| Almost all research in the social and behavioral sciences, and also in economic and marketing research, criminological research, and social medical research deals with the analysis of categorical data. Categorical data are quantified as either nominal or ordinal variables. This volume is a collection of up-to-date studies on modern categorical data analysis methods, emphasizing their application to relevant and interesting data sets.
Different scores on nominal variables distinguish groups. Examples known to everyone are gender, socioeconomic status, education, religion, and political persuasion. Other examples, perhaps less well known, are the type of solution strategy used by a child to solve a mental problem in an intelligence test and different educational training programs used to tesch language skills to eight-year old pupils. Because nominal scores only identify groups, calculations must use this information but no more; thus, addition and multiplication of such scores lead to meaningless results.
About the Author
Timo M. Bechger (timo.bechger@citogroep.nl) is affiliated to the Central Institute for Educational Measurement in Arnhem, the Netherlands. He has published about topics in aducational measurement, structural equation modelling, and behavior genetics. His involvement in psychometrics is of a more recent nature. |