What does CVR stand for in regression diagnostics?

What does CVR stand for in regression diagnostics?

• A. Covariance ratio (CVR)
• B. Covariate
• C. Cox and Snell's
• D. Cramér's V

Answer: (A)

Covariance ratio is what CVR stands for in regression diagnostics. It measures how much a single data point changes the precision of the estimated coefficients by comparing the covariance matrix of the coefficient estimates with and without that observation. In practice, you look at how removing that point alters the determinant of the covariance matrix of the estimates; a value close to 1 means little impact, while a value noticeably different from 1 indicates that the observation is influential on the stability of the regression estimates. This concept is distinct from a covariate, which is simply a predictor variable in the model, and from Cox and Snell's or Cramér's V, which are different statistics (pseudo R-squared and a measure of association for categorical variables, respectively).

Covariance ratio is what CVR stands for in regression diagnostics. It measures how much a single data point changes the precision of the estimated coefficients by comparing the covariance matrix of the coefficient estimates with and without that observation. In practice, you look at how removing that point alters the determinant of the covariance matrix of the estimates; a value close to 1 means little impact, while a value noticeably different from 1 indicates that the observation is influential on the stability of the regression estimates.

This concept is distinct from a covariate, which is simply a predictor variable in the model, and from Cox and Snell's or Cramér's V, which are different statistics (pseudo R-squared and a measure of association for categorical variables, respectively).