Results 91 to 100 of about 6,488 (205)

Semiparametric volatility model with varying frequencies

Communications in Statistics - Simulation and Computation
In extracting time series data from various sources, it is inevitable to compile variables measured at varying frequencies as this is often dependent on the source. Modeling from these data can be facilitated by aggregating high frequency data to match the relatively lower frequencies of the rest of the variables.
Jetrei Benedick R. Benito, Joseph Ryan G. Lansangan, Erniel B. Barrios   +2 more
openaire   +2 more sources

Censoring, Competing Events, and Multistate Models: Comment on Beyersmann et al. “Hazards Constitute Key Quantities for Analyzing, Interpreting and Understanding Time‐to‐Event Data”

Biometrical Journal, Volume 68, Issue 4, August 2026.
ABSTRACT Beyersmann et al. propose a functional interpretation of hazards, viewing them as evolving quantities describing the entire event process rather than as pointwise causal contrasts. In this commentary, we elaborate on the implications of this view for causal inference in modern clinical trials with survival outcomes. We emphasize how censoring,
Malka Gorfine, Daniel Nevo
wiley   +1 more source

Overlap‐Weight Estimators With Machine‐Learned Plug‐Ins and Overlap‐Weight Targeted Maximum Likelihood Estimator

Biometrical Journal, Volume 68, Issue 4, August 2026.
ABSTRACT In estimating the average treatment effect (ATE), the plug‐in estimator with the efficient influence function and the targeted maximum likelihood estimator (TMLE) are semiparametrically efficient. However, the estimators suffer from the fact that too small/large a propensity score (PS) in the denominators can make the estimators unstable. This
Myoung‐jae Lee, Sanghyeok Lee
wiley   +1 more source

Models and methodologies for credit scoring in personal banking: A literature review

Revista CEA, 2017
This paper provides a literature review on risk scoring models for credit granting in personal banking. The methods by Abdou & Pointon (2011), Glennon, Kiefer, Larson, & Choi (2008), and Saavedra-García (2010) are considered.
David Esteban Rodríguez-Guevara, Jairo Alfonso Becerra-Arévalo, Daniel Cardona-Valencia   +2 more
doaj   +1 more source

Improving the Finite Sample Estimation of Average Treatment Effects Using Double/Debiased Machine Learning With Propensity Score Calibration

Journal of Applied Econometrics, Volume 41, Issue 5, Page 613-626, August 2026.
ABSTRACT Double/debiased machine learning (DML) uses for estimating an average treatment effect (ATE) a double‐robust score function that relies on the prediction of nuisance functions, such as the propensity score, which is the probability of treatment assignment given covariates.
Daniele Ballinari, Nora Bearth
wiley   +1 more source

Inverse‐Intensity‐Weighted Generalized Estimating Equations With Irregularly Measured Longitudinal Data and Informative Dropout

Statistics in Medicine, Volume 45, Issue 18-19, August 2026.
ABSTRACT Longitudinal data are commonly encountered in biomedical research, including randomized trials and retrospective cohort studies. Subjects are typically followed over a period of time and may be scheduled for follow‐up at predetermined time points.
George Stefan, Eleanor Pullenayegum
wiley   +1 more source

Variable Selection for Fixed and Random Effects in Multilevel Functional Mixed Effects Models

Statistics in Medicine, Volume 45, Issue 18-19, August 2026.
ABSTRACT We develop a new method for simultaneously selecting fixed and random effects in a multilevel functional regression model. The proposed method is motivated by accelerometer‐derived physical activity data from the 2011 to 2012 cohort of the National Health and Nutrition Examination Survey (NHANES), with the aim of identifying age and race ...
Rahul Ghosal, Marcos Matabuena, Enakshi Saha   +2 more
wiley   +1 more source

Joint Modeling of Longitudinal Data and Potentially Informative Visiting Process to Dynamically Predict Future Visit Times

Statistics in Medicine, Volume 45, Issue 18-19, August 2026.
ABSTRACT Frequent visits in cohort studies are important as they enable, among others, the assessment of disease progression and treatment effectiveness. In HIV studies, extended intervals between visits have been shown to be associated with adverse outcomes (e.g., antiretroviral therapy interruption).
Achilleas Stamoulopoulos, Christos Thomadakis, Giota Touloumi   +2 more
wiley   +1 more source

Multilevel Semiparametric Modeling with Overdispersion and Excess Zeros on School Dropout Rates in Indonesia

JTAM (Jurnal Teori dan Aplikasi Matematika)
This study aims to identify key factors influencing high school dropout rates in Indonesia by applying advanced statistical modeling that accounts for complex data characteristics.
Arna Ristiyanti Tarida, Anik Djuraidah, Agus Mohamad Soleh   +2 more
doaj   +1 more source

Examining the clustering of lifestyle factors and affect in daily life: An idiographic approach

Applied Psychology: Health and Well-Being, Volume 18, Issue 4, August 2026.
Abstract There has been an increase in interest in the health and well‐being benefits of lifestyle factors such as physical activity, diet, sleep, and social interaction. Previous research has highlighted how lifestyle factors, both healthy and unhealthy, tend to covary or cluster together.
Austen R. Anderson, Lindsey Ostermiller, Isabel Rice, Casandra O'Rourke   +3 more
wiley   +1 more source