Multilevel models are statistical models of parameters that vary at more than one level. An example could be a model of student performance that contains...

Multilevel regression with poststratification (MRP) is a statistical technique used for correcting model estimates for known differences between a sample...

Snijders, Bosker, T.A.B, R.J (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling. Vol. 2nd edition. London:Sage.{{cite...

One application of multilevel modeling (MLM) is the analysis of repeated measures data. Multilevel modeling for repeated measures data is most often discussed...

the U.S. Department of Defense (DoD) multilevel security (MLS) policy. The model is a formal state transition model of computer security policy that describes...

of X on a given individual. GLMMs are also referred to as multilevel models and as mixed model. In general, fitting GLMMs is more computationally complex...

econometrics, a random effects model, also called a variance components model, is a statistical model where the model parameters are random variables...

In statistics, a probit model is a type of regression where the dependent variable can take only two values, for example married or not married. The word...

multi-group modeling, longitudinal modeling, partial least squares path modeling, latent growth modeling and hierarchical or multilevel modeling. SEM researchers...

generalized logistic function in epidemiological modeling is its relatively easy application to the multilevel model framework, where information from different...

In statistics, a logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent...

professor who spent 40 years researching and teaching the pitfalls of multilevel marketing": "You'd be hard-pressed to find anyone making over $1.50 an...

In statistics, an errors-in-variables model or a measurement error model is a regression model that accounts for measurement errors in the independent...

entries of the covariance matrix of the errors, are null. The fit of a model to a data point is measured by its residual, r i {\displaystyle r_{i}} ...

Multilevel security or multiple levels of security (MLS) is the application of a computer system to process information with incompatible classifications...

The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy...

class of linear unbiased estimators, if the errors in the linear regression model are uncorrelated, have equal variances and expectation value of zero. The...

Christian B. (2007). "Generalized Least Squares Inference in Panel and Multilevel Models with Serial Correlation and Fixed Effects". Journal of Econometrics...

1214/aos/1176343056. JSTOR 2958945. Goldstein, H. (1986). "Multilevel Mixed Linear Model Analysis Using Iterative Generalized Least Squares". Biometrika...

problems, i.e. with more than two possible discrete outcomes. That is, it is a model that is used to predict the probabilities of the different possible outcomes...

between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a...

marginal models (Heagerty & Zeger, 2000) are a technique for obtaining regression estimates in multilevel modeling, also called hierarchical linear models. People...

effects model is a statistical model in which the model parameters are fixed or non-random quantities. This is in contrast to random effects models and mixed...

Tikhonov) is a method of estimating the coefficients of multiple-regression models in scenarios where the independent variables are highly correlated. It has...

In statistical modeling, regression analysis is a set of statistical processes for estimating the relationships between a dependent variable (often called...

descriptions of redirect targets Layer (disambiguation) Multilevel model – Type of statistical model Multitree – Directed acyclic graph with ≤1 directed paths...

Andrew Gelman proposed a different approach of ANOVA, viewed as a multilevel model. Let us imagine a data set for which a dependent variable may be influenced...

general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models. In that...

the alternative: a score-based approach with application to segmented modelling" (PDF). Journal of Statistical Computation and Simulation. 86 (15): 3059–3067...

data structures such as multilevel data. A complete overview of the latent Markov models, with special attention to the model assumptions and to their...