scholarly journals Kimesurface representation and tensor linear modeling of longitudinal data

2022 ◽  
Author(s):  
Rongqian Zhang ◽  
Yupeng Zhang ◽  
Yuyao Liu ◽  
Yunjie Guo ◽  
Yueyang Shen ◽  
...  
Keyword(s):  
Longitudinal Data ◽  
Linear Modeling

How to Perform Idiographic and a Combination of Idiographic and Nomothetic Approaches

2010 ◽  
Vol 218 (3) ◽  
pp. 166-174 ◽  
Author(s):  
Michaela Schmidt ◽  
Franziska Perels ◽  
Bernhard Schmitz
Keyword(s):  
Time Series ◽  
Longitudinal Data ◽  
Hierarchical Linear Modeling ◽  
Self Regulation ◽  
Training Group ◽  
Group Level ◽  
Linear Modeling ◽  
Individual Level ◽  
Cross Correlations ◽  
Time Series Analyses

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.

Values Enactment in Organizations: A Multi-Level Examination

2008 ◽  
Vol 34 (4) ◽  
pp. 806-843 ◽  
Author(s):  
Melissa L. Gruys ◽  
Susan M. Stewart ◽  
Jerry Goodstein ◽  
Mark N. Bing ◽  
Andrew C. Wicks
Keyword(s):  
Longitudinal Data ◽  
Hierarchical Linear Modeling ◽  
Organizational Values ◽  
Work Life ◽  
Organizational Productivity ◽  
Linear Modeling ◽  
Individual Values ◽  
Multi Level ◽  
Low Levels

Business writers and practitioners recommend that core organizational values be integrated into employee work life for enhanced organizational productivity, yet no published studies have empirically examined the antecedents and outcomes of values enactment. Using longitudinal data on 2,622 employees, hierarchical linear modeling (HLM) results revealed that tenure and department-level values enactment were significant predictors of individual values enactment. Furthermore, employees who demonstrated high levels of values enactment were less likely to leave, and employees of high or low levels of values enactment in departments whose levels of values enactment matched their own were the most likely to be promoted.

The Relationship Between Leader–Member Exchange and Employees’ Proactive Behaviors

2019 ◽  
Vol 18 (2) ◽  
pp. 106-111
Author(s):  
Fong-Yi Lai ◽  
Szu-Chi Lu ◽  
Cheng-Chen Lin ◽  
Yu-Chin Lee
Keyword(s):  
Hierarchical Linear Modeling ◽  
Future Research ◽  
Leader Member Exchange ◽  
Voice Behavior ◽  
Linear Modeling ◽  
Team Members ◽  
Member Exchange ◽  
Multi Temporal ◽  
The Relationship ◽  
Practical Implications

Abstract. The present study proposed that, unlike prior leader–member exchange (LMX) research which often implicitly assumed that each leader develops equal-quality relationships with their supervisors (leader’s LMX; LLX), every leader develops different relationships with their supervisors and, in turn, receive different amounts of resources. Moreover, these differentiated relationships with superiors will influence how leader–member relationship quality affects team members’ voice and creativity. We adopted a multi-temporal (three wave) and multi-source (leaders and employees) research design. Hypotheses were tested on a sample of 227 bank employees working in 52 departments. Results of the hierarchical linear modeling (HLM) analysis showed that LLX moderates the relationship between LMX and team members’ voice behavior and creative performance. Strengths, limitations, practical implications, and directions for future research are discussed.

Loglinear Models for Longitudinal Data: Prospects and Limitations

2001 ◽  
Vol 46 (5) ◽  
pp. 506-508
Author(s):  
Daniel A. Powers
Keyword(s):  
Longitudinal Data ◽  
Loglinear Models

Measures Collected on the USMA Class of 1998 as Part of the Baseline Officer Longitudinal Data Set (BOLDS)

2002 ◽  
Author(s):  
Lynn M. Milan ◽  
Dennis R. Bourne ◽  
Michelle M. Zazanis ◽  
Paul T. Bartone
Keyword(s):  
Longitudinal Data ◽  
Data Set
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