Optimal Matching Analysis in Career Research: A Review and Some Best-practice Recommendations

@article{Dlouhy2015OptimalMA,
  title={Optimal Matching Analysis in Career Research: A Review and Some Best-practice Recommendations},
  author={Katja Dlouhy and Torsten Biemann},
  journal={Journal of Vocational Behavior},
  year={2015},
  volume={90},
  pages={163-173}
}
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The authors apply optimal matching techniques to class careers from age 15 to age 35 for two moderately large samples, as a means of exploring the utility of this sequence-oriented approach for the
Beyond Transitions: Applying Optimal Matching Analysis to Life Course Research
TLDR
An analytic strategy is introduced that allows assessing the classification’s internal validity and produced a classification with better fit than straightforward CA, suggesting passages into adulthood have become more diverse since the 1970s.
Optimal Matching Analysis and Life-Course Data: The Importance of Duration
TLDR
A modified version of the optimal matching algorithm is proposed, weighting OM’s elementary operations inversely with episode length, and it is found that where all the sequences in a data set consist of few long spells, and there is low variability in the number of spells, the modified algorithm generates an overall pattern of distances that is not very different from standard OM.
Optimal Matching Analysis: A Methodological Note on Studying Career Mobility
This article explores how Optimal Matching Analysis (OMA) can be applied to study career mobility. I first apply OMA to career history data to identify typical mobility paths. Then I test whether the
Is Optimal Matching Suboptimal?
TLDR
The author identifies a flaw in OM ‘‘indel costs’’ and proposes a solution to this flaw, and conducts an empirical test of traditional OM, the alternative localized OM, and sequence comparison.
Sequence Analysis and Optimal Matching Methods in Sociology
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Career patterns of top management team members in five countries: an optimal matching analysis
This paper introduces optimal matching analysis (OMA) to the field of top management research. With this method, we develop six career patterns of top management team (TMT) members from five
Career Patterns of Executive Women in Finance: An Optimal Matching Analysis1
This article examines the objective and subjective facets of female finance‐executive careers. Optimal matching and qualitative analyses are used to show how the careers are shaped by workplace
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