Consequently, based on a unifying vocabulary, this survey sheds light on (i) the weak and strong points of current approaches for modeling complex multidimensional structures that reflect real-world situations in a conceptual multidimensional model and (ii) existing mechanisms to avoid summarizability problems when conceptual multidimensional models are being implemented.
Note that the multidimensional models are so-called simple structure or between-item multidimensional models (e.g., Adams et al. 1997).
Two multidimensional models are widely accepted.
These findings argue that the current multidimensional models are not culturally sensitive to assess insight.
The correlation between the latent dimensions in the multidimensional models was 0.73.
However, even though a good conceptual multidimensional model is designed underneath a DW, there is a semantic gap between this model and its logical representation.
A multidimensional model is proposed, which supports the consistency verification, liveness and safety property verification, OCL constraints and LTL formula verification.
An overall multidimensional model was built by entering explanatory variables from each of the seven dimension models showing an association of p<0.20 with not working as independent variables.
Injury-related factors associated with increased odds of not working that remained in the overall multidimensional model were: those workers who perceived their injury was a threat to their life and those who were admitted to hospital following their injury.
The most important pre-injury predictors of not working following injury found by multidimensional modelling were as follows: low or unknown income, financial insecurity, physical work tasks, temporary employment, long week schedules, obesity, perceived threat to life and hospital admission.
