In this study, the purpose is to compare factor retention methods under simulation conditions. For this purpose, simulations conditions with a number of factors (1, 2 [simple]), sample sizes (250, 1.000, and 3.000), number of items (20, 30), average factor loading (0.50, 0.70), and correlation matrix (Pearson Product Moment [PPM] and Tetrachoric)…

This Monte Carlo simulation study aimed to investigate confirmatory factor analysis (CFA) estimation methods under different conditions, such as sample size, distribution of indicators, test length, average factor loading, and factor structure. Binary data were generated to compare the performance of maximum likelihood (ML), mean and variance…

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted…

Purpose: Systems intelligence (SI) (Saarinen and Hämäläinen, 2004) is a construct defined as a person's ability to act intelligently within complex systems involving interaction and feedback. SI relates to our ability to act in systems and reason about systems to adaptively carry out productive actions within and with respect to systems such as…

"Curriculum alignment" is the compatibility between a country's centralized curriculum determined by the ministry of education and what teachers do during the teaching process. However, it is observed that teachers do not exactly implement the curriculum. The purpose of this study is to develop a scale that will determine the factors…

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

This article reports results of a confirmatory factor analysis performed to cross-validate the factor structure of the Educators' Attitudes Toward Educational Research Scale. The original scale had been developed by the author and revised based on the results of an exploratory factor analysis. In the present study, the revised scale was given to…

Numerous procedures have been suggested for determining the number of factors to retain in factor analysis. However, previous studies have focused on comparing methods using normal data sets. This study had two phases. The first phase explored the Kaiser method, Scree test, Bartlett's chi-square test, Minimum Average Partial (1976&2000),…

This article reports a meta-analysis of personality-academic performance relationships, based on the 5-factor model, in which cumulative sample sizes ranged to over 70,000. Most analyzed studies came from the tertiary level of education, but there were similar aggregate samples from secondary and tertiary education. There was a comparatively…

Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…

Simulation results show that the power to detect small mean differences when fitting a model with free residual variances across groups decreases as the difference in R squared increases. This decrease is more pronounced in the presence of correlated errors and if group sample sizes differ. (SLD)

The relationship of sample size to number of variables in the use of factor analysis has been treated by many investigators. In attempting to explore what the minimum sample size should be, none of these investigators pointed out the constraints imposed on the dimensionality of the variables by using a sample size smaller than the number of…

The degree of indeterminacy of the factor score estimates is biased and can lead to erroneous conclusion regarding the nature of the results. The magnitude of this bias is illustrated and guidelines for describing factor analytic studies using factor scores are offered. (Author/PN)

In this article, the authors study the factorial structure of 2 versions (64 items and 32 items) of the Dutch translation of the Inventory of Interpersonal Problems (IIP; L. M. Horowitz, L. E. Alden, J. S. Wiggins, & A. L. Pincus, 2000) in both a clinical sample (n = 382) and a student sample (n = 287). First, the authors test whether both…