American Sociological Association

Search

Search

The search found 149 results in 0.503 seconds.

Search results

  1. Comment: Bayes, Model Uncertainty, and Learning from Data

    The problem of model uncertainty is a fundamental applied challenge in quantitative sociology. The authors’ language of false positives is reminiscent of Bonferroni adjustments and the frequentist analysis of multiple independent comparisons, but the distinct problem of model uncertainty has been fully formalized from a Bayesian perspective.
  2. Comment: Some Challenges When Estimating the Impact of Model Uncertainty on Coefficient Instability

    I once had a colleague who knew that inequality was related to an important dependent variable. This colleague knew many other things, but I focus on inequality as an example. It was difficult for my colleague to know just how to operationalize inequality. Should it be the percentage of income held by the top 10 percent, top 5 percent, or top 1 percent of the population? Should it be based on the ratio of median black income to median white income, or should it be the log of that ratio? Should it be based on the Gini index, or perhaps the Theil index would be better?
  3. We Ran 9 Billion Regressions: Eliminating False Positives through Computational Model Robustness

    False positive findings are a growing problem in many research literatures. We argue that excessive false positives often stem from model uncertainty. There are many plausible ways of specifying a regression model, but researchers typically report only a few preferred estimates. This raises the concern that such research reveals only a small fraction of the possible results and may easily lead to nonrobust, false positive conclusions. It is often unclear how much the results are driven by model specification and how much the results would change if a different plausible model were used.
  4. Estimating Heterogeneous Treatment Effects with Observational Data

    Individuals differ not only in their background characteristics but also in how they respond to a particular treatment, intervention, or stimulation. In particular, treatment effects may vary systematically by the propensity for treatment. In this paper, we discuss a practical approach to studying heterogeneous treatment effects as a function of the treatment propensity, under the same assumption commonly underlying regression analysis: ignorability.

  5. Qualitative Comparative Analysis in Critical Perspective

    Qualitative comparative analysis (QCA) appears to offer a systematic means for case-oriented analysis. The method not only offers to provide a standardized procedure for qualitative research but also serves, to some, as an instantiation of deterministic methods. Others, however, contest QCA because of its deterministic lineage. Multiple other issues surrounding QCA, such as its response to measurement error and its ability to ascertain asymmetric causality, are also matters of interest.

  6. Comparing Regression Coefficients Between Same-sample Nested Models Using Logit and Probit: A New Method

    Logit and probit models are widely used in empirical sociological research. However, the common practice of comparing the coefficients of a given variable across differently specified models fitted to the same sample does not warrant the same interpretation in logits and probits as in linear regression. Unlike linear models, the change in the coefficient of the variable of interest cannot be straightforwardly attributed to the inclusion of confounding variables. The reason for this is that the variance of the underlying latent variable is not identified and will differ between models.

  7. Terror, Terrorism, Terrorists

    The terms terror, terrorism, and terrorist do not identify causally coherent and distinct social phenomena but strategies that recur across a wide variety of actors and political situations. Social scientists who reify the terms confuse themselves and render a disservice to public discussion. The U.S. government's own catalogs of terrorist events actually support both claims.

  8. Practicing Intersectionality in Sociological Research: A Critical Analysis of Inclusions, Interactions, and Institutions in the Study of Inequalities

    In this article we ask what it means for sociologists to practice intersectionality as a theoretical and methodological approach to inequality. What are the implications for choices of subject matter and style of work? We distinguish three styles of understanding intersectionality in practice: group-centered, process-centered, and system-centered. The first, emphasizes placing multiply-marginalized groups and their perspectives at the center of the research.

  9. Theory Construction in Qualitative Research: From Grounded Theory to Abductive Analysis

    A critical pathway for conceptual innovation in the social is the construction of theoretical ideas based on empirical data. Grounded theory has become a leading approach promising the construction of novel theories. Yet grounded theory–based theoretical innovation has been scarce in part because of its commitment to let theories emerge inductively rather than imposing analytic frameworks a priori. We note, along with a long philosophical tradition, that induction does not logically lead to novel theoretical insights.

  10. The Feminist Question in Realism

    Feminist standpoint theory and critical realism both offer resources to sociologists interested in making arguments that account for causal complexity and epistemic distortion. However, the impasse between these paradigms limits their utility. In this article, I argue that critical realism has much to gain from a confrontation with feminist theory. Feminist theory’s emphasis on boundary-crossing epistemologies and gendered bodies can help critical realism complicate its notion of the bifurcation between epistemology and ontology.