Factor analysis

Context (archaeology)

Exploratory analysis

Statistics

Multivariate statistics

Chromatography

Multivariate analysis

Archaeology

Computer science

Exploratory data analysis

Structural equation modeling

Environmental health

Factor (programming language)

Regression analysis

Confirmatory factor analysis

Mathematics

Geography

Econometrics

Population

Data science

Sample size determination

Medicine

Chemistry

Programming language

Sample (material)

Exploratory factor analysis

Behavior Research Methods

Nowadays, exploratory and confirmatory factor analyses are two important consecutive steps in an overall analysis process. The overall analysis should start with an exploratory factor analysis that explores the data and establishes a hypothesis for the factor model in the population. Then, the analysis process should be continued with a confirmatory factor analysis to assess whether the hypothesis proposed in the exploratory step is plausible in the population. To carry out the analysis, researchers usually collect a single sample, and then split it into two halves. As no specific splitting methods have been proposed to date in the context of factor analysis, researchers use a random split approach. In this paper we propose a method to split samples into equivalent subsamples similar to one that has already been proposed in the context of multivariate regression analysis. The method was tested in simulation studies and in real datasets.

SOLOMON: a method for splitting a sample into equivalent subsamples in factor analysis