Comparison of methods for dealing with missing values in the EPV-R

Background: The development of an effective instrument to assess the risk of partner violence is a topic of great social relevance. This study evaluates the scale of “Predicción del Riesgo de Violencia Grave Contra la Pareja” –Revisada– (EPV-R - Severe Intimate Partner Violence Risk Prediction Scale...

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Detalles Bibliográficos
Autores: Paniagua, David, Amor, Pedro J., Echeburúa, Enrique, Abad García, Francisco José
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universidad Autónoma de Madrid
Repositorio:Biblos-e Archivo. Repositorio Institucional de la UAM
Idioma:inglés
OAI Identifier:oai:repositorio.uam.es:10486/681098
Acceso en línea:http://hdl.handle.net/10486/681098
https://dx.doi.org/10.7334/psicothema2016.75
Access Level:acceso abierto
Palabra clave:Abuse
Missing values
Imputation
Item response theory
Psicología
Descripción
Sumario:Background: The development of an effective instrument to assess the risk of partner violence is a topic of great social relevance. This study evaluates the scale of “Predicción del Riesgo de Violencia Grave Contra la Pareja” –Revisada– (EPV-R - Severe Intimate Partner Violence Risk Prediction Scale-Revised), a tool developed in Spain, which is facing the problem of how to treat the high rate of missing values, as is usual in this type of scale. Method: First, responses to the EPV-R in a sample of 1215 male abusers who were reported to the police were used to analyze the patterns of occurrence of missing values, as well as the factor structure. Second, we analyzed the performance of various imputation methods using simulated data that emulates the missing data mechanism found in the empirical database. Results: The imputation procedure originally proposed by the authors of the scale provides acceptable results, although the application of a method based on the Item Response Theory could provide greater accuracy and offers some additional advantages. Conclusions: Item Response Theory appears to be a useful tool for imputing missing data in this type of questionnaire