Among the wide variety of procedures to handle missing data, imputing the missing values is a popular strategy to deal with missing item responses. In this paper some simple and easily implemented imputation techniques like item and person mean substitution, and some hot-deck procedures, are investigated. A simulation study was performed based on responses to items forming a scale to measure a latent trait of the respondents. The effects of different imputation procedures on the estimation of the latent ability of the respondents were investigated, as well as the effect on the estimation of Cronbach's alpha (indicating the reliability of the test) and Loevinger's H-coefficient (indicating scalability). The results indicate that procedures w...
A critical issue in analyzing multi-item scales is missing data treatment. Previous studies on this ...
Objectives: Regardless of the proportion of missing values, complete-case analysis is most frequentl...
In real-life situations, we often encounter data sets containing missing observations. Statistical m...
Among the wide variety of procedures to handle missing data, imputing the missing values is a popula...
Among the wide variety of procedures to handle missing data, imputing the missing values is a popula...
Among the wide variety of procedures to handle missing data, imputing the missing values is a popula...
missing data, mean imputation, hot-deck imputation, item response theory, simulation,
Researchers in many fields use multiple item scales to measure important vari-ables such as attitude...
Unplanned missing responses are common to surveys and tests including large scale assessments. There...
Missing data are ubiquitous in educational research settings, including item responses in multilevel...
Nonresponse is a major problem often faced by social scientists when analysing survey data. A range ...
Missing data are a significant problem in testing. Research into strategies for dealing with it have...
Objectives Regardless of the proportion of missing values, complete-case analysis is most frequently...
Imputation is a method of adjusting for missing data. Missing responses to data items is a common pr...
EnThe aim of this paper is two-fold: to propose the imputation procedure named ABBN for replacing mi...
A critical issue in analyzing multi-item scales is missing data treatment. Previous studies on this ...
Objectives: Regardless of the proportion of missing values, complete-case analysis is most frequentl...
In real-life situations, we often encounter data sets containing missing observations. Statistical m...
Among the wide variety of procedures to handle missing data, imputing the missing values is a popula...
Among the wide variety of procedures to handle missing data, imputing the missing values is a popula...
Among the wide variety of procedures to handle missing data, imputing the missing values is a popula...
missing data, mean imputation, hot-deck imputation, item response theory, simulation,
Researchers in many fields use multiple item scales to measure important vari-ables such as attitude...
Unplanned missing responses are common to surveys and tests including large scale assessments. There...
Missing data are ubiquitous in educational research settings, including item responses in multilevel...
Nonresponse is a major problem often faced by social scientists when analysing survey data. A range ...
Missing data are a significant problem in testing. Research into strategies for dealing with it have...
Objectives Regardless of the proportion of missing values, complete-case analysis is most frequently...
Imputation is a method of adjusting for missing data. Missing responses to data items is a common pr...
EnThe aim of this paper is two-fold: to propose the imputation procedure named ABBN for replacing mi...
A critical issue in analyzing multi-item scales is missing data treatment. Previous studies on this ...
Objectives: Regardless of the proportion of missing values, complete-case analysis is most frequentl...
In real-life situations, we often encounter data sets containing missing observations. Statistical m...