"outcome distribution" is a correct and usable phrase in written English.
It describes the way in which different possible outcomes are distributed or spread out in a certain situation or context. It can be used in various fields, such as statistics, economics, and psychology, to discuss the likelihood or distribution of different results. Example: "The study analyzed the outcome distribution of different treatments for depression and found that cognitive-behavioral therapy had the most positive outcomes for the majority of participants."
This approach estimating associations along outcome distribution also allows us to describe distributional outcome changes associated with increasing exposure.
However, the reasoning inherent in the GSLC tool focuses on the practical problem of determining the outcome distribution of DNA fragments in general.
Let (psi ^{(t)}=prod _{i=1}^{K} Phi _{i}^{(t)}) denote the outcome distribution at time t and (psi =frac {1}{T}sum _{t=1}^{T} psi ^{(t)}), the time averaged history of these distributions.
This approach directly accounts for the greater opportunity for significant variation over longer intervals and thus maximizes safety while keeping the glycemic outcome distribution best aligned in the desired range to maximise the opportunity for outcome BG in that range.
Disadvantageous inequity aversion (IA) is a behavioural response to an inequitable outcome distribution yielding a smaller reward to oneself than to a conspecific, given comparable efforts to obtain the reward.
Overall, these findings underscore the importance of gene-gene and gene-environment interactions in shaping the genetic architecture of BMI and advance a method for detecting such interactions by using only the sample outcome distribution.
The outcome distributions are sufficiently skewed that, even with large numbers of projects, it is not possible to diversify away substantial residual variability through portfolio strategies.
The channels through which the forcing variable affects the potential outcome distributions are constrained to be minimal, to preserve the nonparametric feature of the RD design.
But a more detailed investigation is advisable since the outcome distributions varied significantly across different datasets.
Gamble outcome distributions ensured that all subjects received equal exposure to all gambles and experienced identical outcomes at the indicated probabilities before reporting their affective responses and preferences at the end of the experiment.
Outcome distributions were examined prior to modeling.
