<p>Research into how different life events shape individual religiosity has a long history within sociology. However, some scholars have begun to question whether research in this area has methodologically justified making strong causal claims. In an effort to re-center religion within the field of sociological concerns, quantitative sociologists of religion have tended to over-state the meaning of their statistical relationships and this has led to many of their causal assumptions being unstated and/or untested in their analyses. The advances in causal statistical modeling and counterfactually grounded analyses has led to the development of statistical models that are better able to establish causal relationships. It is time to begin implementing these approaches within the sociology of religion. This more rigorous statistical approach runs the risk of demonstrating that social life’s influence on religion may be less impressive than was previously thought. But researchers in this area must take this risk to develop a better sense of the real effects of society on religion. This in turn will provide a better foundation for developing theories of religion’s role in our modern world. </p><p> One way in which sociologists of religion can improve their causal modeling strategies is through the use of longitudinal data and methods. In recent years there has been a significant increase in the availability of large-scale longitudinal data that collects information on respondents’ religious belief, practice, and belonging. With these data, scholars interested in religious change can move away from their reliance on comparing individuals to one another – a constraint of cross-sectional data – and begin to analyze how certain life course events may lead to change in individual religiosity. I revisit two important areas within the sociology of religion –the relationship between family formation and religious service attendance and the effects of educational achievement on religious beliefs and practices – to assess whether these relationships can be considered causal in light of results from longitudinal statistical models. By implementing longitudinal models, I am able to directly assess whether between-individual differences or individual change over time is driving the statistical relationships found in my analyses. I will show that the story we thought we knew about how religion responds to family formation and educational attainment changes when these additional statistical tests are brought to bear on the data.</p> / Dissertation
| Identifer | oai:union.ndltd.org:DUKE/oai:dukespace.lib.duke.edu:10161/10472 |
| Date | January 2015 |
| Creators | Schleifer, Cyrus Joseph |
| Contributors | Chaves, Mark |
| Source Sets | Duke University |
| Detected Language | English |
| Type | Dissertation |
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