Investigating the Number of Non-linear and Multi-modal Relationships Between Observed Variables Measuring Growth-oriented Atmosphere |
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Authors: | P Nokelainen T Silander P Ruohotie H Tirri |
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Institution: | 1.Research Centre for Vocational Education,University of Tampere,H?meenlinna,Finland;2.Helsinki Institute for Information Technology,Complex Systems Computation Group,HUT,Finland;3.Nokia Group, Nokia Research Center,Nokia Group,Finland |
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Abstract: | This study investigates the number of non-linear and multi-modal relationships between observed variables measuring the Growth-oriented
Atmosphere. The sample (N = 726) represents employees of three vocational high schools in Finland. The first stage of analysis showed that only 22%
of all dependencies between variables were purely linear. In the second stage two sub samples of the data were identified
as linear and non-linear. Both bivariate correlations and confirmatory factor analysis (CFA) parameter estimates were found
to be higher in the linear sub sample. Results showed that some of the highest bivariate correlations in both sub samples
were explained via third variable in the non-linear Bayesian dependence modeling (BDM). Finally, the results of CFA and BDM
led in different substantive interpretations in two out of four research questions concerning organizational growth. |
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Keywords: | categorical data survey data non-linear modeling structural equation modeling organizational atmosphere |
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