Multilevel Model News Today : Breaking News, Live Updates & Top Stories | Vimarsana

Stay updated with breaking news from Multilevel model. Get real-time updates on events, politics, business, and more. Visit us for reliable news and exclusive interviews.

Top News In Multilevel Model Today - Breaking & Trending Today

"Predicting the Finite Population Distribution Function under a Multile" by Sumonkanti Das, Nicola Salvati et al.

Chambers and Dunstan proposed a model-based predictor of the population distribution function that makes use of auxiliary population information under a general sampling design. Subsequently, Rao, Kovar, and Mantel proposed design-based ratio and difference predictors of the population distribution function that also use this auxiliary information. Both predictors (CD and RKM) assume a single level model for the target population. In this article we develop predictors of the finite population distribution function for a population that follows a multilevel model. These new predictors use the same smearing approach underpinning the CD predictor. We compare our new predictors with the CD and RKM predictors via design-based simulation, and show that they perform better than these single level predictors when there is significant intra-cluster correlation. The performances of these new two level predictors are also examined via an empirical study based on data from a large-scale UK busines ....

United Kingdom , Business Survey , Distribution Function , Multilevel Model , Mearing Approach ,

Can machine learning algorithms identify patients at risk of a delay in starting cancer treatment?

Multi-level machine learning models for estimating the risk of delay between cancer diagnosis and treatment initiation in a large group of cancer patients. ....

United States , Fox Chase Cancer Center , Multilevel Model , Identify Patients , Starting Cancer , Image Credit , Pacific Islander , Hispanic White , Cancer Treatment , Machine Learning , Cancer Diagnosis , Health Disparities ,

"The Effects of Omitting Components in a Multilevel Model With Social N" by Thomas Suesse, David Steel et al.

Multilevel models are often used to account for the hierarchical structure of social data and the inherent dependencies to produce estimates of regression coefficients, variance components associated with each level, and accurate standard errors. Social network analysis is another important approach to analysing complex data that incoproate the social relationships between a number of individuals. Extended linear regression models, such as network autoregressive models, have been proposed that include the social network information to account for the dependencies between persons. In this article, we propose three types of models that account for both the multilevel structure and the social network structure together, leading to network autoregressive multilevel models. We investigate theoretically and empirically, using simulated data and a data set from the Dutch Social Behavior study, the effect of omitting the levels and the social network on the estimates of the regression coeffici ....

Dutch Social Behavior , Autoregressive Model , Multilevel Model , Etwork Autoregressive Multilevel Models ,