What can the Real World do for simulation studies? A comparison of exploratory methods

Bollmann, Stella; Heene, Moritz; Küchenhoff, Helmut und Bühner, Markus (14. April 2015): What can the Real World do for simulation studies? A comparison of exploratory methods. Department of Statistics: Technical Reports, Nr. 181

Abstract

For simulation studies on the exploratory factor analysis (EFA), usually rather simple population models are used without model errors. In the present study, real data characteristics are used for Monte Carlo simulation studies. Real large data sets are examined and the results of EFA on them are taken as the population models. First we apply a resampling technique on these data sets with sub samples of different sizes. Then, a Monte Carlo study is conducted based on the parameters of the population model and with some variations of them. Two data sets are analyzed as an illustration. Results suggest that outcomes of simulation studies are always highly influenced by particular specification of the model and its violations. Once small residual correlations appeared in the data for example, the ranking of our methods changed completely. The analysis of real data set characteristics is therefore important to understand the performance of different methods.

• Dokumententyp: Paper
• Keywords: Real World simulation, data set characteristics, simulation study, sample size
• Fakultät: Mathematik, Informatik und Statistik > Statistik ; Mathematik, Informatik und Statistik > Statistik > Technische Reports
• Themengebiete: 100 Philosophie und Psychologie > 150 Psychologie
• Sprache: Englisch