1,720,988 research outputs found
Estimation of Box's e for low- and high-dimensional repeated measures designs with unequal covariance matrices
No full textWe present new inference methods for the analysis of low- and high-dimensional repeated measures data from two-sample designs that may be unbalanced, the number of repeated measures per subject may be larger than the number of subjects, covariance matrices are not assumed to be spherical, and they can differ between the two samples. In comparison, we demonstrate how crucial it is for the popular Huynh-Feldt (HF) method to make the restrictive and often unrealistic or unjustifiable assumption of equal covariance matrices. The new method is shown to maintain desired a-levels better than the well-known HF correction, as demonstrated in several simulation studies. The proposed test gains power when the number of repeated measures is increased in a manner that is consistent with the alternative. Thus, even increasing the number of measurements on the same subject may lead to an increase in power. Application of the new method is illustrated in detail, using two different real data sets. In one of them, the number of repeated measures per subject is smaller than the sample size, while in the other one, it is larger
A conditional error function approach for adaptive enrichment designs with continuous endpoints
No full textAdaptive enrichment designs offer an efficient and flexible way to demonstrate the efficacy of a treatment in a clinically defined full population or in, eg, biomarker‐defined subpopulations while controlling the family‐wise Type I error rate in the strong sense. Frequently used testing strategies in designs with two or more stages include the combination test and the conditional error function approach. Here, we focus on the latter and present some extensions. In contrast to previous work, we allow for multiple subgroups rather than one subgroup only. For nested as well as nonoverlapping subgroups with normally distributed endpoints, we explore the effect of estimating the variances in the subpopulations. Instead of using a normal approximation, we derive new t ‐distribution–based methods for two different scenarios. First, in the case of equal variances across the subpopulations, we present exact results using a multivariate t ‐distribution. Second, in the case of potentially varying variances across subgroups, we provide some improved approximations compared to the normal approximation. The performance of the proposed conditional error function approaches is assessed and compared to the combination test in a simulation study. The proposed methods are motivated by an example in pulmonary arterial hypertension.Bundesministerium für Bildung und Forschung https://doi.org/10.13039/501100002347Deutsches Zentrum für Herz-Kreislaufforschung https://doi.org/10.13039/10001044
Clinical trials with nested subgroups: Analysis, sample size determination and internal pilot studies
No full text The importance of subgroup analyses has been increasing due to a growing interest in personalized medicine and targeted therapies. Considering designs with multiple nested subgroups and a continuous endpoint, we develop methods for the analysis and sample size determination. First, we consider the joint distribution of standardized test statistics that correspond to each (sub)population. We derive multivariate exact distributions where possible, providing approximations otherwise. Based on these results, we present sample size calculation procedures. Uncertainties about nuisance parameters which are needed for sample size calculations make the study prone to misspecifications. We discuss how a sample size review can be performed in order to make the study more robust. To this end, we implement an internal pilot study design where the variances and prevalences of the subgroups are reestimated in a blinded fashion and the sample size is recalculated accordingly. Simulations show that the procedures presented here do not inflate the type I error significantly and maintain the prespecified power as long as the sample size of the smallest subgroup is not too small. We pay special attention to the case of small sample sizes and attain a lower boundary for the size of the internal pilot study. </jats:p
Wild bootstrapping rank-based procedures: Multiple testing in nonparametric factorial repeated measures designs
No full textnparcomp: An R Software Package for Nonparametric Multiple Comparisons and Simultaneous Confidence Intervals
Full text linkOne-way layouts, i.e., a single factor with several levels and multiple observations at each level, frequently arise in various fields. Usually not only a global hypothesis is of interest but also multiple comparisons between the different treatment levels. In most practical situations, the distribution of observed data is unknown and there may exist a number of atypical measurements and outliers. Hence, use of parametric and semiparametric procedures that impose restrictive distributional assumptions on observed samples becomes questionable. This, in turn, emphasizes the demand on statistical procedures that enable us to accurately and reliably analyze one-way layouts with minimal conditions on available data. Nonparametric methods offer such a possibility and thus become of particular practical importance. In this article, we introduce a new R package nparcomp which provides an easy and user-friendly access to rank-based methods for the analysis of unbalanced one-way layouts. It provides procedures performing multiple comparisons and computing simultaneous confidence intervals for the estimated effects which can be easily visualized. The special case of two samples, the nonparametric Behrens-Fisher problem, is included. We illustrate the implemented procedures by examples from biology and medicine
Blinded sample size recalculation in adaptive enrichment designs
No full textAbstract
In the precision medicine era, (prespecified) subgroup analyses are an integral part of clinical trials. Incorporating multiple populations and hypotheses in the design and analysis plan, adaptive designs promise flexibility and efficiency in such trials. Adaptations include (unblinded) interim analyses (IAs) or blinded sample size reviews. An IA offers the possibility to select promising subgroups and reallocate sample size in further stages. Trials with these features are known as adaptive enrichment designs. Such complex designs comprise many nuisance parameters, such as prevalences of the subgroups and variances of the outcomes in the subgroups. Additionally, a number of design options including the timepoint of the sample size review and timepoint of the IA have to be selected. Here, for normally distributed endpoints, we propose a strategy combining blinded sample size recalculation and adaptive enrichment at an IA, that is, at an early timepoint nuisance parameters are reestimated and the sample size is adjusted while subgroup selection and enrichment is performed later. We discuss implications of different scenarios concerning the variances as well as the timepoints of blinded review and IA and investigate the design characteristics in simulations. The proposed method maintains the desired power if planning assumptions were inaccurate and reduces the sample size and variability of the final sample size when an enrichment is performed. Having two separate timepoints for blinded sample size review and IA improves the timing of the latter and increases the probability to correctly enrich a subgroup.Deutsches Zentrum für Herz‐Kreislaufforschung http://dx.doi.org/10.13039/100010447Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/50110000234
NGAL expression during cardiopulmonary bypass does not predict severity of postoperative acute kidney injury
No full textBackground: Renal injury is a serious complication after cardiac surgery and therefore, early detection and much more prediction of postoperative kidney injury is desirable. Neutrophil gelatinase-associated lipocalin (NGAL) is a predictive biomarker of acute kidney injury and may increase after cardiopulmonary bypass (CPB). However, time correlation of NGAL expression and severity of renal injury is still unclear. The aim of our study was to investigate CPB-related urine NGAL (uNGAL) secretion in correlation to postoperative renal function. Methods: Data of NGAL expression along with clinical data of 81 patients (52 male and 29 female) were included in this study. Mean age of the patients was 66.8 +/- 12.8 years. Urine NGAL was measured at seven time points (T-0: baseline; T-1: start CPB, T-2: 40 min on CPB; T-3: 80 min on CPB; T-4: 120 min on CPB; T-p1: 15 min after CPB; T-p2: 4 h after admission to the intensive care unit) and renal function in the postoperative period was classified daily according to Acute Kidney Injury Network (Ronco et al, Int J Artif Organs 30(5): 373-6) criteria (AKIN). Results: Expression of uNGAL increased at T-4 (120 min on CPB) and post-CPB (T-p1 and T-p2; p < 0.01 vs. baseline) but there was no correlation between uNGAL level and duration of CPB nor between uNGAL expression and occurrence of postoperative kidney injury. The renal function over 10 days after surgery remained normal in 50 patients (AKIN level 0), 18 patients (22%) developed mild and insignificant renal injury (AKIN level 1), eight patients (10%) developed moderate renal failure (AKIN level 2), and five patients (6%) severe kidney failure (AKIN level 3). Twenty-four out of 31 patients developed renal failure within the first 48 h after surgery. However, there was no correlation between uNGAL expression and severity of acute renal failure. Conclusion: Although uNGAL expression increased after CPB, the peak values neither predict acute postoperative kidney injury, nor severity of the injury
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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