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Logistic Regression: Why We Cannot Do What We Think We Can Do, and What We Can Do About It
Logistic regression estimates do not behave like linear regression estimates in one important respect: They are affected by omitted variables, even when these variables are unrelated to the independent variables in the model. This fact has important implications that have gone largely unnoticed by sociologists. Importantly, we cannot straightforwardly interpret log-odds ratios or odds ratios as effect measures, because they also reflect the degree of unobserved heterogeneity in the model. In addition, we cannot compare log-odds ratios or odds ratios for similar models across groups, samples, or time points, or across models with different independent variables in a sample. This article discusses these problems and possible ways of overcoming them.
Journal Article
Institutional ethnography : a theory of practice for writing studies researchers
\"Reclaims ethnography as a rigorous writing studies research practice, particularly how \"work\" (a concept defined generously) is co-constituted within writing. The study of work and work processes reveals how institutional discourse, social relations, and norms of professional practice coordinate what people do across time\"--Provided by publisher.
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Coordinating Futures: Toward a Theory of Anticipation
This article presents a theoretical approach for studying the coordination of futures. Building off theories of temporality and action, the authors map three different modes of future making-protentions, trajectories, and temporal landscapes-that actors need to coordinate in order to make sense of action together. Using a wide range of empirical evidence, they then show that these modes of future-coordination are autonomous from each other, so that although they are connected, they can clash or move in disjointed directions in interaction. By focusing on the coordination and disjunctures of those three modes, the authors argue that sociologists can provide a methodological axis of comparison between cases; depict mechanisms through which other theoretical or empirical constructs-such as racism or late modernity-operate; and open a window into the ways in which people organize and coordinate their futures, a topic of inquiry in its own right. Adapted from the source document.
Journal Article
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. We refer to this as the problem of rescaling. We propose a solution that allows researchers to assess the influence of confounding relative to the influence of rescaling, and we develop a test to assess the statistical significance of confounding. A further problem in making comparisons is that, in most cases, the error distribution, and not just its variance, will differ across models. Monte Carlo analyses indicate that other methods that have been proposed for dealing with the rescaling problem can lead to mistaken inferences if the error distributions are very different. In contrast, in all scenarios studied, our approach performs as least as well as, and in some cases better than, others when faced with differences in the error distributions. We present an example of our method using data from the National Education Longitudinal Study.
Journal Article
Instrumental Variables in Sociology and the Social Sciences
Instrumental variable (IV) methods provide a powerful but underutilized tool to address many common problems with observational sociological data. Key to their successful use is having IVs that are uncorrelated with an equation's disturbance and that are sufficiently strongly related to the problematic endogenous covariates. This review briefly defines IVs, summarizes their origins, and describes their use in multiple regression, simultaneous equation models, factor analysis, latent variable structural equation models, and limited dependent variable models. It defines and contrasts three methods of selecting IVs: auxiliary instrumental variable, model implied instrumental variable, and randomized instrumental variable. It provides overidentification tests and weak IV diagnostics as methods to evaluate the quality of IVs. I review the use of IVs in models that assume heterogeneous causal effects. Another section summarizes the use of IVs in contemporary sociological publications. The conclusion suggests ways to improve the use of IVs and suggests that there are many areas in which IVs could be profitably used in sociological research.
Journal Article
A General Panel Model with Random and Fixed Effects: A Structural Equations Approach
Fixed- and random-effects models for longitudinal data are common in sociology. Their primary advantage is that they control for time-invariant omitted variables. However, analysts face several issues when they employ these models. One is the choice of which to apply; another is that FEM and REM models as usually implemented might be insufficiently flexible. For example, the effects of variables, including the latent time-invariant variable, might change over time. The latent time-invariant variable might correlate with some variables and not others. Lagged endogenous variables might be necessary. Alternatives that move beyond the classic FEM and REM models are known, but they involve estimators and software that make these extended models difficult to implement and to compare. This article presents a general panel model that includes the standard FEM and REM as special cases. In addition, it provides a sequence of nested models that provide a richer range of models that researchers can easily compare with likelihood ratio tests and fit statistics. Furthermore, researchers can implement our general panel model and its special cases in widely available structural equation models software.
Journal Article
Multiple Levels of Analysis and the Limitations of Methodological Individualisms
This article discusses relations among the multiple levels of analysis present in macro-sociological explanation—i.e., relations of individual, structural, and institutional processes. It also criticizes the doctrinal insistence upon single-level individualistic explanation found in some prominent contemporary sociological theory. For illustrative material the article returns to intellectual uses of Weber's \"Protestant Ethic thesis,\" showing how an artificial version has been employed as a kind of proof text for the alleged scientific necessity of individualist explanation. Our alternative exposition renders the discussion of Protestantism and capitalism in an explicitly multilevel way, distinguishing possible individual-level, social-organizational, and institutional linkages. The causal processes involved are distinct ones, with the more structural and institutional forms neither captured nor attainable by individual-level thinking. We argue more generally that \"methodological individualisms\" confuse issues of explanation with issues about microfoundations. This persistent intellectual conflation may be rooted in the broader folk models of liberal individualism.
Journal Article
Jak se vyrábí sociologická znalost
„Především si řekněme, o čem tahle knížka není. Nechce nahradit standardní učebnici sociologického výzkumu, nenabízí úplnou zbrojnici metod a technik a už vůbec nechce naučit čtenáře statistice. Její cíl je v tomto smyslu daleko skromnější: porozumění logice výzkumu a porozumění smyslu statistických operací.“
Tolik autor ve svém úvodním slově. Obvykle nezáživné metody sociologie Disman představuje s humorem a nadhledem a více než o znalost statistiky samotné mu jde o schopnost porozumět „skutečnému smyslu našich dat“.
Druhý dotisk 4. vydání úspěšné učebnice
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