TY - JOUR
AU - Rosén, Monica
AB -  In this study, the impact of missing data on estimates of gender differences in hierarchically ordered ability dimensions is investigated. The data consist of 13 ability tests on which the whole sample of 1,224 13‐year‐old students has information and 3 standardized achievement tests on which a reduced sample of 981 participants has information. Utilizing missing data techniques for latent variable models, the study also becomes a validation of previously reported gender differences in latent hierarchical ability dimensions. In the previous analysis, the 243 students lacking data were assumed to be missing at random and thus excluded from the analysis. The attrition was found to have an impact on both the hierarchical model and on gender differences in latent dimensions. The attrition appeared biased with respect to general achievement and gender. When the cases with missing data were included in the analysis, the structure of the model remained stable and strengthened in some respects. The female advantage on g increased, whereas their advantage on Crystallized Intelligence decreased. The male advantage on spatial dimensions increased, whereas their advantage on narrow achievement factors decreased. About half of the attrition was due to missing classes, and the other half was due to missing individuals. There was no gender difference in proportions of the two types of attriters. It was mainly male individual attriters who contributed to the bias by performing much worse than the male completers. 
TI - Gender differences in hierarchically ordered ability dimensions: The impact of missing data
JF - Structural Equation Modeling: A Multidisciplinary Journal
DO - 10.1080/10705519809540088
DA - 1998-01-01
UR - https://www.deepdyve.com/lp/taylor-francis/gender-differences-in-hierarchically-ordered-ability-dimensions-the-8vJuaYxp4A
SP - 37
EP - 62
VL - 5
IS - 1
DP - DeepDyve
ER -