A unified approach to linearization variance estimation from survey data after imputation for item nonresponse
نویسندگان
چکیده
Variance estimation after imputation is an important practical problem in survey sampling. When deterministic imputation or stochastic imputation is used, we show that the variance of the imputed estimator can be consistently estimated by a unifying linearize and reverse approach. We provide some applications of the approach to regression imputation, fractional categorical imputation, multiple imputation and composite imputation. Results from a simulation study, under a factorial structure for the sampling, response and imputation mechanisms, show that the proposed linearization variance estimator performs well in terms of relative bias, assuming a missing at random response mechanism.
منابع مشابه
An Empirical Comparison of Performance of the Unified Approach to Linearization of Variance Estimation after Imputation with Some Other Methods
Imputation is one of the most common methods to reduce item non_response effects. Imputation results in a complete data set, and then it is possible to use naϊve estimators. After using most of common imputation methods, mean and total (imputation estimators) are still unbiased. However their variances (imputation variances) are underestimated by naϊve variance estimators. Sampling mechanism an...
متن کاملEstimating Variance of the Sample Mean in Two-phase Sampling with Unit Non-response Effect
In sample surveys, we always deal with two types of errors: Sampling error and non-sampling error. One of the most common non-sampling errors is nonresponse. This error happens when some sample units are not observed or viewed but they do not answer some of the questions. The complete prevention of this error is not possible, but it can be significantly reduced. The non-response causes bias and ...
متن کاملThe Effect of Multiple Weighting Steps on Variance Estimation
1. Introduction Multiple steps in weighting are common in survey estimation. Each step usually introduces a source of variability in an estimator that may be important to reflect when estimating variances. A typical sequence of weighting steps in a probability sample is this: 1. Compute base weights. 2. Adjust weights to account for units with unknown eligibility. 3. Adjust weights for nonrespo...
متن کاملVariance Estimation in the Presence of Imputation for Missing Data
Item nonresponse is usually treated by some form of deterministic or random imputation. We focus on deterministic imputation; in particular, ratio and nearest neighbour imputations commonly used in establishment surveys. Frequentist inference from imputed data is based on a repeated sampling framework and assumed response mechanism. On the other hand, use of imputation models requires only that...
متن کاملA Simulation Study to Evaluate the Robustness of Recent Methods for Preparing Variance Estimates in the Presence of Hot Deck Imputation
Many large-scale surveys currently use a variety of single imputation methods–as discussed by Chapman (1976), Cox (1980; and Kalton and Kasprzyk (1986)—to handle item nonresponse. Since the use of such imputation increases the underlying variation in the survey results, methods are needed to assess the impact. Until fairly recently, methods to assess the impact of the imputation on the variance...
متن کامل