scholarly journals Weighted Lin-Wang Tests for Crossing Hazards

2014 ◽  
Vol 2014 ◽  
pp. 1-5
Author(s):  
James A. Koziol ◽  
Zhenyu Jia
Keyword(s):  
Statistical Power ◽  
Logrank Test ◽  
Crossing Hazards

Lin and Wang have introduced a quadratic version of the logrank test, appropriate for situations in which the underlying survival distributions may cross. In this note, we generalize the Lin-Wang procedure to incorporate weights and investigate the performance of Lin and Wang’s test and weighted versions in various scenarios. We find that weighting does increase statistical power in certain situations; however, none of the procedures was dominant under every scenario.

Abstract W P113: Prolonged Use of Clopidogrel and Aspirin and Stroke Risk in Intracranial Stenosis in SAMMPRIS

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Christine Holmstedt ◽  
Michael J Lynn ◽  
Tanya N Turan ◽  
Colin P Derdeyn ◽  
David Fiorella ◽  
...  
Keyword(s):  
Primary Endpoint ◽  
Statistical Power ◽  
Intracranial Stenosis ◽  
Antithrombotic Agent ◽  
Logrank Test ◽  
Major Hemorrhage ◽  
Exact Test ◽  
Lipid Disorder ◽  
Primary Endpoints ◽  
Event Rates

Background: In the SAMMPRIS trial, the use of combination aspirin and clopidogrel for 90 days after enrollment could be one reason that the outcome of patients in the medical arm was better than expected. The SAMMPRIS protocol required stopping clopidogrel after 90 days unless the patient had a non-neurological indication for continued use. We sought to compare outcomes in patients on vs. off clopidogrel beyond 90 days. Methods: For patients who did not have a primary endpoint within 90 days after enrollment (n = 397), we compared baseline features (t and Fisher’s exact tests), survival curves for the primary endpoint beyond 90 days after enrollment (the logrank test), and major hemorrhages (Fisher’s exact test) in patients on vs. off clopidogrel in the medical arm and stenting arms. Results: In the medical and stenting groups combined, baseline factors that were significantly (p<0.05) different between those on vs. off clopidogrel beyond 90 days (all higher in on clopidogrel group) were: age, diabetes, lipid disorder, coronary disease, SBP, and on antithrombotic agent at qualifying event. The table shows the primary endpoints and major hemorrhages in patients on vs. off clopidogrel in both treatment groups. Conclusion: This analysis, which was underpowered to detect even very large differences in event rates, suggests that prolonged use of clopidogrel plus aspirin may lower the risk of stroke in medically treated patients with intracranial stenosis, but increase the risk of major hemorrhage. Further studies with higher statistical power are needed to test this hypothesis.

Power-Enhanced Funnel Plots for Meta-Analysis

2020 ◽  
Vol 228 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Michael Kossmeier ◽  
Ulrich S. Tran ◽  
Martin Voracek
Keyword(s):  
Statistical Power ◽  
Meta Analysis ◽  
Relevant Information ◽  
Selective Reporting ◽  
Graphical Display ◽  
Funnel Plot ◽  
Evidential Value ◽  
Graphical Displays ◽  
Funnel Plots ◽  
Meta Analyses

Abstract. Currently, dedicated graphical displays to depict study-level statistical power in the context of meta-analysis are unavailable. Here, we introduce the sunset (power-enhanced) funnel plot to visualize this relevant information for assessing the credibility, or evidential value, of a set of studies. The sunset funnel plot highlights the statistical power of primary studies to detect an underlying true effect of interest in the well-known funnel display with color-coded power regions and a second power axis. This graphical display allows meta-analysts to incorporate power considerations into classic funnel plot assessments of small-study effects. Nominally significant, but low-powered, studies might be seen as less credible and as more likely being affected by selective reporting. We exemplify the application of the sunset funnel plot with two published meta-analyses from medicine and psychology. Software to create this variation of the funnel plot is provided via a tailored R function. In conclusion, the sunset (power-enhanced) funnel plot is a novel and useful graphical display to critically examine and to present study-level power in the context of meta-analysis.

How to Detect Publication Bias in Psychological Research

2019 ◽  
Vol 227 (4) ◽  
pp. 261-279 ◽  
Author(s):  
Frank Renkewitz ◽  
Melanie Keiner
Keyword(s):  
Publication Bias ◽  
Effect Size ◽  
Statistical Power ◽  
Type I Error ◽  
Psychological Research ◽  
Type I ◽  
True Effect Size ◽  
Questionable Research Practices ◽  
True Effect ◽  
Meta Analyses

Abstract. Publication biases and questionable research practices are assumed to be two of the main causes of low replication rates. Both of these problems lead to severely inflated effect size estimates in meta-analyses. Methodologists have proposed a number of statistical tools to detect such bias in meta-analytic results. We present an evaluation of the performance of six of these tools. To assess the Type I error rate and the statistical power of these methods, we simulated a large variety of literatures that differed with regard to true effect size, heterogeneity, number of available primary studies, and sample sizes of these primary studies; furthermore, simulated studies were subjected to different degrees of publication bias. Our results show that across all simulated conditions, no method consistently outperformed the others. Additionally, all methods performed poorly when true effect sizes were heterogeneous or primary studies had a small chance of being published, irrespective of their results. This suggests that in many actual meta-analyses in psychology, bias will remain undiscovered no matter which detection method is used.

Replication of the Superstition and Performance Study by

2014 ◽  
Vol 45 (3) ◽  
pp. 239-245 ◽  
Author(s):  
Robert J. Calin-Jageman ◽  
Tracy L. Caldwell
Keyword(s):  
Task Difficulty ◽  
Statistical Power ◽  
Meta Analysis ◽  
A Priori ◽  
Significant Heterogeneity ◽  
Performance Study ◽  
Improve Performance ◽  
Research Designs ◽  
Series Of Experiments ◽  
And Performance

A recent series of experiments suggests that fostering superstitions can substantially improve performance on a variety of motor and cognitive tasks ( Damisch, Stoberock, & Mussweiler, 2010 ). We conducted two high-powered and precise replications of one of these experiments, examining if telling participants they had a lucky golf ball could improve their performance on a 10-shot golf task relative to controls. We found that the effect of superstition on performance is elusive: Participants told they had a lucky ball performed almost identically to controls. Our failure to replicate the target study was not due to lack of impact, lack of statistical power, differences in task difficulty, nor differences in participant belief in luck. A meta-analysis indicates significant heterogeneity in the effect of superstition on performance. This could be due to an unknown moderator, but no effect was observed among the studies with the strongest research designs (e.g., high power, a priori sampling plan).

Power of Modified Brown-Forsythe and Mixed-Model Approaches in Split-Plot Designs

Methodology ◽  
2017 ◽  
Vol 13 (1) ◽  
pp. 9-22 ◽  
Author(s):  
Pablo Livacic-Rojas ◽  
Guillermo Vallejo ◽  
Paula Fernández ◽  
Ellián Tuero-Herrero
Keyword(s):  
Repeated Measures ◽  
Statistical Power ◽  
Mixed Model ◽  
Covariance Structure ◽  
Simulation Method ◽  
Future Research ◽  
Repeated Measures Design ◽  
Fixed And Random Effects ◽  
Split Plot ◽  
High Level

Abstract. Low precision of the inferences of data analyzed with univariate or multivariate models of the Analysis of Variance (ANOVA) in repeated-measures design is associated to the absence of normality distribution of data, nonspherical covariance structures and free variation of the variance and covariance, the lack of knowledge of the error structure underlying the data, and the wrong choice of covariance structure from different selectors. In this study, levels of statistical power presented the Modified Brown Forsythe (MBF) and two procedures with the Mixed-Model Approaches (the Akaike’s Criterion, the Correctly Identified Model [CIM]) are compared. The data were analyzed using Monte Carlo simulation method with the statistical package SAS 9.2, a split-plot design, and considering six manipulated variables. The results show that the procedures exhibit high statistical power levels for within and interactional effects, and moderate and low levels for the between-groups effects under the different conditions analyzed. For the latter, only the Modified Brown Forsythe shows high level of power mainly for groups with 30 cases and Unstructured (UN) and Autoregressive Heterogeneity (ARH) matrices. For this reason, we recommend using this procedure since it exhibits higher levels of power for all effects and does not require a matrix type that underlies the structure of the data. Future research needs to be done in order to compare the power with corrected selectors using single-level and multilevel designs for fixed and random effects.

The Limits of Ego Depletion

2019 ◽  
Vol 50 (5-6) ◽  
pp. 292-304 ◽  
Author(s):  
Mario Wenzel ◽  
Marina Lind ◽  
Zarah Rowland ◽  
Daniela Zahn ◽  
Thomas Kubiak
Keyword(s):  
Research Agenda ◽  
Statistical Power ◽  
Interindividual Variability ◽  
Ego Depletion ◽  
Crossover Design ◽  
Effect Sizes ◽  
Future Research ◽  
Future Research Agenda ◽  
Depletion Effect ◽  
Within Subjects

Abstract. Evidence on the existence of the ego depletion phenomena as well as the size of the effects and potential moderators and mediators are ambiguous. Building on a crossover design that enables superior statistical power within a single study, we investigated the robustness of the ego depletion effect between and within subjects and moderating and mediating influences of the ego depletion manipulation checks. Our results, based on a sample of 187 participants, demonstrated that (a) the between- and within-subject ego depletion effects only had negligible effect sizes and that there was (b) large interindividual variability that (c) could not be explained by differences in ego depletion manipulation checks. We discuss the implications of these results and outline a future research agenda.

Statistical Power in Meta-Analysis

2006 ◽  
Author(s):  
Guy Cafri ◽  
Michael T. Brannick ◽  
Jeffrey Kromrey
Keyword(s):  
Statistical Power ◽  
Meta Analysis

Missing Data - Better "Not to Have Them", but What If You Do? (Part 1)

Marketing ZFP ◽  
2019 ◽  
Vol 41 (4) ◽  
pp. 21-32
Author(s):  
Dirk Temme ◽  
Sarah Jensen
Keyword(s):  
Missing Data ◽  
Statistical Power ◽  
Missing Values ◽  
Graphical Representation ◽  
Marketing Research ◽  
Likelihood Estimation ◽  
Parameter Estimates ◽  
Full Information Maximum Likelihood ◽  
Definition Of ◽  
Traditional Approaches

Missing values are ubiquitous in empirical marketing research. If missing data are not dealt with properly, this can lead to a loss of statistical power and distorted parameter estimates. While traditional approaches for handling missing data (e.g., listwise deletion) are still widely used, researchers can nowadays choose among various advanced techniques such as multiple imputation analysis or full-information maximum likelihood estimation. Due to the available software, using these modern missing data methods does not pose a major obstacle. Still, their application requires a sound understanding of the prerequisites and limitations of these methods as well as a deeper understanding of the processes that have led to missing values in an empirical study. This article is Part 1 and first introduces Rubin’s classical definition of missing data mechanisms and an alternative, variable-based taxonomy, which provides a graphical representation. Secondly, a selection of visualization tools available in different R packages for the description and exploration of missing data structures is presented.

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