Statistics III

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The goal of this course is twofold. On the one hand, it supplements Statistics II; that is the analysis of two-way designs with a dichotomous instead of quantitative dependent variable. On the other hand, the emphasis lies on the analysis of tests and questionnaires. In this way, this course provides a solid statistical preparation for the course Psychodiagnostics. The course includes three techniques spanning several weeks: logistic regression, reliability analysis and factor analysis. Logistic regression is the cognate of the variance and regression analysis covered in Statistics II if the dependent variable is dichotomous instead of continuous, such as recovery from disease or passing an exam. Logistic regression allows us to adjust the effects of multiple independent variables for each other (confounding) and to study interactions. In this way, it also expands upon the contingency table analysis from Statistics I to multiple independent variables. Reliability analysis is a classical psychometric method for analysing tests and questionnaires. Oftentimes, persons' answers to multiple- choice questions (items) are scored logically and tallied to give a total score for e.g. intelligence or attitude. In doing so, one assumes that these items measure the same thing. Reliability analysis can verify whether each item fits into the scale and how reliable the total score is. The course offers training in classical psychometrics and an introduction into modern psychometrics (the Rasch model), validity, and agreement between evaluators. Factor analysis is a method used to reduce a multitude of variables to a small number of underlying factors. In the past, factor analysis was used to reduce the scores on various tests to a small number of dimensions, such as verbal and spatial intelligence, or extraversion and neuroticism. Nowadays, factor analysis is more often used to group items of one questionnaire into sub-scales. Factor analysis is thus related to psychometrics. The course offers training in exploratory factor analysis with SPSS.