The phrase "adjustment variable" is correct and usable in written English.
It can be used in contexts related to statistics, economics, or any field where variables are adjusted to analyze data or outcomes.
Example: "In our analysis, we identified the adjustment variable that significantly impacted the results of the experiment."
Alternatives: "modifying variable" or "tuning variable".
After adjustment on these same variables, very similar results were obtained in an analysis not considering weaning as a competing risk, but taking into account breastfeeding duration as an additional adjustment variable (less vs. more than 6 months): adjusted hazard ratio, 3.6 (95%CI, 1.3 10.0, p = 0.01).
When an explanatory variable lost its significance due to the adjusted analyses, we ran a series of regression analyses with each adjustment variable to examine which one resulted in the greatest change in the beta coefficient of the explanatory variable.
Daniel Vaughan-Whitehead, senior economist at the International Labour Office, adds: "There is a need to change the mentalities of suppliers in the sense that they may have the tendency to treat wages as the adjustment variable at the end of the chain, once they have paid other production costs".
These days, as everyone can see with Greece's economic troubles, the only adjustment variable is jobs.
In such situations, intensive daily travelling seems to be an adjustment variable between the individual's personal and professional lives.
In total, 3902 (85.9%) had records for each adjustment variable and were valid for multivariable analysis (Fig. 1).
Another risk-adjustment variable that contributed to a decrease in the HSMR is patient age at admission, which has increased over time (table 1).
Studies have highlighted the importance of gathering functional status data to facilitate its use as a prognostic or risk-adjustment variable.
In this article, we propose an approach to adjustment-variable selection which aims to produce well-adjusted estimates for a given research question based on plausible DAGs which are also consistent with the data at hand, and to clearly communicate assumptions and uncertainties underlying the estimates in DAG format.
Adjustment-variable selection in epidemiology can be broadly grouped into background knowledge-based and statistics-based approaches.
A potential criticism of the approach is that it does not eliminate background knowledge from adjustment-variable selection.
