target indications has led to a need to identify unexpected potential toxicities promptly even while blinded clinical trials are under way. One component of recently issued FDA rules regarding safety reporting requirements raises the possibility of breaking the blind for pre-identified serious adverse events that are not the clinical endpoints of a blinded study. Concern has been expressed that unblinding individual cases of frequently occurring adverse events could compromise the overall validity of the study...
September 25, 2016: Statistics in Medicine
Hong Sun, Frank Bretz, Oke Gerke, Werner Vach
The increasing emergence of predictive markers for different treatments in the same patient population allows us to define stratified treatment strategies. We consider randomized clinical trials that compare a standard treatment with a new stratified treatment strategy that divides the study population into subgroups receiving different treatments. Because the new strategy may not be beneficial in all subgroups, we consider in this paper an intermediate approach that establishes a treatment effect in a subset of patients built by joining several subgroups...
September 25, 2016: Statistics in Medicine
Vern Farewell, Tony Johnson
Background is provided on the discovery of an unpublished biography of Major Greenwood written by one of his sons. The motivation and preparation for online publication of the biography in Statistics in Medicine are outlined. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.
September 22, 2016: Statistics in Medicine
Zhiguo Li
In sequential multiple assignment randomized trials, longitudinal outcomes may be the most important outcomes of interest because this type of trials is usually conducted in areas of chronic diseases or conditions. We propose to use a weighted generalized estimating equation (GEE) approach to analyzing data from such type of trials for comparing two adaptive treatment strategies based on generalized linear models. Although the randomization probabilities are known, we consider estimated weights in which the randomization probabilities are replaced by their empirical estimates and prove that the resulting weighted GEE estimator is more efficient than the estimators with true weights...
September 19, 2016: Statistics in Medicine
Yong Zang, Ying Yuan
In the early phase development of molecularly targeted agents (MTAs), a commonly encountered situation is that the MTA is expected to be more effective for a certain biomarker subgroup, say marker-positive patients, but there is no adequate evidence to show that the MTA does not work for the other subgroup, that is, marker-negative patients. After establishing that marker-positive patients benefit from the treatment, it is often of great clinical interest to determine whether the treatment benefit extends to marker-negative patients...
September 19, 2016: Statistics in Medicine
Jun Yin, Rui Qin, Monia Ezzalfani, Daniel J Sargent, Sumithra J Mandrekar
Phase I oncology trials are designed to identify a safe dose with an acceptable toxicity profile. The dose is typically determined based on the probability of severe toxicity observed during the first treatment cycle, although patients continue to receive treatment for multiple cycles. In addition, the toxicity data from multiple types and grades are typically summarized into a single binary outcome of dose-limiting toxicity. A novel endpoint, the total toxicity profile, was previously developed to account for the multiple toxicity types and grades...
September 15, 2016: Statistics in Medicine
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