Assessing Change in Social Support During Late Life

The purpose of this study is to evaluate change in 14 measures of social support with data provided by a nationwide longitudinal study of older adults. The findings reveal that fairly substantial change took place during the three-year follow-up period. More important, the data indicate that change is not uniform or systematic across the entire study sample. Instead, there appears to be considerable individual-level change taking place. The implications of these findings for the development of conceptual models as well as support-based interventions are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68866/2/10.1177_0164027599214002.pd

A 6-item scale for overall, emotional, and social loneliness: Confirmatory tests on survey data

Loneliness is an indicator of social well-being and pertains to the feeling of missing an intimate relationship (emotional loneliness) or missing a wider social network (social loneliness). The 11-item De Jong Gierveld Loneliness Scale has proved to be a valid and reliable measurement instrument for overall, emotional, and social loneliness, although its length has sometimes rendered it difficult to use in large surveys. In this study, the authors empirically tested a shortened version of the scale on data from two surveys (N = 9,448). Confirmatory factor analyses confirmed the specification of two latent factors. Congruent validity and the relationship with determinants (partner status, health) proved to be optimal. The 6-item De Jong Gierveld Loneliness Scale is a reliable and valid measurement instrument for overall, emotional, and social loneliness that is suitable for large surveys

Corporate image: a service recovery perspective

This article explores direct and indirect antecedents that contribute to corporate image formation in a service recovery context. Two studies were carried out in Egypt. Study 1 comprises 29 semistructured interviews with complainants of mobile phone network service providers in Egypt. Study 2 encompasses a mail survey of another 437 complainants. Findings reveal the importance of perceived justice, namely, interactional justice, in corporate image formation, as well as the mediating role of satisfaction with service recovery in the perceived justice-corporate image relationship. Results also reveal two empirical relationships: problem solving as a determinant of distributive justice and follow-up as a driver of procedural justice. Accordingly, this study contributes to the service field by providing the first empirical evaluation of new direct and indirect antecedents of corporate image formation in a service recovery context. Managerial recommendations are provided that encourage service practitioners to emphasize perceived justice and satisfaction with a service recovery process to enhance the company’s image. Additionally, companies should invest in implementing problem solving and follow-up as service recovery strategies since both significantly enhance perceived justice

Classical Models for Twin Data

The classical models ACE and ADE were used in the 1990s to estimate heredity of a phenotype from data on monozygotic and dizygotic twins. These models are extended to a model called ACDE with four parameters instead of only three. It is showed how these models can be easily estimated by maximum likelihood. The models and methods are extended to two populations in which the heredity is the same in both populations. Examples are given to estimate the heredity of BMI using twin data from the UK and Australia

Classical Models for Twin Data : The Case of Categorical Data

The classical models ACE and ADE were used in the 1990's to estimate heredity of a phenotype from data on monozygotic and dizygotic twins. The author extended these models to a model called ACDE with four parameters instead of only three. In that paper, the data were assumed to be continuous. This paper considers the same models in the case where the data is categorical. It is showed how these models can be estimated by maximum likelihood. An example is given based on twin data on BMI from the UK. This is the same data as in the previous paper but in categorized form

2. Session (31.03.2003)

Content: Examples; Exploratory Factor Analysi

4. Session (31.03.2003)

Content: Models for Longitudinal Data; Examples; Path Diagram for Stability of Alienation; Antocorrelated Measurement Erro

Pairwise likelihood estimation for factor analysis models with ordinal data

Pairwise maximum likelihood (PML) estimation method is developed for factor analysis models with ordinal data and fitted both in an exploratory and confirmatory set-up. The performance of the method is studied via simulations and comparisons with full information maximum likelihood (FIML) and three-stage limited information estimation methods, namely the robust unweighted least squares (3S-RULS) and robust diagonally weighted least squares (3SRDWLS). The advantage of PML over FIML is mainly computational. Unlike PML estimation, the computational complexity of FIML estimation increases either with the number of factors or with the number of observed variables depending on the model formulation. Contrary to 3S-RULS and 3S-RDWLS estimation, PML estimates of all model parameters are obtained simultaneously and the PML method does not require the estimation of a weight matrix for the computation of correct standard errors. The simulation study on the performance of PML estimates and estimated asymptotic standard errors investigates the effect of different model and sample sizes. The bias and mean squared error of PML estimates and their standard errors are found to be small in all experimental conditions and decreasing with increasing sample size. Moreover, the PML estimates and their standard errors are found to be very close to those of FIML