A case study on the use of multiple imputation.
نویسندگان
چکیده
Multiple imputation is a relatively new technique for dealing with missing values on items from survey data. Rather than deleting observations for which a value is missing, or assigning a single value to incomplete observations, one replaces each missing item with two or more values. Inferences then can be made with the complete data set. This paper presents an application of multiple imputation using the 1987-1988 National Survey of Families and Households. We impute several binary indicators of whether the respondent's elderly mother/mother-in-law is married. Descriptive statistics are then presented for the sample of adult children with an unmarried mother or mother-in-law.
منابع مشابه
Accuracy 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 کاملچند رویکرد برخورد با مقادیر گمشده متغیرهای کمی و بررسی اثر آنها بر نتایج حاصل از یک کارآزمایی بالینی
Background and Objectives: A major challenge that affects the longitudinal studies is the problem of missing data. Missing in the data may result in the loss of part of the information which reduces the accuracy of the estimator and obtain the results will be biased and inaccurate. Therefore, it is necessary to evaluate the missing data mechanism from a longitudinal research and to consider thi...
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 کاملImputation of parent-offspring trios and their effect on accuracy of genomic prediction using Bayesian method
The objective of this study was to evaluate the imputation accuracy of parent-offspring trios under different scenarios. By using simulated datasets, the performance Bayesian LASSO in genomic prediction was also examined. The genome consisted of 5 chromosomes and each chromosome was set as 1 Morgan length. The number of SNPs per chromosome was 10000. One hundred QTLs were randomly distributed a...
متن کاملSelection of Variables that Influence Drug Injection in Prison: Comparison of Methods with Multiple Imputed Data Sets
Background: Prisoners, compared to the general population, are at greater risk of infection. Drug injection is the main route of HIV transmission, in particular in Iran. What would be of interest is to determine variables that govern drug injection among prisoners. However, one of the issues that challenge model building is incomplete national data sets. In this paper, we addressed the process ...
متن کاملEffect of Reference Population Size and Imputation Methods on the Accuracy of Imputation in Pure and Mixed Populations
Imputation as a method of creating low-density chips to high-density chips has been introduced to increase the accuracy of genomic selection in animals. In the current study, to investing imputation accuracy, three populations of mixed (scenario 1), pure (scenario 2) and mixed + pure (scenario 3) were simulated using QMSim. Two methods of imputation including Beagle and Flmpute were used fo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Demography
دوره 32 3 شماره
صفحات -
تاریخ انتشار 1995