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The method or technique for producing the sequence of parameter estimates that, under the mild regularity conditions, converges to maximum likelihood estimator. Of particular significance in the context of the incomplete data problems. The algorithm comprises of two steps, called as the E, or Expectation step and the M, or the Maximization step. In the previous, the expected value of log-likelihood conditional on the observed data and the current estimates of parameters are found. In the M-step, the function is maximized to provide the updated parameter estimates which increase the likelihood. The two steps are alternated until the convergence is attained. The algorithm might, in some cases, becoms very slow to converge. This is acronym for the Epidemiological, Graphics, Estimation and Testing of the program developed for the analysis of the data from studies in epidemiology. It can be made in use for logistic regression and models might include random effects to permit over dispersion to be modelled. The beta- binomial distribution can be fitted.
Nuisance parameter : The parameter of the model in which there is no scienti?c interest but whose values are generally required (but in usual are unknown) to make inferences about
The diagnostic tools or devices used to approach the closeness to the linearity of the non-linear model. They calculate the deviation of so-called expectation surface from the plan
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
Normality - Reasons for Screening Data Prior to analyzing multivariate normality, one should consider univariate normality Histogram, Normal Q-Qplot (values on x axis
Bayes factor : A summary of evidence for the modelM1 against the another modelM0 provided by the set of data D, which can be used in the model selection. Given by the ratio of post
The rapid development or growth of the disease in a community or region. Statistical thinking has made very much significant contributions to the understanding of such type of phen
Data which occur when failure period is recorded which are dependent. Such type of data can arise in number contexts, for instance, in epidemiological cohort studies in which th
Poisson regression In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regre
You have learned that there are 3 major central measures of any data set. Namely: mean, median, and mode. Which of the three, do the outliers affect the most?
Quasi-experiment is a term taken in use for studies which resemble experiments but are weak on some of the characteristics, particularly that allocation of the subjects to groups
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