Results 101 to 110 of about 71,233 (305)

Dynamic survival risk prediction with time‐varying high‐dimensional images

Canadian Journal of Statistics, EarlyView.
Abstract Integrating longitudinal data with survival models is a prevalent strategy for dynamic survival risk prediction while accounting for subjects' longitudinally observed variables. However, existing methods primarily focus on scalar longitudinal data and seldom tackle the complexities associated with high‐dimensional longitudinal imaging data ...
Bingfan Liu, Haolun Shi, Shu Jiang, Liangliang Wang, Da Ma, Mirza Faisal Beg, Jiguo Cao, for the Alzheimer's Disease Neuroimaging Initiative   +7 more
wiley   +1 more source

Wissensproduktion im Teamlernen (Knowledge Productive Learning in Teams)

Beiträge zur Lehrerinnen- und Lehrerbildung, 2008
Teamlernen bedeutet, dass die Beiträge Einzelner zu einem gemeinsam geteilten Verständnis über einen Sachverhalt unter professionell Handelnden führen. Die einzelnen Mitglieder des Teams sind Teil einer Forschungsgemeinschaft von Sachkundigen.
Harm H. Tillema
doaj   +1 more source

Copula‐based joint modelling of emergency department visits with time‐varying dependence

Canadian Journal of Statistics, EarlyView.
Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley   +1 more source

12. Vorlesung (23.01.2020): IRT Modelle

, 2020
Vorlesungsinhalt: Mehrgruppen IRT Modelle; Längsschnittliche IRT Modelle; Agenda; Kategorien- vs.
Rose, Norman, Multimediazentrum
core  

Analyzing zero‐truncated recurrent event data by stratified regression with time‐varying coefficients

Canadian Journal of Statistics, EarlyView.
Abstract This article presents a strategy for conducting regression analysis of zero‐truncated recurrent event data. The research is partly motivated by a pediatric mental health care (PMHC) program based on administrative data. We are particularly interested in how the occurrence of an event depends on its past occurrences and the associated ...
Anqi A. Chen, X. Joan Hu, Rhonda J. Rosychuk, Leilei Zeng   +3 more
wiley   +1 more source

Nonparametric maximum likelihood estimation of the survival function using current lifetime data

Canadian Journal of Statistics, EarlyView.
Abstract An issue when estimating the failure time survival function is how to set up a prevalent cohort study infrastructure to follow subjects after enrollment. This problem can be circumvented through the well‐known Grenander density estimator using current lifetime observations only.
James H. McVittie, Masoud Asgharian
wiley   +1 more source

Are language models models?

Behavioral and Brain Sciences
Abstract Futrell and Mahowald claim language models (LMs) “serve as model systems,” but an assessment at each of Marr’s three levels suggests the claim is clearly not true at the implementation level, poorly motivated at the algorithmic-representational level, and problematic at the computational theory level.
openaire   +3 more sources

Homophily‐adjusted social influence estimation

Canadian Journal of Statistics, EarlyView.
Abstract Homophily and social influence are two key concepts of social network analysis. Distinguishing between these phenomena is difficult, and approaches to disambiguate the two have been primarily limited to longitudinal data analyses. In this study, we provide sufficient conditions for valid estimation of social influence through cross‐sectional ...
Hanh T.D. Pham, Daniel K. Sewell
wiley   +1 more source

Lasso for hierarchical polynomial models

Canadian Journal of Statistics, EarlyView.
Abstract The divisibility conditions implicit in a polynomial hierarchy suggest parameter constraints in regression. With this idea, we establish strong and weak hierarchies for both the lasso and relaxed lasso. Our proposal extends prior work on hierarchical lasso, which was mainly concerned with models of degree 2.
H. Maruri‐Aguilar, S. Lunagómez
wiley   +1 more source

Sparse maximum likelihood estimation of regression models

Canadian Journal of Statistics, EarlyView.
Abstract For regression model selection and estimation, we study a small set of candidate models of maximum likelihood from which all information criteria such as the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) choose their models.
Min Tsao
wiley   +1 more source