Results 121 to 130 of about 30,695 (301)
Acta Universitatis Lodziensis. Folia Oeconomica, 2014 The aim of this paper is to evaluate the spatial and hierarchical models for data generating processes with spatial heterogeneity and spatial dependence at the higher level.
Edyta Łaszkiewicz
doaj
Model Misspecification, Learning and Real Exchange Rate Dynamics
, 2015 Based on Lewis & Markiewicz (2009), the purpose of this paper is to explore if implied real exchange rate dynamics are similar to these obtained from observed data under a model with misspecification.
Liu, Jia-luen
core
Canadian Journal of Statistics, EarlyView.Abstract Irregular observation times are common in longitudinal observational studies and can affect causal inferences. We use data from electronic health records of Kaiser Permanente Washington patients in the United States who initiated an antidepressant medication between 2008 and 2018, with a confirming diagnosis of depression. We are interested in
Janie Coulombe +2 more
wiley +1 more source
Model selection for causal inference in missing exposure problems
Canadian Journal of Statistics, EarlyView.Abstract In causal inference, properly selecting the propensity score (PS) model is an important topic and has been widely investigated in observational studies. However, there are very few studies investigating the model selection issue for causal inference when the exposure is missing at random (MAR). When the exposure variable contains missing data,
Yuliang Shi, Yeying Zhu, Joel A. Dubin
wiley +1 more source
Joint copula‐based beta regression with covariate‐dependent dispersion for malaria indicators
Canadian Journal of Statistics, EarlyView.Abstract Malaria surveillance relies on multiple indicators that reflect different aspects of transmission and disease burden, yet these outcomes are often analyzed separately under constant‐variance assumptions. Such approaches may obscure residual dependence and heterogeneity in variability. Using Demographic and Health Survey data from Burkina Faso (
Guanjie Lyu, Cindy Feng
wiley +1 more source
Semi-parametric local variable selection under misspecification [PDF]
Local variable selection aims to test for the effect of covariates on an outcome within specific regions. We outline a challenge that arises in the presence of non-linear effects and model misspecification.
Saez, Ignacio +3 more
core +1 more source
BMC Medical Research MethodologyBackground 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 +3 more
doaj +1 more source
Canadian Journal of Statistics, EarlyView.Abstract Primary biliary cholangitis (PBC) is a progressive autoimmune cholestatic disease for which modelling death, with transplantation as a competing event, is clinically important. Cox proportional hazards (PH) models are widely used, but standard diagnostics detect lack of fit without distinguishing non‐PH from misspecified covariate functions ...
Tingxuan Wu, Cindy Feng, Longhai Li
wiley +1 more source
Assessing parametric misspecification and heterogeneity in growth regression
, 2011 A fully nonparametric analysis is applied to address the problems of nonlinearity and heterogeneity in classical growth regression models using original data from seminal contributions in this field.
Haupt, Harry +3 more
core +1 more source
Clinical Pharmacology &Therapeutics, EarlyView.Cofetuzumab pelidotin (Cofe‐P) is an anti‐protein tyrosine kinase 7 (PTK7) antibody‐drug conjugate (ADC) being investigated for the treatment of adults with PTK7‐expressing, recurrent non‐small cell lung cancer (NSCLC). The first‐in‐human (FIH) trial demonstrated tolerability of dosages ≤ 2.8 mg/kg once every 3 weeks (Q3W) and ≤ 3.2 mg/kg Q2W ...
Carla Biesdorf +8 more
wiley +1 more source