Titlebook: Sociometric Research: Vol.2: Data Analysis; Willem E. Saris (Professor of Social Science Metho Book 1988 Palgrave Macmillan, a division of

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Time Series Analysis with Intervention Effects: Method and Application or identification phase we end up with a model that is able to describe the regularities in the time series. Before the central theme of the chapter is brought up, the principles of this approach will be discussed briefly. First, should we analyse the plain series, the series of changes, or should

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Artifacts in Mail Surveys: the Influence of Dillman’s Total Design Method on the Quality of the Resphe efficacy of the TDM has been concerned with the response rate. Using the TDM Dillman (1978, p. 27) reports an average response rate of 70 per cent for samples from the general population of the United States. There is some evidence for the cross-cultural usefulness of the TDM. For instance, in Th

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Explanatory Analysis of Scientific Theoriesd delineate the original problem situation, the various attempts to cope with it (including erroneous trials), the way the adopted solution was tested and its actual or expected influence on future developments. Very few historical studies perform all the preceding tasks; and Popper, for example, he

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LCAG — Loglinear Modelling with Latent Variables: a Modified LISREL Approachath analysis approach’ (Goodman, 1972, 1975, 1973). As he pointed out, the loglinear techniques are not exactly identical with the classical regression techniques, but there is indeed a rather striking analogy between the two (see also Brier, 1979). As such, these phrases were very aptly chosen. The

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Loglinear Modelling with Latent Variables: the Case of Mobility Tableswith latent variables will be presented. The methodology is embedded in the latent structure analysis, developed by Paul F. Lazarsfeld (Lazarsfeld, 1950a, 1950b, 1954, 1959; Lazarsfeld and Henry, 1968). Besides Lazarsfeld’s and Clogg’s work, papers by Leo Goodman (1974a, 1974b), Jacques Hagenaars (1

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On the Problem of Endogenous Measurement Errorm one state to another. Moreover, often part of the explanatory variables are measured subjectively, for lack of objective assessments. It may happen then, that the reported perceptions and opinions from which the subjective scales are constructed are biased towards the alternative which a responden