Examining Temporal Stability of Scale Validity in Longitudinal Studies

A method for examining invariance in validity of multiple-component instruments in repeated measure designs is outlined. The approach is developed within the framework of covariance structure modeling and is applicable for purposes of ascertaining temporal stability in scale validity. In addition, the procedure provides a range of plausible values in a population under investigation for the change in composite validity across longitudinal assessment occasions. The proposed method can also be used to examine possible sources of lack of validity invariance, and is illustrated with a pair of examples.     

Cross Racial Identity Scale (CRIS) Scores: Stability and Relationships With Psychological Adjustment

A humor test composed of cartoons, comic strips, and jokes was administered to 30 college couples (26 single, 4 married) who rated them for humor. Subjects also stated how much they loved and liked their partner, their probability of marrying the partner, and filled out Rubin's Liking and Love Scales. The hypotheses were that similarity of rating of the humorous stimuli would be associated with loving, liking, and predisposition to marry. Hypotheses were confirmed.     

Stability of the Spanish version of the five-item Francis Scale of Attitude toward Christianity

The aim of this study was to establish test-retest reliability of a Spanish version of the Francis Scale of Attitude toward Christianity (Campo-Arias, Oviedo, & Cogollo, 2009) among adolescent students in Cartagena, Colombia. A group of ninth grade students from two public schools in Colombia (N = 157) completed the five-item scale. Cronbach's alphas were .74 and .76 in the first and second administrations, respectively. Both Pearson's rho and intra-class correlation coefficient were .69. A Spanish translation of the 5-item scale had consistent stability over four weeks.     

Logistic Regression

Logistic regression has probably been underutilized in clinical investigations of personality because of its relatively recent development (dictated by the need for computer programs to obtain maximum likelihood estimates), and the fact that use has been largely confined to the fields of biostatistics, epidemiology, and economics Its use should be given serious consideration when the outcome of interest is dichotomous (or polychotomous) in nature and the predictors of interest may be categorical or continuous. The logit transformation is quite tractable mathematically, and it embodies the notion of threshold, which may have relevance for many of the variables that are of interest to investigators in the field of personality. Furthermore, investigators with experience in multiple linear regression or contingency table analysis should have little trouble in transitioning to logistic regression. Logistic regression programs are readily available in the major statistical packages, all of which provide fairly standard output.     

Leadership Change and Organizational Regression

Psychotherapists have long recognized the therapeutic power of the here-and-now, but few have attempted to account for this power or provide a rationale for its efficacy. This leaves one of the most central concepts of group therapy without an adequate theoretical base. A major reason for this is the insufficiency of our Western assumptions of time and causality. These ascribe all human behaviors and cognitions to prior influences of one sort or another, making a true focus upon the present almost impossible. Even those who value the here-and-now are inevitably drawn into the past, because the Western philosophy underlying mainstream psychology makes this seem only logical. A theoretical revolution is therefore proposed that draws upon the lessons of history, the insights of other cultures, and developments in physics. This approach is then applied to group therapy, and specific advantages over conventional theorizing are noted.     

Improved Regression Calibration

The likelihood for generalized linear models with covariate measurement error cannot in general be expressed in closed form, which makes maximum likelihood estimation taxing. A popular alternative is regression calibration which is computationally efficient at the cost of inconsistent estimation. We propose an improved regression calibration approach, a general pseudo maximum likelihood estimation method based on a conveniently decomposed form of the likelihood. It is both consistent and computationally efficient, and produces point estimates and estimated standard errors which are practically identical to those obtained by maximum likelihood. Simulations suggest that improved regression calibration, which is easy to implement in standard software, works well in a range of situations.     

Harmonic and rhythmic influences on musical expectancy

The effects of harmony and rhythm on expectancy formation were studied in two experiments. In both studies, we generated musical passages consisting of a melodic line accompanied by four harmonic (chord) events. These sequences varied in their harmonic content, the rhythmic periodicity of the three context chords prior to the final chord, and the ending time of the final chord itself. In Experiment 1, listeners provided ratings for how well the final chord in a chord sequence fit their expectations for what was to come next; analyses revealed subtle changes in ratings as a function of both harmonic and rhythmic variation. Experiment 2 extended these results; listeners made a speeded reaction time judgment on whether the final chord of a sequence belonged with its set of context chords. Analysis of the reaction time data suggested that harmonic and rhythmic variation also influenced the speed of musical processing. These results are interpreted with reference to current models of music cognition, and they highlight the need for rhythmical weighting factors within the psychological representation of tonal/pitch information.     

Determination of the Regression Coefficients and Their Associated Standard Errors in Hierarchical Regression Analysis

Hierarchical regression analysis is potentially a very useful statistical technique for establishing the significance of sets of predictor variables. However, when a hierarchical analysis which is based on theory is performed, some estimation procedures for the regression coefficients and their associated standard errors are potentially inappropriate. Specifically, the hierarchical regression equations, the incremental or hierarchical tests, and the parameter estimation of this procedure may not correspond. This problem is investigated by the development of four approaches (simultaneous, stagewise, orthogonal, and hierarchical) of estimation to the analysis. For each method, regression, coefficient estimators and their standard errors are determined. By comparison of these approaches, the use of orthogonalized sets of predictor variates or a modification to a series of simultaneous analyses are recommended as the most sensible technique for a theory driven hierarchical analysis.     

Stability of body image concerns among chinese adolescents: nine-month test-retest reliabilities of the Negative Physical Self Scale

This research assessed the stability of specific body image concerns among Chinese adolescents. A sample of 216 boys and 375 girls completed the Negative Physical Self Scale, a 38-item measure of body image concerns developed specifically for use in Chinese samples. Participants returned nine months later to complete the same scale. Bivariate correlation analyses within each sex obtained good test-retest reliabilities (r = .48 to r = .78). Findings indicate that body image concerns of Chinese adolescents, especially those of girls, are relatively stable over a nine-month interval.     

On the Use of Nonparametric Regression in Assessing Parametric Regression Models

We develop a new method for assessing the adequacy of a smooth regression function based on nonparametric regression and the bootstrap. Our methodology allows users to detect systematic misfit and to test hypotheses of the form “the proposed smooth regression model is not significantly different from the smooth regression model that generated these data.” We also provide confidence bands on the location of nonparametric regression estimates assuming that the proposed regression function is true, allowing users to pinpoint regions of misfit. We illustrate the application of the new method, using local linear nonparametric regression, both where an error model is assumed and where the error model is an unknown non-stationary function of the predictor.     

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.     

用安戈夫方法对网络成瘾与网络游戏成瘾的界定

旨在探讨网络成瘾与网络游戏成瘾的界定问题。采用标准设定中最为广泛使用的安戈夫方法对网络成瘾和网络游戏成瘾分别进行评定,最终得到的网络成瘾的界定量表,共有12个项目,界定分数为8,即受试者在12个项目中有8项作出肯定回答即被界定为网络成瘾;网络游戏成瘾的界定量表,共有10个项目,界定分数为7,即受试者在10个项目中有7项作出肯定回答即被界定为网络游戏成瘾。     

Regression to the mean and football wagers

Football performances are an imperfect measure of abilities, and consequently exaggerate differences in abilities. The skills of those football teams that perform the best and the worst are not really that far from average; thus their future performances regress to the mean. Betting data indicate that gamblers do not fully account for this regression. Copyright © 2002 John Wiley & Sons, Ltd.     

Regression estimation and post-stratification in factor analysis

Regression estimation and poststratification are methods used in survey sampling to estimate a population mean, when additional information is available for some auxiliary variables. The extension of these methods to factor analysis is considered. These methods may be used either to improve the efficiency of estimation or to adjust for the effects of nonrandom selection. The estimation procedure may be formulated in a LISREL framework.The author is grateful to the referees for their comments.     

Regression and reparation in religious experience and creativity

The purpose of this article is to examine regressive processes that take place in religious experience, and, by comparing its stages to similar stages in creativity, demonstrate how the experience can be reparative rather than pathological.He has written numerous articles in the area of psychology and religion, and his bookThe Recovery of Self has been recently published by Paulist Press.     

自我韧性量表与Connor-Davidson韧性量表的应用比较

目的:考察自我韧性量表中文版的心理测量学指标,探讨其与Connor-Davidson韧性量表的关系,比较两者在中国人群中的应用效果。方法:在社区人群中施测自我韧性量表和Connor-Davidson韧性量表的中文版,以及自尊量表、生活满意度指数A问卷、大五人格问卷。结果:自我韧性量表中文版的内部一致性系数为0.77,略低于Connor-Davidson韧性量表。自我韧性量表与Connor-Davidson韧性量表的相关系数为0.61。在以自尊、生活满意度、大五人格为效标时,偏相关分析表明控制了Connor-Davidson韧性量表得分后,自我韧性量表与效标的相关未达到显著水平(除大五人格的外向性维度外);但控制了自我韧性量表得分后,Connor-Davidson量表与效标的相关仍达到显著水平(除开放性维度外)。结论:在我国人群的应用中,Connor-Davidson韧性量表优于自我韧性量表,是值得推广的韧性测量工具。