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 Prof Karl Joreskog at the 1998 Dallas workshop

Analysis of Ordinal Variables Part 3: Longitudinal Data


Karl G. Joreskog

December 12, 2001

Because of the mathematical content and length of this contribution to Karl's Corner, we are only making it available as a PDF file. It can then be printed using Adobe's Acrobat Reader (version 4 and higher).

The zip file contains both the PDF file and examples (input files and datasets).

The contents of this column are briefly described below.

Many papers have considered the specification of models incorporating causation and measurement errors in the analysis of data from panel studies, and statistical models and methods for the analysis of longitudinal data.

The characteristic feature of a longitudinal design is that the same measurement instruments are used on the same people at two or more occasions. The purpose of a longitudinal design or panel study is to assess the changes that occur between the occasions, and to attribute these changes to certain background characteristics and events existing or occurring before the first occasion and/or to various treatments and developments that occur after the first occasion. Often, when the same variables are used repeatedly, there is a tendendency for the measurement errors in these variables to correlate over time because of specific factors, memory or other retest effects. Hence there is a need to consider models with correlated measurement errors.

The analysis of ordinal variables in longitudinal studies requires special techniques and procedures (available in LISREL 8.51) which are different from those used with continuous longitudinal variables. This contribution by Karl illustrates these techniques and procedures using the Political Action Panel Study for the USA which is a two-wave panel study. The original USA sample consisted of 1719 cases interviewed in 1974. Five years later 933 of these cases were re-interviewed using the same six political efficacy items that were analyzed in part two of the series.

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