Results 71 to 80 of about 77,552 (290)

Target Firm's ESG Engagement and Post–M&A Performance: The Mediating Role of Acquirer's CSR Strategy

Business Strategy and the Environment, EarlyView.
ABSTRACT The paper examines whether the environmental, social and governance (ESG) performance of target firms influences both accounting‐based and market‐based corporate financial performance (CFP) within the merger and acquisition (M&A) context and whether this relationship is mediated by the acquirer's corporate social responsibility (CSR) strategy.
Francesco Gangi, Nicola Varrone, Mario Ossorio, Lucia Michela Daniele, Maria Coscia   +4 more
wiley   +1 more source

Can quartet analyses combining maximum likelihood estimation and Hennigian logic overcome long branch attraction in phylogenomic sequence data? [PDF]

PLoS ONE, 2017
Systematic biases such as long branch attraction can mislead commonly relied upon model-based (i.e. maximum likelihood and Bayesian) phylogenetic methods when, as is usually the case with empirical data, there is model misspecification.
Patrick Kück, Mark Wilkinson, Christian Groß, Peter G Foster, Johann W Wägele   +4 more
doaj   +1 more source

Strategic Shift: The Power of Green Strategy on Sustainability Performance

Business Strategy and the Environment, EarlyView.
ABSTRACT Employing FTSE Russell's unique Green Revenues data on S&P 1500 firms from 2016 to 2024, this study examines the long‐term effects of a corporate strategic shift toward green strategy, proxied by green revenue reporting, on corporate sustainability performance.
Post Raj Pokharel
wiley   +1 more source

Performance Bounds for Parameter Estimation under Misspecified Models: Fundamental findings and applications

, 2017
Inferring information from a set of acquired data is the main objective of any signal processing (SP) method. In particular, the common problem of estimating the value of a vector of parameters from a set of noisy measurements is at the core of a ...
Fortunati, S., Gini, F., Greco, M. S., Richmond, C. D.   +3 more
core   +1 more source

The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?

Chemistry – A European Journal, EarlyView.
Machine‐learning potentials are increasingly taking on the exploratory tasks of homogeneous catalysis, enabling rapid conformer sampling and reaction‐space mapping. However, when selectivity depends on subtle electronic effects, electronic‐structure methods remain essential.
Maxime Ferrer, Julen Munarriz, Thijs Stuyver, Ruben Laplaza   +3 more
wiley   +1 more source

Modelling the Incremental Value of Personality Facets: The Domains‐Incremental Facets‐Acquiescence Bifactor Model

European Journal of Personality, EarlyView., 2020
Abstract Personality can be described at different levels of abstraction. Whereas the Big Five domains are the dominant level of analysis, several researchers have called for more fine‐grained approaches, such as facet‐level analysis. Personality facets allow more comprehensive descriptions, more accurate predictions of outcomes, and a better ...
Daniel Danner, Clemens M. Lechner, Christopher J. Soto, Oliver P. John, René Mõttus   +4 more
wiley   +1 more source

Investigating item complexity as a source of cross-national DIF in TIMSS math and science

Large-scale Assessments in Education
Background Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or ...
Qi Huang, Daniel M. Bolt, Weicong Lyu
doaj   +1 more source

Rank‐based estimation of propensity score weights via subclassification

Canadian Journal of Statistics, EarlyView.
Abstract Propensity score (PS) weighting estimators are widely used for causal effect estimation and enjoy desirable theoretical properties, such as consistency and potential efficiency under correct model specification. However, their performance can degrade in practice due to sensitivity to PS model misspecification.
Linbo Wang, Yuexia Zhang, Thomas S. Richardson, Xiaohua Zhou   +3 more
wiley   +1 more source

A goodness‐of‐fit test for regression models with discrete outcomes

Canadian Journal of Statistics, EarlyView.
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang, Christian Genest, Johanna G. Nešlehová   +2 more
wiley   +1 more source

A partially heterogeneous weighted fusion learning method for potential heterogeneous treatment effect in multi-site survival study

BMC Medical Research Methodology
Background In multi-site studies in clinical practice, the treatment effects may exhibit potential heterogeneity across different sites. Additionally, propensity score methods used to adjust for confounding may suffer from model misspecification, which ...
Chen Huang, Kecheng Wei, Yongfu Yu, Guoyou Qin   +3 more
doaj   +1 more source