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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.
What is a Generalized Linear Model? A traditional linear model is of the form where Yi is the response variable for the ith observation, xi is a column vector of explanator
Link functions: The link function relates the linear predictor ηi to the expected value of the data. In classical linear models the mean and the linear predictor are identical
Categorizing continuous variables : A practice which involves the conversion of the continuous variables into the series of the categories, which is common in the field of medical
This is the powerful visualization tool for studying how the response relies on an explanatory variable given the values of other explanatory variables. The plot comprises of a num
The scatter plots of SRES1, RESI1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plots sho
Concordant mutations test : A statistical test used in the cancer studies to determine whether or not a diagnosed second primary tumour is biologically independent of the original
The theory of measurement which recognizes that in any measurement situation there are multiple (actually infinite) sources of variation (known as facets in the theory), and that a
Incidental parameter problem is a problem which sometimes occurs when the number of parameters increases in the tandem with the number of observations. For instance, models for pa
Missing Data - Reasons for screening data In case of any missing data, the researcher needs to conduct tests to ascertain that the pattern of these missing cases is random.
Recurrence risk : Usually the probability that an individual experiences an event of interest given previous experience(s) of the event; for example, the probability of recurrence
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