The most prevalent variables were related to nursing staff supply: quantity/intensity (17 times), quality (18) and skill mix (18).
From these runs, one might identify the Φ most prevalent variables in f i, i.e., the more likely activators/repressors of the gene in question.
The most prevalent variables in these models are patient/family involvement (13 times); problems and symptoms management (13), nursing work practice environment characteristics (12), assessment, planning and evaluation (8) and care continuity (8).
The most prevalent variables cut across the different categories of nursing-sensitive outcomes and include symptom management (22 times), skin integrity (17), falls (17), patient satisfaction (17), physical functional capacity (17), cognitive and psychosocial functional capacity (15), medication management (14), nosocomial infections (12) and ability to achieve appropriate self-care (11).
With these Φ most prevalent variables, the i t h row in the BioProbMatrix can be fixed with 1′ s in the corresponding columns of these variables and the rest fixed to 0, in order to find the most optimal polynomial models.
In the case that the number of most prevalent variables is less than Φ, several runs of the EA can be done; in each one of these runs, for the i t h row of the BioProbMatrix, one can fix to 1 the values for these variables while considering combinations of the other variables to be fixed to 1 and the rest of the variables fixed to 0, until we find best scored polynomial models.
For certain variables, the most prevalent way of reporting was used for the analyses (for example, mean TBSA instead of median TBSA).
To evaluate shared characteristics of PRL-induced carcinomas, in a preliminary study we examined the transcript profiles of six NRL-PRL carcinomas, including three each of the most prevalent histotypes (glandular and papillary), expressing variable levels of ERα (three positive, three negative by IHC, not associated with histotype).
Participants reporting pain limiting work ability as compared to participants who rated no pain were used to operationalise our binomial-dependent variables when regressing independent variables as potentially associated for the most prevalent regions.
Common variable immunodeficiency (CVID) is the most prevalent primary immunodeficiency, and predominantly affects adults.
The algorithm identifies the top 200 most prevalent covariates within each data dimension by creating binary variables for each diagnosis, procedure and medication.
