TY - JOUR
T1 - Confirmatory factor analysis with missing data in a small sample
T2 - cognitive reserve in people with Down Syndrome
AU - Cañete-Massé, Cristina
AU - Carbó-Carreté, Maria
AU - Figueroa-Jiménez, María Dolores
AU - Oviedo, Guillermo R.
AU - Guerra-Balic, Myriam
AU - Javierre, Casimiro
AU - Peró-Cebollero, Maribel
AU - Guàrdia-Olmos, Joan
N1 - Funding Information:
Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This study has been funded by the Spanish Ministry of Science, Innovation and Universities (PGC2018-095829-B-I00).
Publisher Copyright:
© 2021, The Author(s).
PY - 2022/10
Y1 - 2022/10
N2 - The presence of missing data and small sample sizes are very common in social and health sciences. Concurrently to present a methodology to solve the small sample size and missing data, we aim to present a definition of Cognitive Reserve for people with Down Syndrome. This population has become an appealing focus to study this concept because of the high incidence of dementia. The accidental sample comprised 35 persons with DS (16–35 years). A total of 12 variables were acquired, four of them had missing data. Two types of multiple imputation were made. Confirmatory factor analysis with Bayesian estimations was performed on the final database with non-informative priors. However, to solve the sample size problem, two additional corrections were made: first, we followed the Jiang and Yuan (2017) schema, and second, we made a Jackknife correlation correction. The estimations of the confirmatory factor analysis, as well as the global fit, are adequate. As an applied perspective, the acceptable fit of our model suggests the possibility of operationalizing the latent factor Cognitive Reserve in a simple way to measure it in the Down Syndrome population.
AB - The presence of missing data and small sample sizes are very common in social and health sciences. Concurrently to present a methodology to solve the small sample size and missing data, we aim to present a definition of Cognitive Reserve for people with Down Syndrome. This population has become an appealing focus to study this concept because of the high incidence of dementia. The accidental sample comprised 35 persons with DS (16–35 years). A total of 12 variables were acquired, four of them had missing data. Two types of multiple imputation were made. Confirmatory factor analysis with Bayesian estimations was performed on the final database with non-informative priors. However, to solve the sample size problem, two additional corrections were made: first, we followed the Jiang and Yuan (2017) schema, and second, we made a Jackknife correlation correction. The estimations of the confirmatory factor analysis, as well as the global fit, are adequate. As an applied perspective, the acceptable fit of our model suggests the possibility of operationalizing the latent factor Cognitive Reserve in a simple way to measure it in the Down Syndrome population.
KW - Bayesian structural equation models
KW - Cognitive reserve
KW - Down syndrome
KW - Missing data
KW - Small sample
UR - http://www.scopus.com/inward/record.url?scp=85118362358&partnerID=8YFLogxK
U2 - 10.1007/s11135-021-01264-x
DO - 10.1007/s11135-021-01264-x
M3 - Article
AN - SCOPUS:85118362358
SN - 0033-5177
VL - 56
SP - 3363
EP - 3377
JO - Quality and Quantity
JF - Quality and Quantity
IS - 5
ER -