Results 21 to 30 of about 13,830,927 (82)

Fuzzy midpoint–based imputation methods for non-parametric survival estimation with interval-censored data

Frontiers in Applied Mathematics and Statistics
The analysis of failure time data frequently encounters situations in which the exact time of event occurrence is unknown but is known to lie within a specified interval, resulting in interval-censored data.
Kumbirai Kimpton Manungo, Chioneso Show Marange, Odilo Ndiweni   +2 more
doaj   +1 more source

Bootstrap Inference for K-Nearest Neighbour Matching Estimators [PDF]

Abadie and Imbens (2008, Econometrica) showed that classical bootstrap schemes fail to provide correct inference for K-nearest neighbour (KNN) matching estimators of average causal effects.
de Luna, Xavier, Sjöstedt-de Luna, Sara, Johansson, Per   +2 more
core   +2 more sources

Biological and Metabolic Correlates of Psychological Resilience in Maintenance Hemodialysis: An Exploratory Gender-Based Study

Medicina
Background and Objectives: Psychological resilience is central to emotional adaptation in patients undergoing maintenance hemodialysis (HD). Although psychosocial determinants have been widely studied, the role of routinely monitored biochemical markers ...
Gloria María Zaragoza Fernández, Avinash Chandu Nanwani, Elena Jiménez Mayor, Celia Rodríguez Tudero, Esperanza Moral Berrio, Alonso González de Gregorio, Marco Vaca Gallardo, Enrique Antonio Florit, José C. De La Flor, Rafael Fernández Castillo   +9 more
doaj   +1 more source

Simulation Experiments in Practice: Statistical Design and Regression Analysis [PDF]

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because ...
Kleijnen, J.P.C.
core   +2 more sources

A nonparametric test of exogeneity [PDF]

, 2004
This paper is concerned with inference about a function g that is identified by a conditional moment restriction involving instrumental variables. The function is nonparametric. It satisfies mild regularity conditions but is otherwise unknown. The paper
Richard Blundell, Joel L. Horowitz, Blundell, R., Horowitz, Joel, Horowitz, J., Blundell, Richard W.   +5 more
core   +1 more source

Borderline-MASI: A Novel Data Adjustment Method for Imbalanced Data Classification

Applied Computational Intelligence and Soft Computing
Imbalanced data are a vital issue in classification tasks, especially in real applications like fraud detection. Although various solutions have been proposed, ranging from sampling methods to algorithm methods, the performance of classifiers often ...
Thi-Lich Nghiem, Pierre Maréchal, Thuy Nguyen Thi Thu, Thi-Toan Nghiem   +3 more
doaj   +1 more source

A novel estimator for the two-way partial AUC

BMC Medical Informatics and Decision Making
Background The two-way partial AUC has been recently proposed as a way to directly quantify partial area under the ROC curve with simultaneous restrictions on the sensitivity and specificity ranges of diagnostic tests or classifiers.
Elias Chaibub Neto, Vijay Yadav, Solveig K. Sieberts, Larsson Omberg   +3 more
doaj   +1 more source

Bootstrap tests for simple structures in nonparametric time series regression. [PDF]

This paper concerns statistical tests for simple structures such as parametric models, lower order models and additivity in a general nonparametric autoregression setting.
Yao, Qiwei, Neumann, Michael H., Kreiss, Jens-Peter   +2 more
core  

R Code and Output Supporting: Resampling-Based Methods for Biologists

, 2020
See readme file.This repository contains data, R code, and associated output from running R code supporting results reported in: Fieberg, J., K. Vitense, and D. H. Johnson 2020. Resampling-Based Methods for Biologists.
Johnson, Douglas H, Vitense, Kelsey, Fieberg, John R   +2 more
core   +1 more source

Exact and approximate stepdown methods for multiple hypothesis testing [PDF]

Consider the problem of testing k hypotheses simultaneously. In this paper, we discuss finite and large sample theory of stepdown methods that provide control of the familywise error rate (FWE).
Michael Wolf, Joseph Romano
core