Dimensionality assessment in the presence of wording effects: A network psychometric and factorial approach.
Behav Res Methods
; 56(6): 6179-6197, 2024 09.
Article
em En
| MEDLINE
| ID: mdl-38379114
ABSTRACT
This study proposes a procedure for substantive dimensionality estimation in the presence of wording effects, the inconsistent response to regular and reversed self-report items. The procedure developed consists of subtracting an approximate estimate of the wording effects variance from the sample correlation matrix and then estimating the substantive dimensionality on the residual correlation matrix. This is achieved by estimating a random intercept factor with unit loadings for all the regular and unrecoded reversed items. The accuracy of the procedure was evaluated through an extensive simulation study that manipulated nine relevant variables and employed the exploratory graph analysis (EGA) and parallel analysis (PA) retention methods. The results indicated that combining the proposed procedure with EGA or PA achieved high accuracy in estimating the substantive latent dimensionality, but that EGA was superior. Additionally, the present findings shed light on the complex ways that wording effects impact the dimensionality estimates when the response bias in the data is ignored. A tutorial on substantive dimensionality estimation with the R package EGAnet is offered, as well as practical guidelines for applied researchers.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Psicometria
Limite:
Humans
Idioma:
En
Revista:
Behav Res Methods
Assunto da revista:
CIENCIAS DO COMPORTAMENTO
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Espanha
País de publicação:
Estados Unidos