心理治疗的会谈间体验对治疗效果的影响——来自追踪研究的证据

采用多层线性分析方法,在短程心理咨询的连续会谈中检验来访者的会谈间体验对咨询效果的影响。以36名个案、151次会谈为样本,结果发现,来访者的症状总体呈线性下降趋势;不同来访者症状变化的速率存在个体差异,会谈间体验的情绪因子能解释症状变化速率总变异的40.79%。结论：在短程心理咨询中,来访者想起咨询会谈或/和咨询师时的情绪体验能显著预测咨询效果。     

Analyzing temporal patterns of infant sleep and negative affective behavior: a comparison between different statistical models

Objective

Variability in infant sleep and negative affective behavior (NAB) is a developmental phenomenon that has long been of interest to researchers and clinicians. However, analyses and delineation of such temporal patterns were often limited to basic statistical approaches, which may prevent adequate identification of meaningful variation within these patterns. Modern statistical procedures such as additive models may detect specific patterns of temporal variation in infant behavior more effectively.

Method

Hundred and twenty-one mothers were asked to record different behaviors of their 4–44 weeks old healthy infants by diaries for three days consecutively. Circadian patterns as well as individual trajectories and day-to-day variability of infant sleep and NAB were modeled with generalized linear models (GLMs) including a linear and quadratic polynomial for time, a GLM with a polynomial of the 8th order, a GLM with a harmonic function, a generalized linear mixed model (GLMM) with a polynomial of the 8th order, a generalized additive model, and a generalized additive mixed model (GAMM).

Results

The semi-parametric model GAMM was found to fit the data of infant sleep better than any other parametric model used. GLMM with a polynomial of the 8th order and GAMM modeled temporal patterns of infant NAB equally well, although the GLMM exhibited a slightly better model fit while GAMM was easier to interpret. Besides the well-known evening clustering in infant NAB we found a significant second peak in NAB around midday that was not affected by the constant decline in the amounts of NAB across the 3-day study period.

Conclusion

Using advanced statistical procedures (GAMM and GLMM) even small variations and phenomena in infant behavior can be reliably detected. Future studies investigating variability and temporal patterns in infant variables may benefit from these statistical approaches.     

Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis

A social network perspective can bring important insight into the processes that shape human behavior. Longitudinal social network data, measuring relations between individuals over time, has become increasingly common—as have the methods available to analyze such data. A friendship duration model utilizing discrete-time multilevel survival analysis with a multiple membership random effect structure is developed and applied here to study the processes leading to undirected friendship dissolution within a larger social network. While the modeling framework is introduced in terms of understanding friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school students, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed.     

Neighborhood Predictors of Intimate Partner Violence: A Theory‐Informed Analysis Using Hierarchical Linear Modeling

Due to high prevalence rates and deleterious effects on individuals, families, and communities, intimate partner violence (IPV) is a significant public health problem. Because IPV occurs in the context of communities and neighborhoods, research must examine the broader environment in addition to individual‐level factors to successfully facilitate behavior change. Drawing from the Social Determinants of Health framework and Social Disorganization Theory, neighborhood predictors of IPV were tested using hierarchical linear modeling. Results indicated that concentrated disadvantage and female‐to‐male partner violence were robust predictors of women's IPV victimization. Implications for theory, practice, and policy, and future research are discussed.     

试论骨科辐射效应的线性与非线性关系

放射界对于辐射效应一直沿用线性无阈理论,但近年来,低剂量辐射效应却让其表现出非线性特征。而且对于骨折以及骨科其他疾病来说不同剂量辐射所产生的效应是不同的,即其在骨科中也存在线性与非线性的对立统一,只有认清这两者的辩证关系,才能抓住其本质,最终产生深远的意义和临床应用。     

Exploring the effects of congruence and Holland’s personality codes on job satisfaction: An application of hierarchical linear modeling techniques

This study applied hierarchical linear modeling to investigate the effect of congruence on intrinsic and extrinsic aspects of job satisfaction. Particular focus was given to differences in job satisfaction by gender and by Holland’s first-letter codes. The study sample included nationally represented 1462 female and 1280 male college graduates who held full-time jobs in 2000. Congruence was measured by using actual occupational and academic major codes. After controlling for the differences across three-letter Holland personality codes, results indicate that job satisfaction was largely a function of individual attributes rather than disparities in personality types. Holland’s congruence was most effective in explaining intrinsic dimensions of job satisfaction for females, and less effective for extrinsic job satisfaction for both genders. Social females and males were less satisfied with extrinsic satisfaction, while Conventional and Social females were more satisfied with intrinsic features in their vocational environments.     

全息项目因素分析在心理学研究中的应用

文章首先指出了经典线性因素分析的种种局限;然后介绍了一种基于“被试—项目矩阵”而非仅仅协方差矩阵或相关矩阵的全息项目因素分析,该方法能克服经典线性因素分析的种种局限,在心理学研究中尤其是人格研究中有着其他因素分析方法不可替代的作用。     

Poisson Multilevel Models with Small Samples

Recent methodological studies have investigated the properties of multilevel models with small samples. Previous work has primarily focused on continuous outcomes and little attention has been paid to count outcomes. The estimation of count outcome models can be difficult because the likelihood has no closed-form solution, meaning that approximation methods are required. Although adaptive Gaussian quadrature (AGQ) is generally seen as the gold standard, its comparative performance has been investigated with larger samples. AGQ approximates the full likelihood, a function that is known to produce biased estimates with small samples with continuous outcomes. Conversely, penalized quasi-likelihood (PQL) is considered to be a less desirable approximation; however, it can approximate the restricted likelihood function, a function that is known to perform well with smaller samples with continuous outcomes. The goal of this paper is to compare the small sample bias of full likelihood methods to the linearization bias of PQL with restricted likelihood. Simulation results indicate that the linearization bias of PQL is preferable to the finite sample bias of AGQ with smaller samples.     

Examining career-related mentoring and managerial performance across cultures: A multilevel analysis

The benefits of the mentoring relationship for protégés have been a primary focus in the mentoring literature. Researchers have recently begun to examine how mentoring can benefit the mentor. The purpose of the present study is to examine whether direct report-ratings of a manager’s career-related mentoring behaviors are related to boss-ratings of that manager’s performance. In addition, this study assesses whether the cultural background of the manager moderates the career-related mentoring-performance relationship via multilevel methodology. Results reveal that managers who are rated by their direct reports as engaging in career-related mentoring behaviors are perceived as better performers by their bosses. Moreover, the GLOBE societal culture dimension of Performance Orientation was a significant cross-level moderator of the career-related mentoring-performance relationship. Implications for the practice of mentoring in cross-cultural contexts across multiple disciplines are discussed.     

The generalized Logit-Linear Item Response Model for Binary-Designed Items

This paper introduces the generalized logit-linear item response model (GLLIRM), which represents the item-solving process as a series of dichotomous operations or steps. The GLLIRM assumes that the probability function of the item response is a logistic function of a linear composite of basic parameters which describe the operations, and the coefficients depend on three design matrices X, Y and Z. The GLLIRM provides a tool for testing hypotheses on the item-solving process and generalizes existing models. An empirical application is included, in which the model is applied to evaluate sources of difficulty and pairwise item interactions in a logical analysis test. This research was supported by the Comunidad de Madrid grant CCG06-UAM/ESP-0043.