The phrase "adjustment and confounding" is correct and usable in written English.
It can be used in contexts related to statistics, research, or data analysis, particularly when discussing the need to control for confounding variables in an analysis.
Example: "In our study, we must consider both adjustment and confounding to ensure the validity of our results."
Alternatives: "control for confounding" or "manage confounding factors".
Regression models allow for adjustment of trends and confounding.
There is potential for prognostic studies to produce conflicting results because of inaccuracy in the measurement of patient characteristics, inadequate measurement of and adjustment for confounding, and lack of power [ 18, 19].
Firstly, the large sample size gives robust results and allowed considerable adjustment for confounding and mediating factors.
Our study has several strengths, including a prospective design; verifiable, independent and robust outcome; evidence of a clear effect both before and after adjustment for confounding variables; and a suitable rate of intervention by MET.
Table 2 presents the association between preeclampsia status and independent variables with no adjustment and with adjustment for confounding variables.
Children born after ART, however, were significantly more likely to have asthma at both 5 and 7 years of age and adjustment for confounding factors strengthened the observed association.
‡Seasonality with phase I data coded as Summer and phase 2 data coded as Winter was entered as a covariate, and adjustment for confounding factors including socio-demographics, health status, chronic morbidity and lifestyle (Additional file 1).
Methodological problems that compounded the difficulties in interpretation and generalisability of study findings included selection biases and use of non-representative samples, idiosyncratic outcome measures, inadequate adjustment for confounding, and the prevailing medico-legal or compensation context.
But previous studies have incorporated only limited adjustment for confounding and mediating factors such as income, access to services and health status.
These effects remained even after adjustment for confounding and mediator variables, whereas associations between neighbourhood unemployment rate and T2DM in women were dissolved by the introduction of confounding variables.
