Amputation versus Imputation of Missing Values through Ratio Method in Sample Surveys
نویسنده
چکیده
In this article we consider the estimation of population mean when some observations on the study characteristic are missing in the bivari ate sample data In all ve estimators are presented and their e ciency properties are discussed One estimator arises from the the amputation of incomplete observations while the remaining four estimators are formu lated using inputed values obtained by the ratio method of estimation
منابع مشابه
تحلیل درستنمایی ماکزیمم مدل رگرسیون لجستیک در حالتی که داده های متغیرهای پیشگو کامل نیستند ولی متغیرهای کمکی وجود دارند
Background and Objectives: Missing data exist in many studies, e.g. in regression models, and they decrease the model's efficacy. Many methods have been suggested for handling incomplete data: they have generally focused on missing outcome values. But covariate values can also be missing.Materials and Methods: In this paper we study the missing imputation by the EM algorithm and auxiliary varia...
متن کاملAn 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 کاملPseudo-GEE Approach to Analyzing Longitudinal Surveys under Imputation for Missing Responses
This paper presents a pseudo-GEE approach to the analysis of longitudinal surveys when the response variable contains missing values. A cycle-specific marginal hotdeck imputation method is proposed to fill in the missing responses and the pseudo-GEE method described in Carrillo et al. (2009) is applied to the imputed data set. Consistency of the resulting pseudo-GEE estimators is established un...
متن کاملAccuracy evaluation of different statistical and geostatistical censored data imputation approaches (Case study: Sari Gunay gold deposit)
Most of the geochemical datasets include missing data with different portions and this may cause a significant problem in geostatistical modeling or multivariate analysis of the data. Therefore, it is common to impute the missing data in most of geochemical studies. In this study, three approaches called half detection (HD), multiple imputation (MI), and the cosimulation based on Markov model 2...
متن کاملMultiple Imputation in a Complex Sample Survey
Multiple imputation for missing survey data is relatively new concept. As defined by one of its leading proponents, "multiple imputation is the technique that replaces each missing or deficient value with two or more acceptable values representing a distribution of possibilities" (Rubin 1987, p.2). Multiply-imputed data reflects the uncertainty contained in the imputation process in a way not p...
متن کامل