The presence of a confounding factor will lead to failure of which of the critical assumptions used to justify claiming your estimates consistently estimate a causal effect?
A) The determining function is linear in parameters.
B) The sample is a random sample from the population.
C) The errors will be homoscedastic.
D) The model's error terms and the treatments will all be uncorrelated.

Question

Quizplus · Accepted Answer

The presence of a confounding factor, which is a variable that is associated with both the treatment and outcome, means that the model's error terms and treatments are no longer uncorrelated. This violates the critical assumption that the model's error terms and treatments are uncorrelated, which is necessary for consistently estimating a causal effect. The other critical assumptions (linear determining function, random sample, and homoscedastic errors) may still hold in the presence of a confounding factor.

The Presence of a Confounding Factor Will Lead to Failure