American Sociological Association

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  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. 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.

  6. Telephone Versus Face-to-Face Interviews: Mode Effect on Semistructured Interviews with Children

    Usually, semistructured interviews are conducted face-to-face, and because of the importance of personal contact in qualitative interviews, telephone interviews are often discounted. Missing visual communication can make a telephone conversation appear less personal and more anonymous but can also help prevent some distortions and place the power imbalance between adult interviewer and (child) respondent into perspective.

  7. 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.

  8. Intergenerational Mobility at the Top of the Educational Distribution

    Research has shown that intergenerational mobility is higher among individuals with a college degree than those with lower levels of schooling. However, mobility declines among graduate degree holders. This finding questions the meritocratic power of higher education. Prior research has been hampered, however, by the small samples of advanced degree holders in representative surveys.
  9. What’s Taking You So Long? Examining the Effects of Social Class on Completing a Bachelor’s Degree in Four Years

    Despite improved access in expanded postsecondary systems, the great majority of bachelor’s degree graduates are taking considerably longer than the allotted four years to complete their four-year degrees. Taking longer to finish one’s BA has become so pervasive in the United States that it has become the norm for official statistics released by the Department of Education to report graduation rates across a six-year window.
  10. Disparities in Debt: Parents’ Socioeconomic Resources and Young Adult Student Loan Debt

    In an era of rising college costs and stagnant grant-based student aid, many young adults rely on their parents’ resources and student loans to pay for their postsecondary education. In this study I ask how parents’ income and education are linked to young adults’ student loan debt. I develop and test two perspectives regarding the functional form of the association between parents’ income, parents’ education, and student loan debt. I have four key findings.