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  1. 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.
  2. Estimating Income Statistics from Grouped Data: Mean-constrained Integration over Brackets

    Researchers studying income inequality, economic segregation, and other subjects must often rely on grouped data—that is, data in which thousands or millions of observations have been reduced to counts of units by specified income brackets.
  3. How to Think Scientifically about Scientists’ Proposals for Fixing Science

    Science is in crisis. Any doubt about this status has surely been dispelled by the loud assurances to the contrary by various authority figures who are deeply invested in the current system and have written things such as, “Psychology is not in crisis, contrary to popular rumor. . . . Crisis or no crisis, the field develops consensus about the most valuable insights. . . . National panels will convene and caution scientists, reviewers, and editors to uphold standards” (Fiske, Schacter, and Taylor 2016: v).
  4. Deciding on the Starting Number of Classes of a Latent Class Tree

    In recent studies, latent class tree (LCT) modeling has been proposed as a convenient alternative to standard latent class (LC) analysis. Instead of using an estimation method in which all classes are formed simultaneously given the specified number of classes, in LCT analysis a hierarchical structure of mutually linked classes is obtained by sequentially splitting classes into two subclasses. The resulting tree structure gives a clear insight into how the classes are formed and how solutions with different numbers of classes are substantively linked to one another.
  5. Item Location, the Interviewer–Respondent Interaction, and Responses to Battery Questions in Telephone Surveys

    Survey researchers often ask a series of attitudinal questions with a common question stem and response options, known as battery questions. Interviewers have substantial latitude in deciding how to administer these items, including whether to reread the common question stem on items after the first one or to probe respondents’ answers. Despite the ubiquity of use of these items, there is virtually no research on whether respondent and interviewer behaviors on battery questions differ over items in a battery or whether interview behaviors are associated with answers to these questions.
  6. Sticks, Stones, and Molotov Cocktails: Unarmed Collective Violence and Democratization

    Sticks, Stones, and Molotov Cocktails: Unarmed Collective Violence and Democratization

  7. After Charlottesville

    Essays explore Americans’ construction and deconstruction of collective memory as White supremacists take to the streets.
  8. Making Protest Great Again

    From the Women’s March to Unite the Right, the Trump presidency has gotten underway during an extraordinary period of mobilized American protest. If nothing else, he may very well be making protest great again.
  9. Do Black Lives Increasingly Matter?

    Christopher Todd Beer on trends in police killings of unarmed citizens.
  10. The Algorithmic Rise of the “Alt-Right”

    As with so many technologies, the Internet’s racism was programmed right in—and it’s quickly fueled the spread of White supremacist, xenophobic rhetoric throughout the western world.