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Multilevel models are the regression models for the multilevel or clustered data where units i are nested in the clusters j, for example a cross-sectional study where students are nested in schools or the longitudinal studies where measurement occasions are nested in subjects. In multilevel data responses are expected to be dependent or correlated even after the conditioning on observed covariates. Such dependence should be taken into account to ensure the valid statistical inference.
Multilevel regression models comprise random effects with the normal distributions to induce dependence among units belonging in the cluster. The simplest multilevel model is the linear random intercept model The multilevel generalized linear models or the generalized linear mixed models are multilevel models where random effects are introduced in linear predictor of generalized linear models. Additionally to linear models for the continuous responses, such type of models include, for instance, the logistic random effects models for dichotomous, ordinal and nominal responses and the log-linear random effects models for counts.
Multilevel models can also be specified for the higher-level data where units are nested in clusters which are nested in the superclusters. An instance of such a design would be measurement occasions nested in subjects which are nested in communities. Other terms sometimes used for the multilevel models include mixed models, random effects models hierarchical models, and random coeffiencnt models.
Method of moments is the procedure for estimating the parameters in a model by equating sample moments to the population values. A famous early instance of the use of the proced
stationary time series
Component bar chart : A bar chart which shows the component parts of the aggregate represented by the whole length of the bar. The component parts are shown as the sectors of bar w
Regression line drawn as y= c+ 1075x ,when x was2, and y was 239,given that y intercept was 11. Calculate the residual ?
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Lexis diagram is the diagram for displaying the simultaneous effects of the two time scales (generally age and calendar time) on a rate. For instance, mortality rates from cancer
Bubble plot : A method or technique for displaying the observations which involve three variable values. Two of the variables are used to make a scatter diagram and values of the t
Protopathic bias is the type of bias (also called as reverse-causality) that is a consequence of differential misclassification of the exposure related to timing of occurrence. It
The analysis of data which are the functions observed continuously, for instance, functions of time. Basically a collection of statistical techniques or methods for answering quest
Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular
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