The phrase "analysis to control for" is correct and usable in written English.
It is typically used in research contexts to indicate that an analysis is being conducted while accounting for certain variables or factors that may influence the results.
Example: "In our study, we performed an analysis to control for demographic variables that could affect the outcomes."
Alternatives: "analysis to account for" or "analysis to adjust for".
Even when they adjusted their analysis to control for age, gender, socioeconomic status, race, and overall health, they found that those with mild to severe smell loss had been more likely to die.
Regression analysis to control for the effect of length of distraction was conducted to examine the effects of other variables.
In our analysis, to control for possible differences in health conditions, we include the full diagnosis vector.
Variables such as birth interval, low birth weight, incidence of acute respiratory infection (ARI), and diarrhea are included in the analysis to control for the maternal/child confounders.
In the ensuing subsection, we explore the robustness of our findings by extending our DD analysis to control for other potential confounding factors.
The role of FA in improving the accuracy of treatment maps was evaluated using logistic regression analysis to control for different observers, different cases, and different posterior pole characteristics.
Health-related quality of life (HRQoL) for responders and non-responders was estimated by modelling EQ-5D™ index data from PREVA in an ordinary least squares regression analysis to control for potential imbalances at baseline between treatment arms.
We now expand on the descriptive analysis in the previous section by using regression analysis to control for other socioeconomic characteristics that are related to the likelihood that individuals are retired and may also systematically differ by country of origin.
We also include instructor in the student analysis to control for variation among student OTL responses due to the individual instructors, rather than measured aspects of the class related to the instructor, such as the instruction methods.
This amounts to clustering instructors by institution in the analysis to control for potential additional unmeasured characteristics of the Calculus I course structure at institutions that is related to instructor perception of OTL.
Cohort was used as a covariate in statistical analysis to control for possible differences between cohorts.
