Handling of clustered or nested data structures requires the use of multilevel modeling techniques. One such multilevel modeling technique is multilevel structural equation modeling (MLSEM). While estimation of indirect effect parameters and standard errors based on the conventional multilevel model (MMM) has been assessed, this is not the case for the use of the MLSEM model for estimating indirect effects. This simulation study was designed to investigate the use of the MLSEM for estimating mediated effects for the “upper-level” mediation model as compared with the MMM. The following conditions were manipulated: number of clusters (G), within-cluster sample size (nj ), intra-class correlation, measurement error in the mediator, and the true value of the mediated effect derived from various patterns of true values for a and b. The generating model entailed an upper-level mediation model for a cluster-randomized trial that included a dichotomous level two independent variable, a cluster-level latent mediator and an individual-level latent dependent variable both with four indicators. Relative parameter and standard error bias, obtained using the MLSEM and the MMM were evaluated and compared. Percent coverage was calculated and compared when PRODCLIN was used to calculate the confidence interval estimates of the ab effect. Finally, Type I error rates for conditions when ab = 0 were assessed and compared. In addition, statistical power for detecting a truly non-zero mediated effect was tallied and compared across models. Results showed that use of the MMM provided inaccurate and misleading parameter and standard error estimates for the estimates of the mediated effect, especially when the true values of a, b and ab were not zero and the measurement error for M was large. However, the MLSEM estimates were also unacceptable in some of the conditions with small values for G and nj. Researchers are encouraged to use the MLSEM for assessing the multilevel mediated effects when either or both paths a and b are expected to be non-zero, if G is at least 40 and nj is also greater than 40. Results are presented and discussed along with implications for applied researchers intending to assess mediated effect with clustered data. / text

Although social capital had been found to solve collective action problems, social capital at work or workplace social capital has only recently begun to be researched. This is noteworthy given that most of our waking hours are spent in the workplace. While workplace social capital is suggested to improve workplace performance, job satisfaction had been found to improve workplace performance. However, workplace social capital and job satisfaction have never been examined together with regard to workplace performance. Furthermore, most studies on workplace performance have focused on developed countries with evidence from developing countries is lacking. The aims of this thesis were to investigate 1) whether workplace social capital affects job satisfaction; 2) the relationship of social capital, job satisfaction and workplace performance; 3) whether individual characteristics differ in determining job satisfaction in developed and developing countries; and 4) whether context of organisations in developed and developing countries differ in determining the relationship of social capital, job satisfaction and workplace performance. To achieve those aims, this thesis selects two sets of secondary data representing developed countries: EWCS2010 in Europe combining workers with their regions and countries and WERS2011 in Britain linking workers to their workplaces; while primary data froma developing country have been gathered from public hospitals in Indonesia associating workers with workplaces. As such, this thesis exploits two approaches using structural equation modelling in multilevel models. First, the customary Macro-micro approach is used to examine the relationship between workplace social capital and job satisfaction treating both variables as latent constructs. Second, the less common micro-Macro approach is exercised to investigate the relationship between workplace social capital, job satisfaction and workplace performance. Results from developed countries show that workplace social capital is positively associated with individual outcomes such as job satisfaction and well-being even in times of financial crisis. Comparing the results between developed and developing countries, workplace social capital is positively significantly associated with job satisfaction in Britain and in Indonesia. With regard to higher level outcomes, workplace social capital is associated with better financial performance, while job satisfaction is associated with higher quality in British general industry. Turning to results from Indonesia, workplace social capital is associated with lower expenditure per bed; job satisfaction, however, failed to be associated with any workplace performance measures. Several individual and workplace characteristics in both developed and developing countries have similar influences on job satisfaction and workplace performance. Nevertheless, there are some contrasting results regarding the influence of those characteristics in developed and developing countries.