The phrase "adequate whereas" is not correct and does not convey a clear meaning in written English.
It is typically used to compare two contrasting ideas or situations, but "adequate" does not fit well with "whereas" in this context.
Example: "The resources provided were adequate, whereas the training was lacking."
Alternatives: "sufficient while" or "acceptable although".
Interestingly, the majority (i.e. 70%%) of third years felt that this was adequate, whereas 68%% of fifth year students stated this was too little.
We conclude that ART1 is not adequate, whereas SOM provide completely satisfactory results including visually effective representation of spatial failure probability of the pattern classes.
They observed that for a 4-storied building, a SCWB factor of 1.2 is adequate, whereas for a 12-storied building the building performance continues to improve up to a SCWB ratio of 3, and therefore, suggested a dependency of the SCWB ratio on the building height, too.
Also, CFI and TLI values were adequate, whereas RMSEA values were less satisfactory.
For malignant lesions, a positive FNAC result is generally considered adequate, whereas 2 FNACs obtained on 2 separate occasions are required before treating benign thyroid nodules.
The difference is clinically relevant since functional SAKI can be reversed completely by early adequate treatment whereas structural kidney damage will mostly require RRT.
An IFI/CFI ≥ .90 and RMSEA ≤ .10 indicated adequate fit, whereas an IFI/CFI ≥ .95 and RMSEA ≤ .06 indicated a good model fit (Byrne, 2006).
First, Kuhn thought that incommensurability was a matter of there being no fully adequate translation whereas Quine's thesis involved the availability of multiple translations.
Young dogs were fed ad libitum to allow for adequate growth, whereas senior dogs were fed a restricted amount of the diet to maintain baseline body weight throughout the experiment.
Patients with four correct responses or more are considered as having adequate literacy whereas fewer than four correct answers indicate low literacy.
Values under 0.06 suggest close approximate (adequate) fit, whereas values above 0.10 indicate poor fit and that the model should be rejected [ 71, 76].
