摘要：The aim of the study is to combine and compare person-oriented and nomothetic approaches to analyze longitudinal data with time series analyses and hierarchical linear modeling (HLM). Based on the evaluation of an intervention study both approaches were used to compare individual and group data. In this study, a training was implemented to foster students’ self-regulation and selected results were presented at the individual and group level for the variables planning and motivation. To analyze data with time series analysis, cross-correlations and trend analyses were conducted. Cross-correlations revealed similar results on the aggregated and individual level whereas trend analysis indicated different results of these two levels. Results of HLM analyses for longitudinal data suggested that students’ motivation has more influence than the type of training group on students’ planning. The findings demonstrate that individual and group-level results differ and that both methods have different focuses. This means that it is useful to combine time series analyses and HLM approaches when analyzing longitudinal data. Keywords: time series analysis , hierarchical linear modeling , self-regulation training
关键词：time series analysis; hierarchical linear modeling; self-regulation training
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