Attachment to parents and to God: a panel-data approach

ABSTRACT

Research at the nexus of attachment theory and religion has generally been constrained both by data limitations and by a view of attachment style as fixed early in life. I use three waves of data to test key hypotheses from this literature in new ways. Closeness to mother and closeness to father serve as proxies for attachment to parents and closeness to God serves as a proxy for attachment to God. The correspondence hypothesis predicts that people who feel closer to their parents feel closer to God, the compensation hypothesis predicts that people lacking a parent feel closer to God, and the socialized correspondence hypothesis predicts that people with nonreligious parents will feel less close to God if they feel closer to their parents. I find strong evidence in favor of the correspondence hypothesis, but I find no evidence in favor of the compensation hypothesis or the socialized correspondence hypothesis.     

Estimating Age-Based Developmental Trajectories Using Latent Change Score Models Based on Measurement Occasion

Abstract

Accelerated longitudinal designs (ALDs) are designs in which participants from different cohorts provide repeated measures covering a fraction of the time range of the study. ALDs allow researchers to study developmental processes spanning long periods within a relatively shorter time framework. The common trajectory is studied by aggregating the information provided by the different cohorts. Latent change score (LCS) models provide a powerful analytical framework to analyze data from ALDs. With developmental data, LCS models can be specified using measurement occasion as the time metric. This provides a number of benefits, but has an important limitation: It makes it not possible to characterize the longitudinal changes as a function of a developmental process such as age or biological maturation. To overcome this limitation, we propose an extension of an occasion-based LCS model that includes age differences at the first measurement occasion. We conducted a Monte Carlo study and compared the results of including different transformations of the age variable. Our results indicate that some of the proposed transformations resulted in accurate expectations for the studied process across all the ages in the study, and excellent model fit. We discuss these results and provide the R code for our analysis.