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An Indicator of Nonresponse Bias Derived from Call-back Analysis. Paul P. Biemer RTI International and UNC. Outline. Ignorable vs. non-ignorable nonresponse Bias in the nonresponse adjusted estimator Call-back model for estimating non-ignorable nonresponse
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An Indicator of Nonresponse Bias Derived from Call-back Analysis Paul P. Biemer RTI International and UNC
Outline • Ignorable vs. non-ignorable nonresponse • Bias in the nonresponse adjusted estimator • Call-back model for estimating non-ignorable nonresponse • Application for estimating drug use prevalence • Future research
Estimation for Population Proportions • Consider a SRS of size n • Want to estimate some proportion, • Letdenote the observed dichotomous variable • Let
Nonresponse Adjusted Estimator Estimator of is which is unbiased if nonresponse is ignorable w.r.t. i.e., if the error in is uncorrelated with
Bias in the Adjusted Estimator if nonresponse is ignorable
Call-back Model Analysis • Goal is to estimate when nonresponse is non-ignorable • Uses and call-back patterns to predict ; note, are only observed for respondents. • For example, suppose • Using data on call outcomes at each call-back for users and nonusers, we can estimate response propensity as a function of • Then
Call-outcomes by LOE for Alcohol Interviewed positives Interviewed negatives
Call-outcomes by LOE for Marijuana Interviewed negatives Interviewed positives
Call-outcomes by LOE for Cocaine Interviewed negatives Interviewed positives
Call-back Notation 1 = interview 2 = non-interview 3 = noncontact Call pattern 31111 => noncontact followed by interview Once interviewed, stays interviewed (absorbing state) Once non-interviewed, stays non-interviewed (absorbing state)
Simple Call-back Model for NI-NRLOE-5 Log-Likelihood Likelihood of interview after l calls Likelihood of non-interview after l calls Likelihood of no contact after 5 calls Obtain parameter estimates by maximum likelihood
Simple LOE-5 Model Parameters 11 parameters and 10 degrees of freedom Over-parameterized; requires constraints These constraints reduces parameters to 7:
Application – Drug Use Survey • Compared estimates of alcohol, marijuana and cocaine past year use prevalence for • unadjusted • current (traditional) adjustment • call-back model adjustment • Current adjustment incorporates 13 grouping variables and their interactions including a number of state specific components • Call-back model incorporated call-back data (for up to 15 call-backs) and the drug use variable of interest
Future Work • Test feasibility of incorporating call-back data in the nonresponse adjustment process • Enter # call-backs into the current logistic regression model (does not adjust for NI-NR) • Apply the simple call-back model to the drug use data after traditional adjustment to provide second adjustment factor for NI-NR • Use the simple call-back model to assess NI-NR bias following traditional adjustment approach