Survey response rates for modern surveys using many different modes are trending downward leaving the potential for nonresponse biases in estimates derived from using only the respondents. The reasons for nonresponse may be complex functions of known auxiliary variables or unknown latent variables not measured by practitioners. The degree to which the propensity to respond is associated with survey outcomes casts light on the overall potential for nonresponse biases for estimates of means and totals. The most common method for nonresponse adjustments to compensate for the potential bias in estimates has been logistic and probit regression models. However, for more …