Abstract of a paper at "Large Scale Data Analysis" International Conference, Cologne, Germany, 1999.
As my data set I have chosen 9 items concerning job satisfaction from a 1989 study. The aim is to fit a rating scale model, or equivalently a polytomous Rasch model with equidistant scoring of the response categories, to these data. This would allow us to scale the individuals on a latent scale representing job satisfaction.
The mentioning of Georg Rasch in the title refers partly to the fact that I shall try to analyze the data - although not by the methods he used - then by methods, which are modern versions of his way to explain data structures. But it is also a reflection of my nostalgia over the fact that my dissertation in 1973 used as its data illustrations a Danish study of job satisfaction, which I had partly worked on together with Georg Rasch. ...
From a methodological point of view, the most important contribution is to show, how analyses of goodness of fit, and other analyses of the data, can be carried out by graphs, for example, showing the variation of standardized residuals, where traditionally one would rely on statistical tests, or studying multiplicative structures by convenient graphs. Thus there will be few tables and also no test quantities, but an abundance of graphs. This is also to pay tribute to the methods used by Georg Rasch, who always held the view, that statistical tests were "destructive" and graphical methods "constructive".
As a last connection to the work of Georg Rasch, I shall show how he arrived at Leo Goodman's RC-association model around 1965, from the polytomous Rasch model. I shall use this formulation of the RC-association model to throw further light on the data structure under consideration. In particular on the appropriateness of an equidistant scoring of the response categories.
Georg Rasch in Memoriam: a discovery journey into a data set. Andersen E. Rasch Measurement Transactions, 2001, 15:1 p.803
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