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In the analysis of multivariate observations designed to assess subjects with respect to an attribute, a Guttman scale (named after Louis Guttman) is a single (unidimensional) ordinal scale for the assessment of the attribute, from which the original observations may be reproduced. The discovery of a Guttman scale in data depends on their ...
The well known Guttman scale [25] [24] (example: 1111, 1121, 1131, 2131, 2231, 2232) is simply a 1-d scalogram, i.e. one all of whose profiles are comparable. The procedure of identifying and interpreting the coordinate scales X 1 ...
Guttman research interests were in the fields of scale and factor analysis, multidimensional scaling and facet theory. [4] His mathematical and philosophical treatments of Factor analysis are among the important parts of his scientific legacy. His earlier work in scaling analysis produced what has become to be known as the Guttman scale. [5]
The item-total correlation approach is a way of identifying a group of questions whose responses can be combined into a single measure or scale. This is a simple approach that works by ensuring that, when considered across a whole population, responses to the questions in the group tend to vary together and, in particular, that responses to no individual question are poorly related to an ...
The Bogardus social distance scale is a cumulative scale (a Guttman scale), because agreement with any item implies agreement with all preceding items. Research by Bogardus first in 1925 and then repeated in 1946, 1956, and 1966 shows that the extent of social distancing in the US is decreasing slightly and fewer distinctions are being made ...
The polytomous Rasch model is generalization of the dichotomous Rasch model.It is a measurement model that has potential application in any context in which the objective is to measure a trait or ability through a process in which responses to items are scored with successive integers.
The sub-space found with principal component analysis or factor analysis is expressed as a dense basis with many non-zero weights which makes it hard to interpret. Varimax is so called because it maximizes the sum of the variances of the squared loadings (squared correlations between variables and factors).
The idea was that a regression analysis could produce a demand or supply curve because they are formed by the path between prices and quantities demanded or supplied. The problem was that the observational data did not form a demand or supply curve as such, but rather a cloud of point observations that took different shapes under varying market ...