Improved Coefficient and Variance Estimation in Stable First-Order Dynamic Regression Models [PDF]
In dynamic regression models the least-squares coefficient estimators are biased in finite samples, and so are the usual estimators for the disturbance variance and for the variance of the coefficient estimators.
Garry D. A. Phillips, Jan F. Kiviet
core
Nonparametric Estimation of ROC Surfaces Under Verification Bias
Revstat Statistical Journal, 2020 Verification bias is a well known problem that can affect the statistical evaluation of the predictive ability of a diagnostic test when the true disease status is unknown for some of the patients under study.
Khanh To Duc +2 more
doaj +1 more source
Development of 4T1 breast cancer mouse model system for preclinical carbonic anhydrase IX studies
FEBS Open Bio, EarlyView.Carbonic anhydrase IX (CAIX) is a well‐recognised therapeutic target and prognostic biomarker in cancer. We developed and characterised a robust murine breast cancer model system that is suitable for CAIX studies in vitro and in vivo—it comprises both CAIX‐positive and CAIX‐negative controls and provides a solid platform for the comprehensive ...
Zane Kalniņa +13 more
wiley +1 more source
Higher Order Bias Correcting Moment Equation for M-Estimation and its Higher Order Efficiency [PDF]
This paper studies an alternative bias correction for the M-estimator, which is obtained by correcting the moment equation in the spirit of Firth (1993).
Kyoo il Kim
core +3 more sources
A chain ratio exponential type estimator in two-phase sampling using auxiliary information
Statistica, 2014 This paper advocates the problem of estimating the population mean of the study variable y using the information on two auxiliary variables x and z. We have suggested the family of chain ratio exponential type estimators in two-phase (or double) sampling.
Rohini Yadav +3 more
doaj +1 more source
Current trends in single‐cell RNA sequencing applications in diabetes mellitus
FEBS Open Bio, EarlyView.Single‐cell RNA sequencing is a powerful approach to decipher the cellular and molecular landscape at a single‐cell resolution. The rapid development of this technology has led to a wide range of applications, including the detection of cellular and molecular mechanisms and the identification and introduction of novel potential diagnostic and ...
Seyed Sajjad Zadian +6 more
wiley +1 more source
Small Sample Bias Propreties of the System GMM Estimator in Dynamic Panel Data Models [PDF]
This paper examines analytically and experimentally why the system GMM estimator in dynamic panel data models is less biased than the first differencing or the level estimators even though the former uses more instruments.
Kazuhiko Hayakawa
core
PLoS ONE, 2019 Estimating a predictive model from a dataset is best initiated with an unbiased estimator. However, since the unbiased estimator is unknown in general, the problem of the bias-variance tradeoff is raised.
Jeongwoo Kim
doaj +1 more source
Beyond p‐values: Assessing clinical significance in acupuncture research
Advanced Chinese Medicine, EarlyView.Abstract In acupuncture randomized controlled trials (RCTs), the proper interpretation of results requires a thorough understanding of key statistical concepts such as p‐value, effect size, and the minimal clinically important difference (MCID). This paper explores the relationships among these metrics and their implications for assessing the clinical ...
Changzhen Gong
wiley +1 more source
Local GMM Estimation of Time Series Models with Conditional Moment Restrictions [PDF]
This paper investigates statistical properties of the local GMM (LGMM) estimator for some time series models defined by conditional moment restrictions. First, we consider Markov processes with possible conditional heteroskedasticity of unknown form and ...
Nikolay Gospodinov, Taisuke Otsu
core