- hierarchical linear-model, hierarchical linear regressionSee multi-level models.
Dictionary of sociology. 2013.
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Hierarchical linear modeling — In statistics, hierarchical linear modeling (HLM), a form of multi level analysis, is a more advanced form of simple linear regression and multiple linear regression. Multilevel analysis allows variance in outcome variables to be analysed at… … Wikipedia
Generalized linear model — In statistics, the generalized linear model (GLM) is a flexible generalization of ordinary least squares regression. It relates the random distribution of the measured variable of the experiment (the distribution function ) to the systematic (non … Wikipedia
Hierarchical model — redirects here. For the statistics usage, see hierarchical linear modeling. A hierarchical data model is a data model inwhich the data is organized into a tree like structure. The structure allows repeating information using parent/child… … Wikipedia
Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… … Wikipedia
Model of Hierarchical Complexity — The model of hierarchical complexity is a framework for scoring how complex a behavior is. It quantifies the order of hierarchical complexity of a task based on mathematical principles of how the information is organized and of information… … Wikipedia
Hierarchical hidden Markov model — The Hierarchical hidden Markov model (HHMM) is a statistical model derived from the hidden Markov model (HMM). In an HHMM each state is considered to be a self contained probabilistic model. More precisely each stateof the HHMM is itself an HHMM … Wikipedia
Random effects model — In statistics, a random effect(s) model, also called a variance components model is a kind of hierarchical linear model. It assumes that the data describe a hierarchy of different populations whose differences are constrained by the hierarchy. In … Wikipedia
Generalized scale-free model — There has been a burst of activity in the modeling of scale free complex networks. The recipe of Barabási and AlbertBarabási, A. L. and R. Albert, Science 286, 509(1999).] has been followed by several variations and generalizationsR. Albert, and… … Wikipedia
Mixture model — See also: Mixture distribution In statistics, a mixture model is a probabilistic model for representing the presence of sub populations within an overall population, without requiring that an observed data set should identify the sub population… … Wikipedia
Marginal model — In statistics, marginal models (Heagerty Zeger, 2000) are a technique for obtaining regression estimates in multilevel modeling, also called hierarchical linear models. People often want to know the effect of a predictor/explanatory variable X,… … Wikipedia