MeasurementError.pptVIP

Measurement Error Measurement Error Survey record differs from its true value Sampling error: arise from the random sampling variation when n of units measured instead of N units. Measurement error (Systematic error, nonsampling error) Not decrease with the overall sample size. Decrease with the repeated measurement. Possible sources of measurement error in survey data Interviewer Coder Simplified Model Effect In presence of measurement error with mean zero, the estimator of mean and total remain unbiased or consistent. For more complex parameters, the nice feature may not hold. Fuller (1995) points out that the usual estimators for dist’n func., quantiles, regression coef. are biased. Assuming non-zero constant measurement error mean, the usual estimators of mean, total, proportion are also biased. Furthermore, assuming correlated errors between individuals with the same interviewer, the usual estimator of standard errors are also biased. If estimates of the measurement error variances are available, it is possible to obtain bias-adjusted estimators. Repeated measurement of sub-samples Allocate resources at design stage to make repeated observations on a sub-sample. Hartley and Rao (1978) and Hartley and Biemer (1978) provided interview and coder assignment conditions that permit the estimation of sampling and measurement error. Measurement error variance model. Interviewer Effect Earliest examination of measurement error in the survey focuses on evaluating the impact of interviewers on the data. There is correlation among measured values collected by the same interviewer. Hansen, Hurwitz and Bershad model shows ANOVA model can be specified to estimate interviewer variability. Model is appropriate for continuous responses. For binary response, the result underestimate the intra-interview variability. References Full, W.A. Estimation in the presence of measurement error. Scott, A. and Davis, P.. Estimating interviewer effects fro survey responses. Hartley