{"title":"Prologue","authors":"Anonymous","doi":"10.1177/0081175018799359","DOIUrl":"https://doi.org/10.1177/0081175018799359","url":null,"abstract":"Readers who leaf through this journal's pages in early 2021 or connect to it online will, sadly, need no reminder of how COVID-19-the respiratory illness caused by a novel strain of coronavirus-spread illness, death, and fear around the world, culminating in the declaration of a pandemic by the World Health Organization on 11 March 2020 Just as spring daffodils and orange blossoms burst forth last spring in the Mediterranean region that is our shared literary-cultural patria, we found ourselves involuntarily immersed in lockdowns Last but not least, we gratefully acknowledge Editorial Board members for continuing to provide detailed and rigorous article evaluations within the requested time frame, authors at all career stages for their submissions of exciting new work, and book reviewers for keeping our readers abreast of current scholarship in comedia studies and beyond","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"xi - xxv"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018799359","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47395063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dedication: Allan McCutcheon: Latent Class Analyst","authors":"A. McCutcheon, Allan Lee","doi":"10.1177/0081175018791565","DOIUrl":"https://doi.org/10.1177/0081175018791565","url":null,"abstract":"","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"ix - x"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018791565","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47514789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mattis van den Bergh, Geert H van Kollenburg, Jeroen K Vermunt
{"title":"Deciding on the Starting Number of Classes of a Latent Class Tree.","authors":"Mattis van den Bergh, Geert H van Kollenburg, Jeroen K Vermunt","doi":"10.1177/0081175018780170","DOIUrl":"https://doi.org/10.1177/0081175018780170","url":null,"abstract":"<p><p>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. A limitation of the current LCT modeling approach is that it allows only for binary splits, which in certain situations may be too restrictive. Especially at the root node of the tree, where an initial set of classes is created based on the most dominant associations present in the data, it may make sense to use a model with more than two classes. In this article, we propose a modification of the LCT approach that allows for a nonbinary split at the root node, and we provide methods to determine the appropriate number of classes in this first split, based either on theoretical grounds or on a relative improvement of fit measure. This novel approach also can be seen as a hybrid of a standard LC model and a binary LCT model, in which an initial, oversimplified but interpretable model is refined using an LCT approach. Furthermore, we show how to apply an LCT model when a nonstandard LC model is required. These new approaches are illustrated using two empirical applications: one on social capital and the other on (post)materialism.</p>","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"303-336"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018780170","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"36859532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comment: Some Challenges When Estimating the Impact of Model Uncertainty on Coefficient Instability","authors":"Robert M. O’Brien","doi":"10.1177/0081175018790569","DOIUrl":"https://doi.org/10.1177/0081175018790569","url":null,"abstract":"","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"34 - 39"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018790569","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44241112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comment: Bayes, Model Uncertainty, and Learning from Data","authors":"B. Western","doi":"10.1177/0081175018799095","DOIUrl":"https://doi.org/10.1177/0081175018799095","url":null,"abstract":"Robert M. O’Brien is a professor emeritus at the University of Oregon. He specializes in criminology and quantitative methods. Within criminology, he focuses on the methods used to gather criminological data, on the analysis of crime rates, and on the task of extricating the effects of ages, periods, and cohorts on crime rates. His most recent publication on that topic, “Homicide Arrest Rate Trends in the United States: The Contributions of Periods and Cohorts (1965–2015),” appeared in 2018 in the Journal of Quantitative Criminology. In quantitative methods, some of his contributions involve the effects of using interval data as ordinal, generalizability theory, identification in structural equation modeling measurement models, the use of multicollinearity indices, and an obsession with age-period-cohort models. In 2015 he published a book on this topic, Age-Period-Cohort Models: Approaches and Analyses with Aggregate Data (Chapman & Hall, 2015).","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"39 - 43"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018799095","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48945486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Nonlinear Autoregressive Latent Trajectory Models","authors":"Shawn Bauldry, K. Bollen","doi":"10.1177/0081175018789441","DOIUrl":"https://doi.org/10.1177/0081175018789441","url":null,"abstract":"Autoregressive latent trajectory (ALT) models combine features of latent growth curve models and autoregressive models into a single modeling framework. The development of ALT models has focused primarily on models with linear growth components, but some social processes follow nonlinear trajectories. Although it is straightforward to extend ALT models to allow for some forms of nonlinear trajectories, the identification status of such models, approaches to comparing them with alternative models, and the interpretation of parameters have not been systematically assessed. In this paper we focus on two forms of nonlinear autoregressive latent trajectory (NLALT) models. The first form allows for a quadratic growth trajectory, a popular form of nonlinear latent growth curve models. The second form derives from latent basis models, or freed loading models, that allow for arbitrary growth processes. We discuss details concerning parameterization, model identification, estimation, and testing for the two forms of NLALT models. We include a simulation study that illustrates potential biases that may arise from fitting alternative models to data derived from an autoregressive process and individual-specific nonlinear trajectories. In addition, we include an extended empirical example modeling growth trajectories of weight from birth through age 2.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"269 - 302"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018789441","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42277749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rejoinder: Can We Weight Models by Their Probability of Being True?","authors":"John Muñoz, Cristobal Young","doi":"10.1177/0081175018796841","DOIUrl":"https://doi.org/10.1177/0081175018796841","url":null,"abstract":"Draper, David. 1995. “Assessment and Propagation of Model Uncertainty.” Journal of the Royal Statistical Society, Series B 57:45–97. Freedman, David A. 1983. “A Note on Screening Regression Equations.” American Statistician 37:152–55. Leamer, Edward E. 1983. “Let’s Take the Con out of Econometrics.” American Economic Review 73:31–43. Raftery, Adrian E. 1996. “Approximate Bayes Factors and Accounting for Model Uncertainty in Generalised Linear Models.” Biometrika 83:251–66. Young, Cristobal, and Katherine Holsteen. 2017. “Model Uncertainty and Robustness: A Computational Framework for Multimodel Analysis.” Sociological Methods and Research 46:3–40.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"43 - 51"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018796841","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46160602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rejoinder: On the Assumptions of Inferential Model Selection—A Response to Vassend and Weakliem","authors":"Michael Schultz","doi":"10.1177/0081175018794488","DOIUrl":"https://doi.org/10.1177/0081175018794488","url":null,"abstract":"","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"102 - 97"},"PeriodicalIF":3.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018794488","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44095198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Causal Inference with Networked Treatment Diffusion","authors":"Weihua An","doi":"10.1177/0081175018785216","DOIUrl":"https://doi.org/10.1177/0081175018785216","url":null,"abstract":"Treatment interference (i.e., one unit’s potential outcomes depend on other units’ treatment) is prevalent in social settings. Ignoring treatment interference can lead to biased estimates of treatment effects and incorrect statistical inferences. Some recent studies have started to incorporate treatment interference into causal inference. But treatment interference is often assumed to follow a simple structure (e.g., treatment interference exists only within groups) or measured in a simplistic way (e.g., only based on the number of treated friends). In this paper, I highlight the importance of collecting data on actual treatment diffusion in order to more accurately measure treatment interference. Furthermore, I show that with accurate measures of treatment interference, we can identify and estimate a series of causal effects that are previously unavailable, including the direct treatment effect, treatment interference effect, and treatment effect on interference. I illustrate the methods through a case study of a social network–based smoking prevention intervention.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"152 - 181"},"PeriodicalIF":3.0,"publicationDate":"2018-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018785216","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46496172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Problem of Underdetermination in Model Selection","authors":"Michael Schultz","doi":"10.1177/0081175018786762","DOIUrl":"https://doi.org/10.1177/0081175018786762","url":null,"abstract":"Conventional model selection evaluates models on their ability to represent data accurately, ignoring their dependence on theoretical and methodological assumptions. Drawing on the concept of underdetermination from the philosophy of science, the author argues that uncritical use of methodological assumptions can pose a problem for effective inference. By ignoring the plausibility of assumptions, existing techniques select models that are poor representations of theory and are thus suboptimal for inference. To address this problem, the author proposes a new paradigm for inference-oriented model selection that evaluates models on the basis of a trade-off between model fit and model plausibility. By comparing the fits of sequentially nested models, it is possible to derive an empirical lower bound for the subjective plausibility of assumptions. To demonstrate the effectiveness of this approach, the method is applied to models of the relationship between cultural tastes and network composition.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":"48 1","pages":"52 - 87"},"PeriodicalIF":3.0,"publicationDate":"2018-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018786762","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42436313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}