职业价值结构初探

本研究通过对教师、管理人员及会计三类人员共307名被试的职业价值评价结果的因素分析,探寻职业价值结构。结果显示：职业价值结构涵盖了11个类别因子,即交往因子、义利因子、挑战因子、环境因子、权力因子、成就因子、创造因子、求新因子、归属因子、责任因子及自认因子,这些因子涉及了职业活动的目标、手段、环境、对象等多方面的价值内容。     

Mutability and propensity in causal selection

We examined differences in causal ratings of 1 factor depending on the mutability (defined as the ease with which a factor can be imagined to be different) and causal propensity (defined as the likelihood that the event would occur in the presence of a factor) of another factor that conjoined to produce the event. In 3 studies, causal ratings of the target factor depended on the interaction of mutability and propensity of the other factor. When the other factor was high in mutability, ratings of the target decreased as the propensity of the contributing factor increased, but when the other was low in mutability, ratings of the target increased as the propensity of the contributing factor increased. Mediation analysis indicated that mutability and propensity affected causal ratings by determining the comparison against which the event was considered. Comparison judgments also mediated beliefs about which factor should have adjusted to the other.     

Convergence in mean square of factor predictors

Sufficient conditions for mean square convergence of factor predictors in common factor analysis are given by Guttman, by Williams, and by Schneeweiss and Mathes. These conditions do not hold for confirmatory factor analysis or when an error variance equals zero (Heywood cases). Two sufficient conditions are given for the three basic factor predictors and a predictor from rotated principal components analysis to converge to the factors of the model for confirmatory factor analysis, including Heywood cases. For certain model specifications the conditions are necessary. The conditions are sufficient for the existence of a unique true factor. A geometric interpretation is given for factor indeterminacy and mean square convergence of best linear factor prediction.     

中国职工组织承诺的结构模型检验

本文对作者所研究的中国职工组织承诺五因素结构模型采用SEM技术进行了检验。结果证明其是理想模型。二阶因子分析表明,五因素模型又可划分为心理因子和社经因子。根据相关分析,得到了五个新的承诺组合模型。     

Psychometric characteristics of the Parenting Scale in a Vietnamese sample

The Parenting Scale (PS) is a well‐established instrument for measuring discipline practices in Western populations. However, whether the PS is a valid and reliable measure in Eastern populations is not known. Thus, this study examined the psychometric properties of the PS in a sample of 433 Vietnamese parents of children aged 2–7 years. Confirmatory factor analyses (CFAs) examined the commonly used Reitman et al.'s two‐factor and Rhoades and O'Leary's three‐factor solutions. Neither factor structure fit the data. An exploratory factor analysis identified a 12‐item one‐factor and 14‐item two‐factor solutions that overlapped substantially with established factor structures. The one‐factor solution reflected Lax/Overreactive parenting and the two‐factor solution consisted of Lax/Overreactive and Hostile subscales. The factor structures were confirmed via multigroup CFA. Internal consistencies were acceptable and ranged between .70 and .85. Each factor was positively associated with parent anger, dysfunctional cognitions about child behaviour, and externalising child behaviour problems. However, when entered simultaneously in a regression, Hostile discipline was not uniquely associated with child behaviour. Overall, results support the potential utility of the 12‐item one‐factor PS as a measure of dysfunctional parenting practices for Vietnamese parents.     

Parceling Cannot Reduce Factor Indeterminacy in Factor Analysis: A Research Note

Parceling—using composites of observed variables as indicators for a common factor—strengthens loadings, but reduces the number of indicators. Factor indeterminacy is reduced when there are many observed variables per factor, and when loadings and factor correlations are strong. It is proven that parceling cannot reduce factor indeterminacy. In special cases where the ratio of loading to residual variance is the same for all items included in each parcel, factor indeterminacy is unaffected by parceling. Otherwise, parceling worsens factor indeterminacy. While factor indeterminacy does not affect the parameter estimates, standard errors, or fit indices associated with a factor model, it does create uncertainty, which endangers valid inference.

     

Model‐related factor score predictors for confirmatory factor analysis

The present paper introduces model‐related (MR) factor score predictors, which reflect specific aspects of confirmatory factor models. The development is mainly based on Schönemann and Steiger's regression score components, but it can also be applied to the factor score coefficients. It is shown that the rotation of factor score predictors has no impact on the covariance matrix reproduced from the corresponding regression component patterns. Thus, regression score components or factor score coefficients can be rotated in order to obtain the required properties. This idea is the basis for MR factor score predictors, which are computed by means of a partial Procrustes rotation towards a target pattern representing the interesting properties of a confirmatory factor model. Two examples demonstrate the construction of MR factor score predictors reflecting specific constraints of a factor model.     

Descriptive axioms for common factor theory,image theory and component theory

Through an extension of work by Guttman, common factor theory, image theory, and component theory are derived from distinct minimum subsets of assumptions chosen out of a set of five possible assumptions. It is thence shown that the problem of indeterminacy of factor scores in the common factor model is precisely reflected in the problem of the non-orthogonality of anti-images. Indeed, image scores are determinate for the same reason that the usual estimates of factor scores are determinate, and image scores cannot be used as though they were factor scores for the same reason that factor score estimates cannot be used as though they were factor scores.     

Assessing stress in cancer patients: a second-order factor analysis model for the Perceived Stress Scale

Using the Perceived Stress Scale (PSS), perceptions of global stress were assessed in 111 women following breast cancer surgery and at 12 and 24 months later This is the first study to factor analyze the PSS. The PSS data were factor analyzed each time using exploratory factor analysis with oblique direct quartimin rotation. Goodness-of-fit indices (root mean square error of approximation [RMSEA]), magnitude and pattern of factor loadings, and confidence interval data revealed a two-factor solution of positive versus negative stress items. The findings, replicated across time, also indicate factor stability. Hierarchical factor analyses supported a second-order factor of "perceived stress." This alternative factor model of the PSS is presented along with observations regarding the measure's use in cancer research.     

Factorial analysis of Thurstone's seven primary abilities

Intercorrelation coefficients among Thurstone's seven primary mental abilities scores were obtained from scores of 170 freshmen engineering students on the experimental edition of thePrimary Mental Abilities Tests. These correlation coefficients were factored to four factors, interpreted as a general factor, a reasoning factor, a verbal factor, and, tentatively, a specific memory factor. The finding of a general factor for a college population corroborates the Thurstones' finding of a general factor for eighth-grade children.     

The influence of ADHD-hyperactivity/impulsivity symptoms on the development of oppositional defiant disorder symptoms in a 2-year longitudinal study

The structural relations among ADHD–inattention (IN), ADHD–hyperactivity/impulsivity (H/I), and oppositional defiant disorder (ODD) factors were examined in a 2-year longitudinal study with 752 children. Structural equation procedures showed that higher scores on the H/I factor in Year 1 were associated with higher scores on ODD factor in Years 2 and 3. Higher scores on the H/I factor in Year 2 were also associated with higher scores on ODD factor in Year 3. The ODD factor did not predict the H/I and IN factors in subsequent years. The IN factor did not predict the ODD and H/I factors in subsequent years and the H/I factor did not predict the IN factor. The ability of the H/I factor to predict the subsequent ODD factor occurred even after taking into account the ability of the ODD, H/I, and IN factors to predict themselves across time. These results suggest that the H/I aspect of ADHD influences the development of ODD behavior.     

Personality and religion: Applying cattell’s model among secondary school pupils

A sample of 1,070 secondary school pupils between the ages of eleven and eighteen years completed the High School Personality Questionnaire alongside the Francis Scale of Attitude toward Christianity. The data demonstrate that religiosity is significantly correlated with five of the fourteen personality factors and with two of the four second-order factors. A positive attitude toward Christianity is associated with high scores on factor G (conformity), factor I (tendermindedness) and factor Q3 (self discipline), and low scores on factor E (submissiveness), factor F (sobriety), second-order factor of extraversion (indicating a relationship with introversion), and second-order factor of tough poise (indicating a relationship with emotionality).     

Additional factorial evidence of construct validity for the Visual Similes Test II with scores from a sample of African-American children

The Visual Similes Test II was designed to measure the construct of arousal. This study investigated its factor structure with scores from a sample of 154 African-American elementary school children (7 to 10 years). The initial factor structure was examined using principal axis factor analysis with the promax rotation. Confirmatory factor analysis was then used to evaluate the model-fit of the data with the hypothesized hierarchical model. Results provided support for the two-factor structure in the principal axis factor analysis and the model-fit of the hypothesized model in the confirmatory factor analysis.     

COMMENTS ON FACTORING DICHOTOMOUS SCORE MATRICES

The fact that the Holley-Guilford G index is a mean cross product between individuals has two implications. First, standard procedures are available for the estimation of R factor loadings. Second, the factor space contains a factor of means. This factor is not unique when item polarities are arbitrary. The factor structure in such cases is a result of both qualitative and quantitative interindividual similarity.     

Mixture Factor Analysis for Approximating a Nonnormally Distributed Continuous Latent Factor With Continuous and Dichotomous Observed Variables

Mixture factor analysis is examined as a means of flexibly estimating nonnormally distributed continuous latent factors in the presence of both continuous and dichotomous observed variables. A simulation study compares mixture factor analysis with normal maximum likelihood (ML) latent factor modeling. Different results emerge for continuous versus dichotomous outcomes. For dichotomous outcomes, normal ML path estimates have bias that worsens as latent factor skew/kurtosis increases and does not diminish as sample size increases, whereas the mixture factor analysis model produces nearly unbiased estimators as sample sizes increase (500 and greater) and offers near nominal coverage probability. For continuous outcome variables, both methods produce factor loading estimates with minimal bias regardless of latent factor skew, but the mixture factor analysis is more efficient. The method is demonstrated using data motivated by a study on youth with cystic fibrosis examining predictors of treatment adherence. In summary, mixture factor analysis provides improvements over normal ML estimation in the presence of skewed/kurtotic latent factors, but due to variability in the estimator relating the latent factor to dichotomous outcomes and computational issues, the improvements were only fully realized, in this study, at larger sample sizes (500 and greater).     

二阶因素模型的测量等价性检验——以大学生网络利他行为量表为例

与一阶因素模型相比,二阶因素模型具有较多优点,但二阶因素模型的测量等价性检验要更复杂,它需要依次进行七个不同水平的检验：形等价、一阶弱等价、二阶弱等价、一阶强等价、二阶强等价、二阶严等价和一阶严等价。低水平的等价性满足之后,才能进行更为严格的高一水平的等价性检验。运用均值和协方差结构（MACS）模型对大学生网络利他行为量表（IABSU）进行二阶因素模型的测量等价性检验,结果表明,IABSU具有跨地域的完全一阶、二阶严等价性。