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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 first threshold of item i, , is the location on the continuum at which a person is equally likely to obtain a score of 0 or 1, the second threshold is the location at which a person is equally likely to obtain a score of 1 and 2, and so on. In the example shown in Figure 1, the threshold locations are −1.5, −0.5, 0.5, and 1.5 respectively.
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 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 ...
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 ...
Moreover, while Mokken scaling analysis is a confirmatory method, meant to test whether a number of items form a coherent scale (like confirmatory factor analysis), an Automatic Item Selection Procedure has been developed to explore which latent dimensions structure responses on a number of observable items (like factor analysis). [17]
The Rasch model, named after Georg Rasch, is a psychometric model for analyzing categorical data, such as answers to questions on a reading assessment or questionnaire responses, as a function of the trade-off between the respondent's abilities, attitudes, or personality traits, and the item difficulty.
The aim of the PRISMA statement is to help authors improve the reporting of systematic reviews and meta-analyses. [3] PRISMA has mainly focused on systematic reviews and meta-analysis of randomized trials, but it can also be used as a basis for reporting reviews of other types of research (e.g., diagnostic studies, observational studies).