Abstract
Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Betriebswirtschaft > Institut für Marketing |
Themengebiete: | 300 Sozialwissenschaften > 330 Wirtschaft |
ISSN: | 8756-9728 |
Sprache: | Englisch |
Dokumenten ID: | 95544 |
Datum der Veröffentlichung auf Open Access LMU: | 31. Mrz. 2023, 07:59 |
Letzte Änderungen: | 31. Mrz. 2023, 07:59 |