In contrast, the latter use archived data and may be conducted off-line days or months after the data were collected; and they primarily improve power system analysis and planning, such as baselining, post-event analysis, and model calibration and validation.
Where there remain missing data, sensitivity analyses may be conducted using a range of assumptions where necessary, and consideration given to suitable imputation.
Where outcome data are non-normally distributed appropriate data transformations (eg logarithmic) may be conducted.
Further exploration of the data, through subgroup analysis, may be conducted but the results of such exploratory analyses may not be reliable As the number of available systematic reviews increases, it is becoming more common to find more than one systematic review for a particular policy question.
However, such meta-analyses can be considered when they are publicly available and, as stated in the "Preamble to the IARC Monographs," "ad-hoc calculations that combine data from different studies may be conducted by the Working Group during the course of a Monograph meeting" (IARC 2012).
Lastly, these results can be used as baseline data in future studies that may be conducted to further validate or improve the proposed models in different contexts.
However, in practice, MR investigations may be conducted with data from several studies, using either pooled data or a meta-analysis approach (17– 17).
In some research settings, CE may be conducted prior to data collection.
Completing each survey requires extensive field data collection and precise data analysis, which often limit the frequency with which surveys may be conducted.
This is an example of considerations that may be conducted through BIOWINE by analyzing phenotype and genomic data.
