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Biometrical Journal. Biometrische Zeitschrift

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https://www.readbyqxmd.com/read/29790186/predicting-events-in-clinical-trials-using-two-time-to-event-outcomes
#1
Rongji Mu, Jin Xu
In clinical trials with time-to-event outcomes, it is of interest to predict when a prespecified number of events can be reached. Interim analysis is conducted to estimate the underlying survival function. When another correlated time-to-event endpoint is available, both outcome variables can be used to improve estimation efficiency. In this paper, we propose to use the convolution of two time-to-event variables to estimate the survival function of interest. Propositions and examples are provided based on exponential models that accommodate possible change points...
May 22, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29775990/cox-model-with-interval-censored-covariate-in-cohort-studies
#2
Soohyun Ahn, Johan Lim, Myunghee Cho Paik, Ralph L Sacco, Mitchell S Elkind
In cohort studies the outcome is often time to a particular event, and subjects are followed at regular intervals. Periodic visits may also monitor a secondary irreversible event influencing the event of primary interest, and a significant proportion of subjects develop the secondary event over the period of follow-up. The status of the secondary event serves as a time-varying covariate, but is recorded only at the times of the scheduled visits, generating incomplete time-varying covariates. While information on a typical time-varying covariate is missing for entire follow-up period except the visiting times, the status of the secondary event are unavailable only between visits where the status has changed, thus interval-censored...
May 18, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29768667/analyzing-self-controlled-case-series-data-when-case-confirmation-rates-are-estimated-from-an-internal-validation-sample
#3
Stanley Xu, Christina L Clarke, Sophia R Newcomer, Matthew F Daley, Jason M Glanz
Vaccine safety studies are often electronic health record (EHR)-based observational studies. These studies often face significant methodological challenges, including confounding and misclassification of adverse event. Vaccine safety researchers use self-controlled case series (SCCS) study design to handle confounding effect and employ medical chart review to ascertain cases that are identified using EHR data. However, for common adverse events, limited resources often make it impossible to adjudicate all adverse events observed in electronic data...
May 16, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29766558/a-cure-rate-model-for-q-learning-estimating-an-adaptive-immunosuppressant-treatment-strategy-for-allogeneic-hematopoietic-cell-transplant-patients
#4
Erica E M Moodie, David A Stephens, Shomoita Alam, Mei-Jie Zhang, Brent Logan, Mukta Arora, Stephen Spellman, Elizabeth F Krakow
Cancers treated by transplantation are often curative, but immunosuppressive drugs are required to prevent and (if needed) to treat graft-versus-host disease. Estimation of an optimal adaptive treatment strategy when treatment at either one of two stages of treatment may lead to a cure has not yet been considered. Using a sample of 9563 patients treated for blood and bone cancers by allogeneic hematopoietic cell transplantation drawn from the Center for Blood and Marrow Transplant Research database, we provide a case study of a novel approach to Q-learning for survival data in the presence of a potentially curative treatment, and demonstrate the results differ substantially from an implementation of Q-learning that fails to account for the cure-rate...
May 16, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29749022/one-inflation-and-unobserved-heterogeneity-in-population-size-estimation-by-ryan-t-godwin
#5
LETTER
Gul Inan
In this study, we would like to show that the one-inflated zero-truncated negative binomial (OIZTNB) regression model can be easily implemented in R via built-in functions when we use mean-parameterization feature of negative binomial distribution to build OIZTNB regression model. From the practitioners' point of view, we believe that this approach presents a computationally convenient way for implementation of the OIZTNB regression model.
May 11, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29748991/marginalized-zero-inflated-poisson-models-with-missing-covariates
#6
Habtamu K Benecha, John S Preisser, Kimon Divaris, Amy H Herring, Kalyan Das
Unlike zero-inflated Poisson regression, marginalized zero-inflated Poisson (MZIP) models for counts with excess zeros provide estimates with direct interpretations for the overall effects of covariates on the marginal mean. In the presence of missing covariates, MZIP and many other count data models are ordinarily fitted using complete case analysis methods due to lack of appropriate statistical methods and software. This article presents an estimation method for MZIP models with missing covariates. The method, which is applicable to other missing data problems, is illustrated and compared with complete case analysis by using simulations and dental data on the caries preventive effects of a school-based fluoride mouthrinse program...
May 11, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29748972/multiple-testing-with-discrete-data-proportion-of-true-null-hypotheses-and-two-adaptive-fdr-procedures
#7
Xiongzhi Chen, Rebecca W Doerge, Joseph F Heyse
We consider multiple testing with false discovery rate (FDR) control when p values have discrete and heterogeneous null distributions. We propose a new estimator of the proportion of true null hypotheses and demonstrate that it is less upwardly biased than Storey's estimator and two other estimators. The new estimator induces two adaptive procedures, that is, an adaptive Benjamini-Hochberg (BH) procedure and an adaptive Benjamini-Hochberg-Heyse (BHH) procedure. We prove that the adaptive BH (aBH) procedure is conservative nonasymptotically...
May 11, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29748967/bivariate-random-effects-meta-analysis-models-for-diagnostic-test-accuracy-studies-using-arcsine-based-transformations
#8
Zelalem F Negeri, Mateen Shaikh, Joseph Beyene
Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation...
May 11, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29733452/modeling-clustered-long-term-survivors-using-marginal-mixture-cure-model
#9
Yi Niu, Lixin Song, Yufeng Liu, Yingwei Peng
There is a great deal of recent interests in modeling right-censored clustered survival time data with a possible fraction of cured subjects who are nonsusceptible to the event of interest using marginal mixture cure models. In this paper, we consider a semiparametric marginal mixture cure model for such data and propose to extend an existing generalized estimating equation approach by a new unbiased estimating equation for the regression parameters in the latency part of the model. The large sample properties of the regression effect estimators in both incidence and the latency parts are established...
May 7, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29718579/a-simulation-approach-for-power-calculation-in-large-cohort-studies-based-on-multistate-models
#10
Bastian Jenny, Jan Beyersmann, Martin Schumacher
Realistic power calculations for large cohort studies and nested case control studies are essential for successfully answering important and complex research questions in epidemiology and clinical medicine. For this, we provide a methodical framework for general realistic power calculations via simulations that we put into practice by means of an R-based template. We consider staggered recruitment and individual hazard rates, competing risks, interaction effects, and the misclassification of covariates. The study cohort is assembled with respect to given age-, gender-, and community distributions...
May 2, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29682785/bayesian-propensity-scores-for-high-dimensional-causal-inference-a-comparison-of-drug-eluting-to-bare-metal-coronary-stents
#11
Jacob V Spertus, Sharon-Lise T Normand
High-dimensional data provide many potential confounders that may bolster the plausibility of the ignorability assumption in causal inference problems. Propensity score methods are powerful causal inference tools, which are popular in health care research and are particularly useful for high-dimensional data. Recent interest has surrounded a Bayesian treatment of propensity scores in order to flexibly model the treatment assignment mechanism and summarize posterior quantities while incorporating variance from the treatment model...
April 23, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29611627/simultaneous-confidence-sets-for-several-effective-doses
#12
Daniel M Tompsett, Stefanie Biedermann, Wei Liu
Construction of simultaneous confidence sets for several effective doses currently relies on inverting the Scheffé type simultaneous confidence band, which is known to be conservative. We develop novel methodology to make the simultaneous coverage closer to its nominal level, for both two-sided and one-sided simultaneous confidence sets. Our approach is shown to be considerably less conservative than the current method, and is illustrated with an example on modeling the effect of smoking status and serum triglyceride level on the probability of the recurrence of a myocardial infarction...
April 3, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29603360/on-the-performance-of-adaptive-preprocessing-technique-in-analyzing-high-dimensional-censored-data
#13
Md Hasinur Rahaman Khan
Preprocessing for high-dimensional censored datasets, such as the microarray data, is generally considered as an important technique to gain further stability by reducing potential noise from the data. When variable selection including inference is carried out with high-dimensional censored data the objective is to obtain a smaller subset of variables and then perform the inferential analysis using model estimates based on the selected subset of variables. This two stage inferential analysis is prone to circularity bias because of the noise that might still remain in the dataset...
March 30, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29577405/smooth-individual-level-covariates-adjustment-in-disease-mapping
#14
Md Hamidul Huque, Craig Anderson, Richard Walton, Samuel Woolford, Louise Ryan
Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed...
March 25, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29577376/dynamic-prediction-of-cumulative-incidence-functions-by-direct-binomial-regression
#15
Mia K Grand, Theo J M de Witte, Hein Putter
In recent years there have been a series of advances in the field of dynamic prediction. Among those is the development of methods for dynamic prediction of the cumulative incidence function in a competing risk setting. These models enable the predictions to be updated as time progresses and more information becomes available, for example when a patient comes back for a follow-up visit after completing a year of treatment, the risk of death, and adverse events may have changed since treatment initiation. One approach to model the cumulative incidence function in competing risks is by direct binomial regression, where right censoring of the event times is handled by inverse probability of censoring weights...
March 25, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29577363/relative-efficiency-of-unequal-versus-equal-cluster-sizes-in-cluster-randomized-trials-using-generalized-estimating-equation-models
#16
Jingxia Liu, Graham A Colditz
There is growing interest in conducting cluster randomized trials (CRTs). For simplicity in sample size calculation, the cluster sizes are assumed to be identical across all clusters. However, equal cluster sizes are not guaranteed in practice. Therefore, the relative efficiency (RE) of unequal versus equal cluster sizes has been investigated when testing the treatment effect. One of the most important approaches to analyze a set of correlated data is the generalized estimating equation (GEE) proposed by Liang and Zeger, in which the "working correlation structure" is introduced and the association pattern depends on a vector of association parameters denoted by ρ...
March 25, 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29722115/editorial-year-2017-report
#17
EDITORIAL
Marco Alfò, Dankmar Böhning
No abstract text is available yet for this article.
May 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29532950/incorporating-historical-information-in-biosimilar-trials-challenges-and-a-hybrid-bayesian-frequentist-approach
#18
Johanna Mielke, Heinz Schmidli, Byron Jones
For the approval of biosimilars, it is, in most cases, necessary to conduct large Phase III clinical trials in patients to convince the regulatory authorities that the product is comparable in terms of efficacy and safety to the originator product. As the originator product has already been studied in several trials beforehand, it seems natural to include this historical information into the showing of equivalent efficacy. Since all studies for the regulatory approval of biosimilars are confirmatory studies, it is required that the statistical approach has reasonable frequentist properties, most importantly, that the Type I error rate is controlled-at least in all scenarios that are realistic in practice...
May 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29532948/mixtures-of-berkson-and-classical-covariate-measurement-error-in-the-linear-mixed-model-bias-analysis-and-application-to-a-study-on-ultrafine-particles
#19
Veronika Deffner, Helmut Küchenhoff, Susanne Breitner, Alexandra Schneider, Josef Cyrys, Annette Peters
The ultrafine particle measurements in the Augsburger Umweltstudie, a panel study conducted in Augsburg, Germany, exhibit measurement error from various sources. Measurements of mobile devices show classical possibly individual-specific measurement error; Berkson-type error, which may also vary individually, occurs, if measurements of fixed monitoring stations are used. The combination of fixed site and individual exposure measurements results in a mixture of the two error types. We extended existing bias analysis approaches to linear mixed models with a complex error structure including individual-specific error components, autocorrelated errors, and a mixture of classical and Berkson error...
May 2018: Biometrical Journal. Biometrische Zeitschrift
https://www.readbyqxmd.com/read/29532943/inference-from-single-occasion-capture-experiments-using-genetic-markers
#20
Chathurika K H Hettiarachchige, Richard M Huggins
Accurate estimation of the size of animal populations is an important task in ecological science. Recent advances in the field of molecular genetics researches allow the use of genetic data to estimate the size of a population from a single capture occasion rather than repeated occasions as in the usual capture-recapture experiments. Estimating the population size using genetic data also has sometimes led to estimates that differ markedly from each other and also from classical capture-recapture estimates. Here, we develop a closed form estimator that uses genetic information to estimate the size of a population consisting of mothers and daughters, focusing on estimating the number of mothers, using data from a single sample...
May 2018: Biometrical Journal. Biometrische Zeitschrift
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