Based on this data and on assumptions on willingness to pay and cost-outcome correlation, we constructed a model of principally achievable significance.
Throughout the research process, we based decisions regarding missing or unclear data on reasonable assumptions, but it is possible that measurement bias may have been introduced into the analysis, resulting in over- or under-estimates of the associations we found depending on the direction of the association in the misclassified trials [29].
So the researchers also analyzed the data on the assumption that only trips starting within a minute of each other could be combined.
In the "Results" section, we estimated the fault slip distribution of the 1703 Genroku event from paleo-shoreline data on the assumption that the mean sea level at 3 kyr BP relative to the present is 0 m.
In addition many authors construct phylogenetic trees from sequence data on the assumption that any tree based on genetic data is the 'true' evolutionary history of those organisms (e.g. [33] [35]).
Such measures are used as proxy for individual-level income data on the assumption that household incomes will be reasonably homogeneous within small enough residential areas.
The estimate from Marco et al. involved fitting FRAP data on the assumption that CAAX−containing proteins cannot exchange between membrane and cytoplasm.
The use of these models allows the analysis of all available data, on the assumption that data are missing at random, 28 conditional on adjustment for centre and observed baseline scores.
These models take account of the correlation between repeated measures on the same individual and allow for incomplete outcome data on the assumption that data are missing at random.
The analytical approached employed to synthesize results from these data relied on assumption that are arguably strong.
Instead, we usually analyse a clean data model based on assumptions about complete information, and later retro£t support for nulls.
