Development and initial validation of the coaching life skills in sport questionnaire

ObjectivesResearchers have advocated for coaches to intentionally teach life skills to their athletes given the accrued developmental benefits. The purpose of this research was to develop and offer initial evidence of validity and reliability for a measure assessing the extent to which coaches are intentional in their approaches to teaching life skills through sport.DesignUsing two independent samples (n = 623; n = 817), three studies were conducted to develop and initially validate the Coaching Life Skills in Sport Questionnaire (CLSS-Q).MethodIn study one, the scale development and content validity processes of the initial measure were conducted. In study two, the factorial validity of the CLSS-Q was tested through exploratory structural equation modeling and confirmatory factor analyses. Moreover, scale invariance, discriminant and convergent validity, and construct reliability were assessed. In study three, concurrent validity was assessed with the combined sample (N = 1440) using two theoretically linked constructs.ResultsThe results of the three studies provide initial evidence for the validity and reliability of the 5-factor 36-item CLSS-Q.ConclusionsThe CLSS-Q represents a useful scale for researchers interested in examining levels of intentionality in coaches' teaching of life skills through sport. As scale development is an ongoing process, further research is needed to continue to accumulate evidence for the validity and reliability of the CLSS-Q.     

On the power of the test for cluster bias

Cluster bias refers to measurement bias with respect to the clustering variable in multilevel data. The absence of cluster bias implies absence of bias with respect to any cluster‐level (level 2) variable. The variables that possibly cause the bias do not have to be measured to test for cluster bias. Therefore, the test for cluster bias serves as a global test of measurement bias with respect to any level 2 variable. However, the validity of the global test depends on the Type I and Type II error rates of the test. We compare the performance of the test for cluster bias with the restricted factor analysis (RFA) test, which can be used if the variable that leads to measurement bias is measured. It appeared that the RFA test has considerably more power than the test for cluster bias. However, the false positive rates of the test for cluster bias were generally around the expected values, while the RFA test showed unacceptably high false positive rates in some conditions. We conclude that if no significant cluster bias is found, still significant bias with respect to a level 2 violator can be detected with an RFA model. Although the test for cluster bias is less powerful, an advantage of the test is that the cause of the bias does not need to be measured, or even known.     

结构方程模型常用拟合指数检验的实质

拟合指数检验是评价结构方程模型(SEM)的重要环节。从协方差结构分析的角度将SEM与传统的回归模型比较,容易理解为什么SEM需要拟合指数。揭示了目前几种流行的拟合指数检验的实质:基于卡方的绝对拟合指数(如RMSEA)检验的实质是重新设定卡方检验的显著性水平(不同于通常的.05),相对拟合指数(如NNFI和CFI)检验的实质是基于虚模型设定均方(卡方与自由度之比)降低到的比例;在NNFI大于临界值后,报告和检验CFI是不必要的。根据研究结果提出了一些方便实用的拟合检验建议。     

Structural heterogeneity in a binary Pd–Si metallic glass

A Pd₈₁Si₁₉ bulk metallic glassy rod with a diameter of 4.5 mm was produced by water quenching the fluxed alloy. Despite a negative heat of mixing between Pd and Si elements and very simple components constituting the binary Pd–Si glass-forming system, structural heterogeneity was induced either by slow cooling of a liquid or sub-T_g annealing of glassy ribbons. The sub-T_g annealing experiments evidenced that a more ordered amorphous phase emerged from the original glassy matrix. Our work provides an alternative way to tune the microstructure of metallic glasses by subsequent thermal treatment on an as-prepared single glassy phase.     

Structural stability of W2B5 under high pressure

High-pressure structural stability studies have been carried out on tungsten boride W₂B₅ up to maximum pressure of 36 GPa using a Mao-Bell diamond-anvil cell at beamline BR-12 of the ELETTRA synchrotron facility (λ = 0.68881 Å). The hexagonal phase (S.G:P6₃/mmc) of W₂B₅ is stable up to the maximum pressure studied. The bulk modulus is estimated to be ~347 GPa using the Birch–Murnaghan equation of state. The variation of lattice parameters and bond lengths B–B and W–B have been studied and the c-axis is seen to be marginally more compressible than the a-axis.     

Regression among factor scores

Structural equation models with latent variables are sometimes estimated using an intuitive three-step approach, here denoted factor score regression. Consider a structural equation model composed of an explanatory latent variable and a response latent variable related by a structural parameter of scientific interest. In this simple example estimation of the structural parameter proceeds as follows: First, common factor models areseparately estimated for each latent variable. Second, factor scores areseparately assigned to each latent variable, based on the estimates. Third, ordinary linear regression analysis is performed among the factor scores producing an estimate for the structural parameter. We investigate the asymptotic and finite sample performance of different factor score regression methods for structural equation models with latent variables. It is demonstrated that the conventional approach to factor score regression performs very badly. Revised factor score regression, using Regression factor scores for the explanatory latent variables and Bartlett scores for the response latent variables, produces consistent estimators for all parameters.     

Resilience as a Mediator Between Parental Acceptance–Rejection and Depressive Symptoms Among University Students in Turkey

The authors investigated the mediational role of perceived resilience between perceived parental acceptance–rejection and occurrences of depressive symptoms among 384 undergraduate students in Turkey. Results indicated that resilience fully mediated the relationship between depressive symptoms and maternal rejection, whereas resilience partially mediated the relationship between depressive symptoms and paternal rejection for female undergraduates. Interventions that focus directly on the facilitation of psychosocial adaptation among emerging adults, especially those who experience feelings of rejection by their parents, are discussed.     

The Relation of Birth Order,Age of Mother,and Size of Family to Intelligence

Variables thought to be associated with the magnitude of interrelationship observed among the elements in a system of social attitudes were investigated. Subjects (N = 753) were asked to respond to an inventory requesting self-report and background data. Several weeks later, Ss were given two forms of the Social Attitude Scale, a scale tapping the liberalism-conservatism domain. The results indicated that those Ss who reported recent changes in religious, moral, or political attitudes displayed a more highly interconnected system of liberal-conservative attitudes than those who did not. Variables relating to active participation in social affairs tended to be associated with higher levels of attitude system organization. Sex differences were observed, with men displaying higher levels of system organization than women. This relationship held even when participation rates were taken into consideration.     

At the Frontiers of Modeling Intensive Longitudinal Data: Dynamic Structural Equation Models for the Affective Measurements from the COGITO Study

With the growing popularity of intensive longitudinal research, the modeling techniques and software options for such data are also expanding rapidly. Here we use dynamic multilevel modeling, as it is incorporated in the new dynamic structural equation modeling (DSEM) toolbox in Mplus, to analyze the affective data from the COGITO study. These data consist of two samples of over 100 individuals each who were measured for about 100 days. We use composite scores of positive and negative affect and apply a multilevel vector autoregressive model to allow for individual differences in means, autoregressions, and cross-lagged effects. Then we extend the model to include random residual variances and covariance, and finally we investigate whether prior depression affects later depression scores through the random effects of the daily diary measures. We end with discussing several urgent—but mostly unresolved—issues in the area of dynamic multilevel modeling.     

Structural Equation Modeling of Social Networks: Specification,Estimation, and Application

Psychologists are interested in whether friends and couples share similar personalities or not. However, no statistical models are readily available to test the association between personalities and social relations in the literature. In this study, we develop a statistical model for analyzing social network data with the latent personality traits as covariates. Because the model contains a measurement model for the latent traits and a structural model for the relationship between the network and latent traits, we discuss it under the general framework of structural equation modeling (SEM). In our model, the structural relation between the latent variable(s) and the outcome variable is no longer linear or generalized linear. To obtain model parameter estimates, we propose to use a two-stage maximum likelihood (ML) procedure. This modeling framework is evaluated through a simulation study under representative conditions that would be found in social network data. Its usefulness is then demonstrated through an empirical application to a college friendship network.