Imputation techniques provides a useful strategy for dealing with data sets with missing values. In this work the Authors present the results of an experimentation of missing data simulation to sample data coming from ISTAT survey on Small and Medium Enterprises, Arts and Professions. In particular, three different multiple imputation methods are compared considering their capacity to estimate mean, median and variance of population
Statistical procedures for missing data have improved significantly in the last years. This study pu...
The present work suggests some imputation methods to deal with the problems of non-response in sampl...
Abstract In multiple imputation, the resulting estimates are consistent if the im-putation model is ...
In the field of data quality, imputation is the most used method for handling missing data. The perf...
Missing values are a serious problem in surveys. The literature suggests to replace these with reali...
This paper compares methods to remedy missing value problems in survey data. The commonly used meth...
Missing values in sample survey can lead to biased estimation if not treated. Imputation was posted ...
La aparición de datos faltantes es un problema común en la mayoría de las encuestas llevadas a cabo ...
This paper compares methods to remedy missing value problems in survey data. The commonly used metho...
Abstract: The aim of this paper is two-fold: to propose the imputation procedure named ABBN for repl...
Missing values are a common problem in many sampling surveys, and imputation is usually employed to ...
Missing data is a problem frequently met in many surveys on the evaluation of university teaching. T...
Missing values present challenges in the analysis of data across many areas of research. Handling in...
Missing data is common in real-world studies and can create issues in statistical inference. Discard...
In this paper, dealing with the problem of estimating missing values concerning a certain Y variable...
Statistical procedures for missing data have improved significantly in the last years. This study pu...
The present work suggests some imputation methods to deal with the problems of non-response in sampl...
Abstract In multiple imputation, the resulting estimates are consistent if the im-putation model is ...
In the field of data quality, imputation is the most used method for handling missing data. The perf...
Missing values are a serious problem in surveys. The literature suggests to replace these with reali...
This paper compares methods to remedy missing value problems in survey data. The commonly used meth...
Missing values in sample survey can lead to biased estimation if not treated. Imputation was posted ...
La aparición de datos faltantes es un problema común en la mayoría de las encuestas llevadas a cabo ...
This paper compares methods to remedy missing value problems in survey data. The commonly used metho...
Abstract: The aim of this paper is two-fold: to propose the imputation procedure named ABBN for repl...
Missing values are a common problem in many sampling surveys, and imputation is usually employed to ...
Missing data is a problem frequently met in many surveys on the evaluation of university teaching. T...
Missing values present challenges in the analysis of data across many areas of research. Handling in...
Missing data is common in real-world studies and can create issues in statistical inference. Discard...
In this paper, dealing with the problem of estimating missing values concerning a certain Y variable...
Statistical procedures for missing data have improved significantly in the last years. This study pu...
The present work suggests some imputation methods to deal with the problems of non-response in sampl...
Abstract In multiple imputation, the resulting estimates are consistent if the im-putation model is ...