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20072026
most citedReproducible Research Can Still Be Wrong: Adopting a Prevention Approach

203 citations

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11 papers · 1 filter

stat.AP2025★ 1 cited

A Spatiotemporal, Quasi-experimental Causal Inference Approach to Characterize the Effects of Global Plastic Waste Export and Burning on Air Quality Using Remotely Sensed Data

Ellen M. Considine, Rachel C. Nethery

Open burning of plastic waste may pose a significant threat to global health by degrading air quality, but quantitative research on this problem -- crucial for policy making -- has…

stat.AP2021

The survival-incorporated median versus the median in the survivors or in the always-survivors: What are we measuring? And why?

Qingyan Xiang, Ronald J. Bosch, Judith J. Lok

Many clinical studies evaluate the benefit of a treatment based on both survival and other continuous/ordinal clinical outcomes, such as Quality of Life scores. In these studies, w…

stat.AP2018★ 1 cited

National PM2.5 and NO2 Exposure Models for China Based on Land Use Regression, Satellite Measurements, and Universal Kriging

Hao Xu, Matthew J. Bechle, Meng Wang +4

Outdoor air pollution is a major killer worldwide and the fourth largest contributor to the burden of disease in China. China is the most populous country in the world and also has…

stat.AP2018

Cox Model with Covariate Measurement Error and Unknown Changepoint

Sarit Agami, David M. Zucker, Donna Spiegelman

The standard Cox model in survival analysis assumes that the covariate effect is constant across the entire covariate domain. However, in many applications, there is interest in co…

stat.AP2018

Estimation in the Cox Survival Regression Model with Covariate Measurement Error and a Changepoint

Sarit Agami, David M. Zucker, Donna Spiegelman

The Cox regression model is a popular model for analyzing the relationship between a covariate and a survival endpoint. The standard Cox model assumes a constant covariate effect a…

stat.AP2018★ 1 cited

Bayesian Multi-study Factor Analysis for High-throughput Biological Data

Roberta De Vito, Ruggero Bellio, Lorenzo Trippa +1

This paper presents a new modeling strategy for joint unsupervised analysis of multiple high-throughput biological studies. As in Multi-study Factor Analysis, our goals are to iden…

stat.AP2018

Bayesian method for inferring the impact of geographical distance on intensity of communication

Fei Li, Jukka-Pekka Onnela, Victor DeGruttola

Both theoretical models and empirical findings suggest that the intensity of communication among groups of people declines with their degree of geographical separation. There is so…

stat.AP2015★ 203 cited

Reproducible Research Can Still Be Wrong: Adopting a Prevention Approach

Jeffrey T. Leek, Roger D. Peng

Reproducibility, the ability to recompute results, and replicability, the chances other experimenters will achieve a consistent result, are two foundational characteristics of succ…

stat.AP2010★ 12 cited

Bayesian inference and model choice in a hidden stochastic two-compartment model of hematopoietic stem cell fate decisions

Youyi Fong, Peter Guttorp, Janis Abkowitz

Despite rapid advances in experimental cell biology, the in vivo behavior of hematopoietic stem cells (HSC) cannot be directly observed and measured. Previously we modeled feline h…

stat.AP2010★ 11 cited

Nonparametric inference procedure for percentiles of the random effects distribution in meta-analysis

Rui Wang, Lu Tian, Tianxi Cai +1

To investigate whether treating cancer patients with erythropoiesis-stimulating agents (ESAs) would increase the mortality risk, Bennett et al. [Journal of the American Medical Ass…

stat.AP2008★ 23 cited

Multi-center clinical trials: Randomization and ancillary statistics

Lu Zheng, Marvin Zelen

The purpose of this paper is to investigate and develop methods for analysis of multi-center randomized clinical trials which only rely on the randomization process as a basis of i…