A primary prerequisite for conducting a comparative study is clearly the standardisation of underlying data collection methods, assumptions, definitions, and data in order to avoid inconsistencies.
The overall methodology used for WTW analysis of sorghum-based ethanol pathways can be divided into three main steps: definition of the system boundary of our WTW analysis, as shown in Figure 1; data collection and parametric assumptions; and configuration and expansion of sorghum-based ethanol pathways with GREET.
We aim to achieve registration of more than 1000 ICSD patients and complete follow-up data collection, with the assumption of a 5 10% incidence of E-storms during the 2-year follow-up.
Since there was no consistent trend in the ratio between low, medium, and high wood density sites within the data collection region, an assumption was made that the ratios would be applicable to stems located at all 17 sites.
The self-administered questionnaire was distributed to study subjects through the facilitators of data collection with an assumption of getting back in a week time.
After scientists locate the data of interest, personal conversation and discussion with the original data producer(s) or collector(s), if possible, are always helpful by revealing first-hand information and subtle details of the data collection, including the fundamental assumptions, processing history, and native context that are essential for rigorous research inquiries.
We extracted the following information from the included studies: study population; accelerometry data collection methods and accelerometry analysis assumptions including valid day criteria; cut-points; and any other relevant assumptions reported.
Problems of constructing a sediment budget for an inlet is often a challenge due to constraints on data collection, quality of data, and assumptions one is willing to consider.
Modeling a river experiences varied and inescapable irregularities in data collection resulting in making the assumptions in the model parameters leading to the magnification of the errors in the model outputs.
Each data source has unique assumptions and data collection and processing methodology.
