Quality & Quantity

, 41:869 | Cite as

Investigating the Number of Non-linear and Multi-modal Relationships Between Observed Variables Measuring Growth-oriented Atmosphere

Article

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.

Keywords

categorical data survey data non-linear modeling structural equation modeling organizational atmosphere 

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Copyright information

© Springer Science + Business Media B.V. 2006

Authors and Affiliations

  • P. Nokelainen
    • 1
  • T. Silander
    • 2
  • P. Ruohotie
    • 1
  • H. Tirri
    • 3
  1. 1.Research Centre for Vocational EducationUniversity of TampereHämeenlinnaFinland
  2. 2.Helsinki Institute for Information TechnologyComplex Systems Computation GroupHUTFinland
  3. 3.Nokia Group, Nokia Research CenterNokia GroupFinland

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