The phrase "all errors of treatment" is correct and usable in written English.
It can be used in contexts discussing mistakes or issues related to a specific treatment, often in medical or therapeutic settings.
Example: "The report highlighted all errors of treatment that occurred during the patient's care, emphasizing the need for improved protocols."
Alternatives: "all treatment mistakes" or "any treatment errors".
This would require standard errors of treatment differences within studies, which generally were not given.
If some results appear unusual then it is of course appropriate to check these for errors; in particular if estimates and standard errors of treatment effects have been confused with other quantities then the results from the meta-analysis will be erroneous.
This is reinforced by the fact that standard errors of treatment-biased change estimates ignore the presence of degradation and deforestation activities and thus remain small due to the pronounced correlation between plot values on successive occasions.
We consider the relative efficiency (estimate divided by its standard error) of treatment effects derived from the DSM, the generic QOL, the generic QOL indirectly estimated from the mapped DSM, and a pooled estimate combining the direct and indirect information on the generic QOL.
One electronic transfer error of treatment parameters from the treatment planning system was reported.
Since unbalance of an omitted covariate, which in the present study is the between-cluster effect of the covariate γB in the ordinary multilevel model, can result in increased standard errors of the treatment effect, the distributions of the estimated standard errors of this parameter were inspected.
This will ensure that estimated standard errors of the treatment effect will be adjusted for the cluster effects.
However, the standard errors of the treatment effect are unbiased, whether the different within- and between-cluster effects are ignored or not.
If the original trial analyses had not adjusted for clustering, we planned to adjust the results for clustering by multiplying the standard errors of the treatment effect by the square root of the design effect.
