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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. 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.
  3. 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.

  4. 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.

  5. “Personal Preference” as the New Racism: Gay Desire and Racial Cleansing in Cyberspace

    In this article, I examine how race impacts online interactions on one of the most popular online gay personal websites in the United States. Based on 15 in-depth interviews and an analysis of 100 profiles, I show that the filtering system on this website allows users to cleanse particular racial bodies from their viewing practices.

  6. Where Are All of the Women? Untangling the Effects of Representation, Participation, and Preferences on Gender Differences in Political Press Coverage

    The author examines why female politicians continue to be underrepresented in the press by measuring how structural inequalities, engagement in traditional and disruptive dialogue, and gender preferences influence the amount of press coverage U.S. House representatives receive.
  7. Biases of Online Political Polls: Who Participates?

    With a large portion of the population online and the high cost of phone-based surveys, querying people about their voter preference online can offer an affordable and timely alternative. However, given that there are biases in who adopts various sites and services that are often used as sampling frames (e.g., various social media), online political polls may not represent the views of the overall population. How are such polls biased? Who is most likely to participate in them?
  8. Testing for Discrimination: Teaching Audit Studies in Quantitative Methods Courses

    This article demonstrates a method for teaching students to conduct audit studies of discrimination. The assignment can be used in courses on quantitative methods, race, gender, or other topics. Audit studies test for unequal treatment by having otherwise identical pairs of people who vary on a single trait, such as race or gender, apply for the same sets of opportunities, such as apartment vacancies or job openings. Once intricate and expensive to conduct, the online shift of the past 15 years has streamlined the approach, enabling researchers to execute audits via email.

  9. Can Online Courses Deliver In-class Results? A Comparison of Student Performance and Satisfaction in an Online versus a Face-to-face Introductory Sociology Course

    This study uses a quasi-experimental design to assess differences in student performance and satisfaction across online and face-to-face (F2F) classroom settings. Data were collected from 368 students enrolled in three online and three F2F sections of an introductory-level sociology course. The instructor, course materials, and assessments were consistent between the two delivery formats. The investigators compare student satisfaction and student performance on midterm exams and an integrating data analysis assignment.

  10. Teaching Content Analysis through Harry Potter

    Content analysis is a valuable research tool for social scientists that unfortunately can prove challenging to teach to undergraduate students. Published classroom exercises designed to teach content analysis have thus far been predominantly envisioned as lengthy projects for upper-level courses. A brief and engaging exercise may be more beneficial for introductory social science courses in which less time can be allotted to any one topic, such as content analysis.