On structural equation modeling with data that are not missing completely at random

A general latent variable model is given which includes the specification of a missing data mechanism. This framework allows for an elucidating discussion of existing general multivariate theory bearing on maximum likelihood estimation with missing data. Here, missing completely at random is not a prerequisite for unbiased estimation in large samples, as when using the traditional listwise or pairwise present data approaches. The theory is connected with old and new results in the area of selection and factorial invariance. It is pointed out that in many applications, maximum likelihood estimation with missing data may be carried out by existing structural equation modeling software, such as LISREL and LISCOMP. Several sets of artifical data are generated within the general model framework. The proposed estimator is compared to the two traditional ones and found superior.The research of the first author was supported by grant No. SES-8312583 from the National Science Foundation and by a Spencer Foundation grant. We wish to thank Chuen-Rong Chan for drawing the path diagram.     

Some properties of estimated scale invariant covariance structures

Scale invariance is a property shared by many covariance structure models employed in practice. An example is provided by the well-known LISREL model subject only to classical normalizations and zero constraints on the parameters. It is shown that scale invariance implies that the estimated covariannce matrix must satisfy certain equations, and the nature of these equations depends on the fitting function used. In this context, the paper considers two classes of fitting functions: weighted least squares and the class of functions proposed by Swain.Constructive comments by the referees are greatly appreciated. The author gratefully acknowledges Michael Browne's interest in his work.     

Probability of directional errors with disordinal (qualitative) interaction

In a factorial design with two or more factors, there is nonzero interaction when the differences among the levels of one factor vary with levels of other factors. The interaction is disordinal or qualitative with respect to a specific factor, sayA, if the difference between at least two levels ofA is positive for some and negative for some levels of the other factors. Using standard methods of analysis, there is a potentially large probability of drawing incorrect conclusions about the signs of differences in the presence of disordinal interaction. The maximum probability of such incorrect conclusions, or directional errors, is derived for two-factor designs in which the factor of interest has two levels and the number of levels of the other factor varies.     

Comparing Chinese youth with American youth on adjustment: An illustration of measurement issues in cross-cultural research

In this article, we used results from two studies to show the need to go beyond linguistic equivalence to establish construct validity and measurement invariance in cross-cultural research. Study 1 examined Rosenberg Self-Esteem (RSE; 10 items) data from 156 Mainland Chinese youth (M = 13.8 years, SD = .53) and 213 Chinese-American youth (M = 13.6 years, SD = 2.1) from high socioeconomic status (SES) families. The Chinese translation of the RSE has been widely used. Study 2 included 1060 Mainland Chinese youth (M = 15.6 years, SD = 2.3) and 412 racially diverse American youth (M = 16.0, SD = 2.9) from all SES backgrounds. Data were collected with the third and newest edition of the Behavioural Assessment System for Children-Self Report of Personality (BASC-3-SRP; 189 items). We translated and back-translated the BASC-3-SRP between English and Chinese to establish linguistic equivalence. All participants were females. Study 1 showed that the RSE had acceptable internal consistency but lacked construct validity. Study 2 showed that the original and the translated BASC-3-SRP had good internal consistency and construct validity, but nine of its 16 subscales lacked measurement invariance. These results highlight measurement issues facing international and cross-cultural research.     

Factorial validation and measurement invariance of the French version of the multidimensional competitive orientation inventory (FVMCOI) in the sport field

IntroductionLittle is known about the importance of the adaptive, maladaptive and neutral facets of competitive orientations among French athletes.ObjectiveThe aim of this study is to test the factorial validation and measurement invariance of the French version of the multidimensional competitive orientation inventory (FVMCOI) from the original version (MCOI, Orosz et al., 2018), which included 12 items and four factors (i.e., hypercompetitive orientation, self-developmental competitive orientation, anxiety-driven competition avoidance, and lack of interest toward competition).MethodA series of three complementary studies was carried out with a total sample of 891 competitors.ResultsFollowing cross-cultural validation methods a preliminary version of the FVMCOI was constructed and the clarity of its items was established (study 1). Then, exploratory structural equation modeling (ESEM) confirmed that the four-factor model for the FVMCOI was factorially valid, and consistent with the model of the original version. As such, the multiple-group invariance tests showed that the FVMCOI was partially invariant across both age and gender and fully invariant across type of sport, level of competition and over time (study 2). Finally, the concurrent validity of the FVMCOI was demonstrated through its expected relationships with achievement goals, competitive aggressiveness and anger in sport (study 3).ConclusionThe establishment of the FVMCOI extends the research in sport psychology by allowing an extensive psychometric study of the MCOI in the sport domain and providing deeper insights into the healthy, unhealthy, and neutral nature of competitive orientation in this context. The FVMCOI's potential practical applications in sport context, with some limitations and perspectives of this study, are also discussed.     

矛盾年龄偏见量表在中国大学生群体中的修订及信效度检验

目的：修订矛盾年龄偏见量表(the Ambivalent Ageism Scale, AAS),并在中国大学生群体中进行信、效度检验。方法：对1182名大学生施测AAS中文翻译版,探索并验证其因子结构,分析信、效度和测量等值性。其中347人还完成老化知识量表(FAQ)和容纳他人量表(AOS),用以检验AAS中文版的校标关联效度。另有74人在4周后重测AAS中文版。结果：AAS中文修订版包含认知帮助/保护、不想要的帮助和敌意年龄偏见三因子,总量表和各维度的Cronbach’s α系数依次为0.83、0.80、0.85、0.76,重测信度依次为0.78、0.62、0.78、0.71。AAS中文修订版及各维度与FAQ和AOS负相关(r=-0.23～-0.48,ps<0.001)。验证因素分析表明AAS中文修订版的拟合良好(χ²/df=3.51,CFI=0.96,TLI=0.94,RMSEA=0.07,SRMR=0.05)。且该量表跨性别形态、弱等值、部分强等值和部分严格测量等值成立。结论：修订后的矛盾年龄偏见量表(AAS)中文版的信、效度良好,具备跨性别的测量部分...     

Psychometric properties and measurement invariance of Depression,Anxiety and Stress Scales (DASS-21) across cultures

Cross-culturally measurement invariant instruments are useful for the assessment of mental symptoms across cultures. The current study aimed to investigate the psychometric properties and measurement invariance of the Depression, Anxiety and Stress Scales (DASS-21) (DASS) across Pakistan and Germany. German participants were recruited through an online survey (N = 1323), while Pakistani participants were recruited through online survey or paper-and-pencil survey (N = 1841). The DASS-21 showed good reliability, construct and structure validity in both countries. The DASS-21 indicated partial weak (stress subscale) and partial strong measurement invariance (depression and anxiety subscales) between both countries. Latent mean comparison of depression and anxiety symptoms between Pakistani and German students indicated that Pakistani university students experience more symptoms of depression and anxiety. Results suggest that the DASS-21 could be used in Pakistan and Germany, but caution should be taken when making direct comparisons between the two countries.     

Modeling the Influence of Language Input Statistics on Children's Speech Production

We trained a computational model (the Chunk-Based Learner; CBL) on a longitudinal corpus of child–caregiver interactions in English to test whether one proposed statistical learning mechanism—backward transitional probability—is able to predict children's speech productions with stable accuracy throughout the first few years of development. We predicted that the model less accurately reconstructs children's speech productions as they grow older because children gradually begin to generate speech using abstracted forms rather than specific “chunks” from their speech environment. To test this idea, we trained the model on both recently encountered and cumulative speech input from a longitudinal child language corpus. We then assessed whether the model could accurately reconstruct children's speech. Controlling for utterance length and the presence of duplicate chunks, we found no evidence that the CBL becomes less accurate in its ability to reconstruct children's speech with age.     

A Validation of a Multicultural Competency Measure Among South Korean Counselors

The authors translated the California Brief Multicultural Competence Scale (CBMCS; Gamst et al., 2004), a measure of multicultural competence, into Korean for cross-cultural validation. An exploratory factor analysis followed by a confirmatory factor analysis on a sample of Korean counselors (N = 365) supported a 3-factor model: Multicultural Ability, Multicultural Knowledge, and Multicultural Awareness. The Korean version was deemed to possess sound psychometric properties, such as high test-retest reliability and criterion-related validity. Los autores tradujeron al idioma coreano la Escala Breve de Competencia Multicultural de California (CBMCS, por sus siglas en inglés; Gamst et al., 2004), un instrumento de medida de competencia multicultural, para su validación intercultural. Un análisis factorial exploratorio seguido de un análisis factorial confirmatorio sobre una muestra de consejeros coreanos (N = 365) respaldó un modelo de 3 factores: Habilidad Multicultural, Conocimiento Multicultural y Conciencia Multicultural. Se concluyó que la versión en coreano tenía propiedades psicométricas sólidas, como una alta fiabilidad de la repetición de las pruebas y una alta validez de criterio.     

A unified approach to exploratory factor analysis with missing data,nonnormal data,and in the presence of outliers

Factor analysis is regularly used for analyzing survey data. Missing data, data with outliers and consequently nonnormal data are very common for data obtained through questionnaires. Based on covariance matrix estimates for such nonstandard samples, a unified approach for factor analysis is developed. By generalizing the approach of maximum likelihood under constraints, statistical properties of the estimates for factor loadings and error variances are obtained. A rescaled Bartlett-corrected statistic is proposed for evaluating the number of factors. Equivariance and invariance of parameter estimates and their standard errors for canonical, varimax, and normalized varimax rotations are discussed. Numerical results illustrate the sensitivity of classical methods and advantages of the proposed procedures.This project was supported by a University of North Texas Faculty Research Grant, Grant #R49/CCR610528 for Disease Control and Prevention from the National Center for Injury Prevention and Control, and Grant DA01070 from the National Institute on Drug Abuse. The results do not necessarily represent the official view of the funding agencies. The authors are grateful to three reviewers for suggestions that improved the presentation of this paper.