Multilevel Models

(noun)

Multilevel models are statistical models of parameters that vary at more than one level. These models can be seen as generalizations of linear models (in particular, linear regression), although they can also extend to non-linear models.

Related Terms

  • Social epidemiology
  • Emile Durkheim

Examples of Multilevel Models in the following topics:

  • Social Epidemiology and Health

    • Use of such multilevel models is also known as hierarchical and mixed effects models.
  • Intorduction to qualitative analysis

    • An alternative approach is block modeling.
    • In principle, one could fit any sort of block model to actor-by-event incidence data.
    • We will examine two models that ask meaningful (alternative) questions about the patterns of linkage between actors and events.
    • Both of these models can be directly calculated in UCINET.
    • Alternative block models, of course, could be fit to incidence data using more general block-modeling algorithms.
  • Introduction to explaining the relations among actors in a network

    • Models like these are very useful for examining the relationships among relational and non-relational attributes of individuals.
    • Several of the models below explore homophily and closeness to predict whether actors have ties, or are close to one another.
    • The last model that we will look at the "P1" model also seeks to explain relations.
    • The P1 model tries to predict whether there exists no relation, an asymmetrical relation, or a reciprocated tie between pairs of actors.
    • This type of model -- a probability model for the presence/absence of each possible relation in a graph as a function of network structures -- is one of the major continuing areas of development in social network methods.
  • Homophily models

    • The routine Tools>Testing Hypotheses>Mixed Dyadic/Nodal>Categorical Attributes>ANOVA Density Models provides specific tests of some quite specific homophily models.
    • Next, a regression model is fit to the data.
    • The results of fitting this model to the data is shown in figure 18.19.
    • This model fits the data much better (R-square = .269, with p < .000) than the constant homophily model.
    • The fit of this model is better (R-square = .037) but still very poor.
  • Integration Theory

    • Numerous models could be presented in this vein.
    • George Ritzer's Integration Model is a good example.
    • If used for understanding a specific cultural phenomenon, like the displaying of abstract art in one's home, the integration model depicts the different influences on the decision.
    • For instance, the model depicts that cultural norms can influence individual behavior.
    • The model also shows that individual level values, beliefs, and behaviors influence macro-level culture.
  • The Structure of Cities

    • Urban structure is the arrangement of land use, explained using different models.
    • In grid models, land is divided by streets intersect at right angles, forming a grid.
    • This model's general applicability has been challenged.
    • Like the concentric ring model, Hoyt's sectoral model has been criticized for ignoring physical features and new transportation patterns that restrict or direct growth.
    • Analyze, using human ecology theory, the similarities and differences between the various urban structure models, such as grid model, sectoral model and concentric ring model, among others
  • Two-mode factions analysis

    • An alternative block model is that of "factions."
    • Networks>Subgroups>Factions fits this block model to one-mode data (for any user-specified number of factions).
    • Network>2-Mode>2-Mode Factions fits the same type of model to two-mode data (but for only two factions).
    • The fit of the two factions model is not as impressive as the fit of the core-periphery model.
    • Two mode factions model of California $1M donors and ballot initiatives (truncated)
  • The probability of a dyadic tie: Leinhardt's P1

    • The P1 model (and its newer successor the P* model), seek to predict the dyadic relations among actor pairs using key relational attributes of each actor, and of the graph as a whole.
    • Figure 18.27 shows the results of fitting the P1 model to the Knoke binary information network.
    • Using the equations, it is possible to predict the probability of each directed tie based on the model's parameters.
    • For example, the model predicts a 93% chance of a tie from actor 1 to actor 2.
    • Here we see that, for example, that actors 3 and 6 are much more likely to have ties than the P1 model predicts.
  • Activity Theory

    • The disengagement model suggests that it is natural for the elderly to disengage from society as they realize that they are ever nearer to death.
    • Five decades of gerontological research, however, suggest that the activity model is more accurate than the disengagement model .
    • Compare the activity model and disengagement model of aging, in terms of activity level and level of life satisfaction
  • CONCOR

    • The goodness of fit of a block model can be assessed by correlating the permuted matrix (the block model) against a "perfect" model with the same blocks (i.e. one in which all elements of one blocks are ones, and all elements of zero blocks are zeros).
    • For the CONCOR two-split (four group) model, this r-squared is .451.
    • That is, about 1/2 of the variance in the ties in the CONCOR model can be accounted for by a "perfect" structural block model.
    • The block model and its image also provide a description of what it means when we say "the actors in block one are approximately structurally equivalent."
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