"is confounded with" is correct and can be used in written English.
You can use it when you want to say that two things, people, or ideas are confused or complicated together. For example, "The statistics often used for the coronavirus are confounded with other health issues such as flu and colds."
With such a design, stimulus repetition is confounded with expectation.
Further, the subset selection bias is confounded with the subset-specific treatment effect, and the two components are not identifiable without additional untestable assumptions.
In sum, as appreciation of curvature changes dynamically over time, any study aiming to find static and general principles of liking regarding curvature is confounded with Zeitgeist effects.
Everyone knows he collaborated with Charles Barry on the Houses of Parliament, but his precise contribution is confounded with the other architect's, and was to be the subject of unseemly disputes between their sons after both were dead.
However, controlling for a variable that is confounded with rule at the individual-subject level but not the group level (reaction time differences across rules) eliminates the MVPA results.
In many paradigms, the difficulty of a task is confounded with whether there is an opportunity for rehearsal.
If the distributions do not have equal variances, then d′ is confounded with response bias and should not be used.
Second, the object that is held during training is confounded with the training itself; participants held a ball and watched or held a simulated weapon and played.
The other side of the argument is that diagnosticity is confounded with witnesses' tendency to identify someone; that is, to "choose" from the lineup (e.g., Wixted & Mickes, 2012).
Crucially, recent research has demonstrated that diagnosticity is confounded with witnesses' willingness to identify a suspect, raising questions about the validity of prior conclusions about the effects of system and estimator variables.
Indeed, one should not do so, because d′ is confounded with response bias whenever the underlying evidence distributions have unequal variance, as is consistently observed in recognition memory judgments (e.g., Ratcliff, Gronlund, & Sheu, 1992).
