A measure of one-dimensional asymmetry for qualitative variables

Descripción del Articulo

This methodological investigation aims to define a concept of asymmetry for qualitative variables, quantify it, and show its validity. A panel of five expert judges and Monte Carlo simulations were used. The statistic Mean Difference in Frequency (MDF) between pairs of categories ordered by frequenc...

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Detalles Bibliográficos
Autor: Moral de la Rubia, José
Formato: artículo
Fecha de Publicación:2022
Institución:Pontificia Universidad Católica del Perú
Repositorio:Revistas - Pontificia Universidad Católica del Perú
Lenguaje:español
OAI Identifier:oai:ojs.pkp.sfu.ca:article/24627
Enlace del recurso:http://revistas.pucp.edu.pe/index.php/psicologia/article/view/24627
Nivel de acceso:acceso abierto
Materia:Skewness
Discrete distribution
Nominal scale
Qualitative variable
Monte Carlo simulation
Asimetría
Distribución discreta
Escala nominal
Variable cualitativa
Simulación Monte Carlo
Asymétrie
Distribution discrète
Échelle nominale
Variable qualitative
Simulation Monte Carlo
Assimetria
Distribuição discreta
Variável qualitativa
Simulação de Monte Carlo
Descripción
Sumario:This methodological investigation aims to define a concept of asymmetry for qualitative variables, quantify it, and show its validity. A panel of five expert judges and Monte Carlo simulations were used. The statistic Mean Difference in Frequency (MDF) between pairs of categories ordered by frequency homogeneity was defined. The MDF statistic showed a behavior adjusted to expectations with different variants of the binomial distribution. The correlation between the mean skewness score of the judges and MDF was very high. To obtain interpretive guiding cutoffs, 20,000 samples of sizes 20, 40, 100, 200, 500, and 1000 were simulated, drawn from a binomial distribution. It is concluded that MDF is validity to measure asymmetry in qualitative variables.
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