Following an exploratory factor analysis, scores may be computed and used in subsequent analyses. Factor are composite variables which provide information about individual’s placement on the factor(s). This article discusses popular methods to create under two different classes: refined non-refined. Strengths considerations of various methods, for using general, discussed. Exploratory analysis (EFA) has been as analytical tool educational research. The with novel or research scenarios a...

AbstractThis study compared diagonal weighted least squares robust estimation techniques available in 2 popular statistical programs: (DWLS; LISREL version 8.80) and squares–mean (WLSM) squares—mean variance adjusted (WLSMV; Mplus 6.11). A 20-item confirmatory factor analysis was estimated using item-level ordered categorical data. Three different nonnormality conditions were applied to 2- 7-category data with sample sizes of 200, 400, 800. Convergence problems seen nonnormal when DWLS used...

This article used multitrait-multimethod methodology and covariance modeling for an investigation of the presence correlates method effects associated with negatively worded items on Rosenberg Self-Esteem (RSE) scale (Rosenberg, 1989) using a sample 757 adults. Results showed that negative item phrasing RSE were present. Method wording similarly observed Social Physique Anxiety Scale (SPAS; Hart, Leary, & Rejeski, present significantly correlated in analyses included both SPAS...

This study investigated the psychological assessment literature to determine what applied researchers are using and reporting from confirmatory factor analysis (CFA) studies for evidence of construct validation. One hundred one articles published in four major journals between 1990 2002 were systematically reviewed. Information each article was collected across broad areas: Background, Data Screening, Reporting Results, Discussing Results. Temporal trends assessed with point-biserial...

This study examined the performance of weighted root mean square residual (WRMR) through a simulation using confirmatory factor analysis with ordinal data. Values and cut scores for WRMR were examined, along comparison its relative to commonly cited fit indexes. The findings showed that illustrated worse when sample size increased or model misspecification increased. Lower (i.e., better) values observed nonnormal data present, there lower loadings, few categories analyzed. generally expected...

Research has revealed that the performance of root mean square error approximation (RMSEA) in assessing structural equation models with small degrees freedom (df) is suboptimal, often resulting rejection correctly specified or closely fitted models. This study investigates standardized residual (SRMR) and comparative fit index (CFI) df various levels factor loadings, sample sizes, model misspecifications. We find that, comparison RMSEA, population SRMR CFI are less susceptible to effects df....

This study investigated the impact of categorization on confirmatory factor analysis (CFA) parameter estimates, standard errors, and 5 ad hoc fit indexes. Models were generated that represented empirical research situations in terms model size, sample sizes, loading values. CFA results obtained from normally distributed, continuous data compared to 5-category Likert-type with normal distributions. The ordered categorical analyzed using estimators: Weighted Least Squares (WLS; polychoric...

Two classification methods, latent class cluster analysis and analysis, are used to identify groups of child behavioral adjustment underlying a sample elementary school children aged 6 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers as input for analyses. Both the procedures results were compared. The uncovered three classes representing differing levels children's (well adjusted, average adjustment, functionally impaired), whereas seven...

We argue that the definition of close fitting models should embody notion substantially ignorable misspecifications (SIM). A SIM model is a misspecified might be selected, based on parsimony, over true knowledge available. Because in applications (i.e., data generating mechanism) unknown, we investigate relationship between population standardized root mean square residual (SRMR) values and various factor analysis to better understand magnitudes SRMR. Summary effect sizes misfit such as SRMR...

When questionnaires include Likert scales, items endorsed by relatively few respondents may result from characteristics of examinees or the constructs under study. Researchers collapse categories to increase cell sample size; however, effects this practice have not been systematically investigated. A five-point ordinal scale was simulated where data included responses in extreme categories. Different estimators were applied sparsely distributed and collapsed category data; size, number...

Abstract This article examines the analysis and interpretation of wording effects associated with use both positively negatively worded items in survey instruments. Recent research using global self-esteem scales has indicated that strategy including may introduce systematic biases interfere measurement substantive trait, self-esteem. Although such elements are "methods effects," they not be purely artifactual nature, we show this distinction between interpretations important implications...

Abstract When developing self-report instruments, researchers often have included both positively and negatively worded items to negate the possibility of response bias. Unfortunately, this strategy may interfere with examinations latent structure instruments by introducing method effects, particularly among items. The substantive nature effects remains unclear requires examination. Building on recommendations from previous (Tomás& Oliver, 1999), study examined longitudinal invariance...

This study examined the effect of model size on chi-square test statistics obtained from ordinal factor analysis models. The performance six robust were compared across various conditions, including number observed variables (p), factors, sample size, (mis)specification, categories, and threshold distribution. Results showed that unweighted least squares (ULS) generally outperform diagonally weighted (DWLS) statistics. ULSM estimator performed best overall. However, when fitting models with...

This study investigates the performance of robust maximum likelihood (ML) estimators when fitting and evaluating small sample latent growth models with non-normal missing data. Results showed that ML methods could be used to account for non-normality even size is very (e.g., N < 100). Among estimators, “MLR” was optimal choice, as it found both data while also yielding more accurate standard error estimates parameter coverage. However, choice “MLMV” produced most p values χ 2 test...

The authors explored patterns of appraising tests in a large sample 1st-year college students. Cluster analysis was used to identify homogeneous groups students who shared similar cognitive appraisals about testing. internally validated findings with an independent from the same population and examined extent which cluster membership differentiated undergraduates on basis external indicators (e.g., anxiety, emotion-regulation strategies, achievement). 2 randomly drawn samples conduct initial...

An index extending the widely used omega-hierarchical coefficient is discussed, which can be for evaluating influence of a second-order factor on interrelationships among components hierarchical measuring instrument. The represents useful and informative complement to traditional measure explained overall scale score variance by that underlying construct. A point interval estimation procedure outlined described index, based model reparameterization developed within latent variable modeling...

ABSTRACT Behavioral and emotional disorders in childhood can have lasting impacts areas such as education future employment, often extending into adulthood. Identifying the potential children's early grades is beneficial to provide proactive assistance. In this study, we employed a well‐validated scale ‐ Strengths Difficulties Questionnaire (SDQ) investigate profiles of five‐dimensional behavioral problems for 639 elementary school children from southern U.S. state. Using diagnostic...

The fifth edition of the Stanford-Binet test went through significant reformulation its item content, administration format, standardization procedures, and theoretical structure. Additionally, was revised to measure five factors important intelligence across both verbal nonverbal domains. To better understand these substantial revisions, underlying factor structure instrument investigated using exploratory confirmatory analysis procedures age groups tested by publishers. Analyses were...

.Universal screening has been routinely advised for determining the presence of problems initiating problem-solving processes and models. The aim this study was to assess effect two screener development methods on validity score inferences teacher screeners child behavioral emotional risk. reliability indices associated with scores were compared by analyzing data 472 children from 20 elementary schools who screened Screener both instruments significantly related academic achievement test...

The BASC-2 Behavioral and Emotional Screening System (BESS) Student Form (Kamphaus & Reynolds, 2007) is a recently developed youth self-report rating scale designed to identify students at risk for behavioral emotional problems. BESS was derived from the Behavior Assessment Children-Second Edition Self-Report of Personality (BASC-2 SRP; Reynolds Kamphaus, 2004) using principal component analytic procedures theoretical considerations. Using 3 samples, authors conducted exploratory factor...