 Jul 2019

www.sthda.com www.sthda.com

it acts as PCA quantitative variables and as MCA for qualitative variables.

 Jan 2019

awspntest.apa.org awspntest.apa.org

This is because most authors usually did not report a plausible theoretical model for the structure of their observed variables, and there was often insufficient information for us to create our own plausible nong models that could be compared with a theory of the existence of Spearman’s g in the data
The EFA vs. CFA question was a stickler for one peer reviewer, and I can understand why. When measurement is based on strong theory, then I believe that CFA is preferable to EFA. But that was rarely the case in these datasets.

the strongest first factor accounted for 86.3% of observed variable variance
I suspect that this factor was so strong because it consisted of only four observed variables, and three of them were written measures of verbal content. All of the verbal cariables correlated r = .72 to .89. Even the "nonverbal" variable (numerical ability) correlates r = .72 to .81 with the other three variables (Rehna & Hanif, 2017, p. 25). Given these strong correlations, a very strong first factor is almost inevitable.

The weakest first factor accounted for 18.3% of variance
This factor may be weak because the sample consists of Sudanese gifted children, which may have restricted the range of correlations in the dataset.

The mean sample size of the remaining data sets was 539.6 (SD = 1,574.5). The large standard deviation in relationship to the mean is indicative of the noticeably positively skewed distribution of sample sizes, a finding supported by the much smaller median of 170 and skewness value of 6.297. There were 16,559 females (33.1%), 25,431 males (48.6%), and 10,350 individuals whose gender was unreported (19.8%). The majority of samples—62 of 97 samples (63.9%)—consisted entirely or predominantly of individuals below 18. Most of the remaining samples contained entirely or predominantly adults (32 data sets, 33.0%), and the remaining 3 datasets (3.1%) had an unknown age range or an unknown mix of adults and children). The samples span nearly the entire range of life span development, from age 2 to elderly individuals.
My colleague, Roberto Colom, stated in his blog (link below) that he would have discarded samples with fewer than 100 individuals. This is a legitimate analysis decision. See his other commentary (in Spanish) at https://robertocolom.wordpress.com/2018/06/01/launiversalidaddelfactorgeneraldeinteligenciag/
