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Multidimensional scaling (MDS) is a generic term for a class of techniques or methods which attempt to construct a low-dimensional geometrical representation of the proximity matrix for a set of stimuli, with the goal of making any structure in the data as transparent as possible. The goal of all such techniques or method is to find a low-dimensional space in which points in the space represent stimuli, one point representing one stimulus, such that the distances between points in the space match as well as possible in some sense the original dissimilarities or the similarities. In a very common sense this simply means that the larger the observed dissimilarity value (or smaller the similarity value) amongs two stimuli, the further apart should be the points representing them in derived spatial solution. A common approach to finding the required coordinate values is to select them so as to minimize some least squares type fit criterion such as follows
It is the multivariate normal random vector which satisfies certain conditional independence suppositions. This can be viewed as a model framework which contains a wide range of st
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
Models which make use of the smoothing techniques such as locally weighted regression to identify and represent the possible non-linear relationships between the explanatory and th
Hosmer-Lemeshow test is a goodness-of-fit test taken in use in logistic regression, particularly when there are regular covariates. Units are spitted into deciles based on predict
The term used in a variety of methods in statistics, but mostly to refer to the categorical variable, with a less number of levels, under examination in an experiment as a possible
Continual reassessment method: An approach which applies Bayesian inference for determining the maximum tolerated dose in a phase I trial. The method starts by assuming a logistic
Latent class analysis is a technique of assessing whether the set of observations including q categorical variables, in specific, binary variables, consists of the number of diffe
R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also
This is given by common network e.g. Phone Company. The public networks are those networks, which are given by common carriers. It can be a telephone company or an other organizati
Observational study is the study in which the objective is to discover cause-and-effect relationships but in which it is not feasible to use the controlled experimentation, in th
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