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We created four new variables, containing the tertiles of the benefit of completion in respect to employment after training, salary, occupational status, and further study.
The derivation of the benefit of completion described therein is based on two identical models modeling the benefit variable of interest (for instance 'employment after training') as a function of a number of predictors, such as sex, age group, location, field of education, qualification level, study status, socio economic status, employment status before training, and prior education.
Since "nonsentinel nodes" are almost never examined using serial sectioning and immunohistochemistry, we must assume that the frequency of involvement of nonsentinel nodes is greater than currently recognized and the yield (if not necessarily the benefit) of completion node dissection is almost surely underestimated.
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Although this research has identified a number of factors correlated with apprenticeship completion, further research could address the benefits of completion such as wages and probability of employment.
These results showing a relative lack of impact of the benefit to completion on the probability of completions were somewhat unexpected.
The results show that the impact of the benefit to completion is very limited, and in the area of a one percent impact on completion probability.
Only the benefit to completion in terms of further study is slightly more pronounced with about a three percentage point increase in completion probability between first and third tertile of the benefit to completion.
While there is a strong completion benefit in terms of further study (e.g. a completer is 125%% more likely to be in further study than a non-completer) and also employment after training and improved employment conditions (25%%), the benefit to completion in terms of salary and occupational status are rather diminutive.
Only the variable containing the benefit to completion in terms of further study has a more pronounced effect on completion as indicated by a predictive margin of one percentage point increase in completion probability between tertile 2 and 1 and a 3 percentage point increase between tertile 3 and 1.
Also it will be assessed what impacts can be expected (the real difference for the beneficiaries for each of the results areas, plus unintended positive or negative results if any) and sustainability (long-term benefits, continuation of generation of benefits after completion of the programmes).
Secondly, the way the variables indicating the benefit to completion are constructed means that they represent the overall benefit to completion, rather than the net benefit.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com