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Biometrical Journal. Biometrische Zeitschrift

Andrea Callegaro, Bart Spiessens, Benjamin Dizier, Fernando U Montoya, Hans C van Houwelingen
In this paper, we considered different methods to test the interaction between treatment and a potentially large number (p) of covariates in randomized clinical trials. The simplest approach was to fit univariate (marginal) models and to combine the univariate statistics or p-values (e.g., minimum p-value). Another possibility was to reduce the dimension of the covariates using the principal components (PCs) and to test the interaction between treatment and PCs. Finally, we considered the Goeman global test applied to the high-dimensional interaction matrix, adjusted for the main (treatment and covariates) effects...
October 20, 2016: Biometrical Journal. Biometrische Zeitschrift
Koko Asakura, Toshimitsu Hamasaki, Scott R Evans
We discuss group-sequential designs in superiority clinical trials with multiple co-primary endpoints, that is, when trials are designed to evaluate if the test intervention is superior to the control on all primary endpoints. We consider several decision-making frameworks for evaluating efficacy or futility, based on boundaries using group-sequential methodology. We incorporate the correlations among the endpoints into the calculations for futility boundaries and sample sizes as a function of other design parameters, including mean differences, the number of analyses, and efficacy boundaries...
October 19, 2016: Biometrical Journal. Biometrische Zeitschrift
Tim Friede, Christian Röver, Simon Wandel, Beat Neuenschwander
Random-effects meta-analyses are used to combine evidence of treatment effects from multiple studies. Since treatment effects may vary across trials due to differences in study characteristics, heterogeneity in treatment effects between studies must be accounted for to achieve valid inference. The standard model for random-effects meta-analysis assumes approximately normal effect estimates and a normal random-effects model. However, standard methods based on this model ignore the uncertainty in estimating the between-trial heterogeneity...
October 18, 2016: Biometrical Journal. Biometrische Zeitschrift
Juha Karvanen, Mikko J Sillanpää
Science can be seen as a sequential process where each new study augments evidence to the existing knowledge. To have the best prospects to make an impact in this process, a new study should be designed optimally taking into account the previous studies and other prior information. We propose a formal approach for the covariate prioritization, that is the decision about the covariates to be measured in a new study. The decision criteria can be based on conditional power, change of the p-value, change in lower confidence limit, Kullback-Leibler divergence, Bayes factors, Bayesian false discovery rate or difference between prior and posterior expectation...
October 14, 2016: Biometrical Journal. Biometrische Zeitschrift
George O Agogo
Measurement error in exposure variables is a serious impediment in epidemiological studies that relate exposures to health outcomes. In nutritional studies, interest could be in the association between long-term dietary intake and disease occurrence. Long-term intake is usually assessed with food frequency questionnaire (FFQ), which is prone to recall bias. Measurement error in FFQ-reported intakes leads to bias in parameter estimate that quantifies the association. To adjust for bias in the association, a calibration study is required to obtain unbiased intake measurements using a short-term instrument such as 24-hour recall (24HR)...
October 5, 2016: Biometrical Journal. Biometrische Zeitschrift
I Manjula Schou, Ian C Marschner
Randomized clinical trials comparing several treatments to a common control are often reported in the medical literature. For example, multiple experimental treatments may be compared with placebo, or in combination therapy trials, a combination therapy may be compared with each of its constituent monotherapies. Such trials are typically designed using a balanced approach in which equal numbers of individuals are randomized to each arm, however, this can result in an inefficient use of resources. We provide a unified framework and new theoretical results for optimal design of such single-control multiple-comparator studies...
October 5, 2016: Biometrical Journal. Biometrische Zeitschrift
An-Min Tang, Xingqiu Zhao, Nian-Sheng Tang
This paper presents a novel semiparametric joint model for multivariate longitudinal and survival data (SJMLS) by relaxing the normality assumption of the longitudinal outcomes, leaving the baseline hazard functions unspecified and allowing the history of the longitudinal response having an effect on the risk of dropout. Using Bayesian penalized splines to approximate the unspecified baseline hazard function and combining the Gibbs sampler and the Metropolis-Hastings algorithm, we propose a Bayesian Lasso (BLasso) method to simultaneously estimate unknown parameters and select important covariates in SJMLS...
September 26, 2016: Biometrical Journal. Biometrische Zeitschrift
Ryan T Godwin
We present the one-inflated zero-truncated negative binomial (OIZTNB) model, and propose its use as the truncated count distribution in Horvitz-Thompson estimation of an unknown population size. In the presence of unobserved heterogeneity, the zero-truncated negative binomial (ZTNB) model is a natural choice over the positive Poisson (PP) model; however, when one-inflation is present the ZTNB model either suffers from a boundary problem, or provides extremely biased population size estimates. Monte Carlo evidence suggests that in the presence of one-inflation, the Horvitz-Thompson estimator under the ZTNB model can converge in probability to infinity...
September 23, 2016: Biometrical Journal. Biometrische Zeitschrift
Jocelânio W Oliveira, Dione M Valença, Pledson G Medeiros, Magaly Marçula
The use of control charts for monitoring schemes in medical context should consider adjustments to incorporate the specific risk for each individual. Some authors propose the use of a risk-adjusted survival time cumulative sum (RAST CUSUM) control chart to monitor a time-to-event outcome, possibly right censored, using conventional survival models, which do not contemplate the possibility of cure of a patient. We propose to extend this approach considering a risk-adjusted CUSUM chart, based on a cure rate model...
September 20, 2016: Biometrical Journal. Biometrische Zeitschrift
Özgür Asar, James Ritchie, Philip A Kalra, Peter J Diggle
We use data from an ongoing cohort study of chronic kidney patients at Salford Royal NHS Foundation Trust, Greater Manchester, United Kingdom, to investigate the influence of acute kidney injury (AKI) on the subsequent rate of change of kidney function amongst patients already diagnosed with chronic kidney disease (CKD). We use a linear mixed effects modelling framework to enable estimation of both acute and chronic effects of AKI events on kidney function. We model the fixed effects by a piece-wise linear function with three change-points to capture the acute changes in kidney function that characterise an AKI event, and the random effects by the sum of three components: a random intercept, a stationary stochastic process with Matérn correlation structure, and measurement error...
September 14, 2016: Biometrical Journal. Biometrische Zeitschrift
Janet A Tooze, Laurence S Freedman, Raymond J Carroll, Douglas Midthune, Victor Kipnis
The food frequency questionnaire (FFQ) is known to be prone to measurement error. Researchers have suggested excluding implausible energy reporters (IERs) of FFQ total energy when examining the relationship between a health outcome and FFQ-reported intake to obtain less biased estimates of the effect of the error-prone measure of exposure; however, the statistical properties of stratifying by IER status have not been studied. Under certain assumptions, including nondifferential error, we show that when stratifying by IER status, the attenuation of the estimated relative risk in the stratified models will be either greater or less in both strata (implausible and plausible reporters) than for the nonstratified model, contrary to the common belief that the attenuation will be less among plausible reporters and greater among IERs...
August 23, 2016: Biometrical Journal. Biometrische Zeitschrift
Willy Wynant, Michal Abrahamowicz
Standard optimization algorithms for maximizing likelihood may not be applicable to the estimation of those flexible multivariable models that are nonlinear in their parameters. For applications where the model's structure permits separating estimation of mutually exclusive subsets of parameters into distinct steps, we propose the alternating conditional estimation (ACE) algorithm. We validate the algorithm, in simulations, for estimation of two flexible extensions of Cox's proportional hazards model where the standard maximum partial likelihood estimation does not apply, with simultaneous modeling of (1) nonlinear and time-dependent effects of continuous covariates on the hazard, and (2) nonlinear interaction and main effects of the same variable...
August 23, 2016: Biometrical Journal. Biometrische Zeitschrift
Ching-Yun Wang, Xiao Song
Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample...
August 22, 2016: Biometrical Journal. Biometrische Zeitschrift
A Catharina Brockhaus, Ulrich Grouven, Ralf Bender
For the calculation of relative measures such as risk ratio (RR) and odds ratio (OR) in a single study, additional approaches are required for the case of zero events. In the case of zero events in one treatment arm, the Peto odds ratio (POR) can be calculated without continuity correction, and is currently the relative effect estimation method of choice for binary data with rare events. The aim of this simulation study is a variegated comparison of the estimated OR and estimated POR with the true OR in a single study with two parallel groups without confounders in data situations where the POR is currently recommended...
August 22, 2016: Biometrical Journal. Biometrische Zeitschrift
Antonio Punzo, Paul D McNicholas
A mixture of multivariate contaminated normal distributions is developed for model-based clustering. In addition to the parameters of the classical normal mixture, our contaminated mixture has, for each cluster, a parameter controlling the proportion of mild outliers and one specifying the degree of contamination. Crucially, these parameters do not have to be specified a priori, adding a flexibility to our approach. Parsimony is introduced via eigen-decomposition of the component covariance matrices, and sufficient conditions for the identifiability of all the members of the resulting family are provided...
August 11, 2016: Biometrical Journal. Biometrische Zeitschrift
Markus Pauly, Thomas Asendorf, Frank Konietschke
We investigate rank-based studentized permutation methods for the nonparametric Behrens-Fisher problem, that is, inference methods for the area under the ROC curve. We hereby prove that the studentized permutation distribution of the Brunner-Munzel rank statistic is asymptotically standard normal, even under the alternative. Thus, incidentally providing the hitherto missing theoretical foundation for the Neubert and Brunner studentized permutation test. In particular, we do not only show its consistency, but also that confidence intervals for the underlying treatment effects can be computed by inverting this permutation test...
August 9, 2016: Biometrical Journal. Biometrische Zeitschrift
Craig Anderson, Duncan Lee, Nema Dean
Spatiotemporal disease mapping focuses on estimating the spatial pattern in disease risk across a set of nonoverlapping areal units over a fixed period of time. The key aim of such research is to identify areas that have a high average level of disease risk or where disease risk is increasing over time, thus allowing public health interventions to be focused on these areas. Such aims are well suited to the statistical approach of clustering, and while much research has been done in this area in a purely spatial setting, only a handful of approaches have focused on spatiotemporal clustering of disease risk...
August 5, 2016: Biometrical Journal. Biometrische Zeitschrift
Wen-Han Hwang, Richard Huggins, Jakub Stoklosa
The negative binomial distribution is a common model for the analysis of count data in biology and ecology. In many applications, we may not observe the complete frequency count in a quadrat but only that a species occurred in the quadrat. If only occurrence data are available then the two parameters of the negative binomial distribution, the aggregation index and the mean, are not identifiable. This can be overcome by data augmentation or through modeling the dependence between quadrat occupancies. Here, we propose to record the (first) detection time while collecting occurrence data in a quadrat...
August 1, 2016: Biometrical Journal. Biometrische Zeitschrift
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September 2016: Biometrical Journal. Biometrische Zeitschrift
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September 2016: Biometrical Journal. Biometrische Zeitschrift
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