Sociological Methodology最新文献_第10页

Deciding on the Starting Number of Classes of a Latent Class Tree. 决定潜在类树的起始类数。

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-08-01 Epub Date: 2018-06-21 DOI: 10.1177/0081175018780170

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":null,"pages":null},"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}

引用次数: 11

Comment: Bayes, Model Uncertainty, and Learning from Data 评论：贝叶斯、模型不确定性和从数据中学习

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-08-01 DOI: 10.1177/0081175018799095

B. Western

引用次数: 1

Comment: Some Challenges When Estimating the Impact of Model Uncertainty on Coefficient Instability 评论：在估计模型不确定性对系数不稳定性的影响时面临的一些挑战

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-08-01 DOI: 10.1177/0081175018790569

Robert M. O’Brien

引用次数: 1

Nonlinear Autoregressive Latent Trajectory Models 非线性自回归潜在轨迹模型

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-08-01 DOI: 10.1177/0081175018789441

Shawn Bauldry, K. Bollen

{"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":null,"pages":null},"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}

引用次数: 4

Rejoinder: Can We Weight Models by Their Probability of Being True? 复辩状：我们能根据模型为真的概率对其进行加权吗？

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-08-01 DOI: 10.1177/0081175018796841

John Muñoz, Cristobal Young

引用次数: 1

Rejoinder: On the Assumptions of Inferential Model Selection—A Response to Vassend and Weakliem 答辩:论推理模型选择的假设——对Vassend和Weakliem的回应

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-08-01 DOI: 10.1177/0081175018794488

Michael Schultz

引用次数: 0

Causal Inference with Networked Treatment Diffusion 网络化治疗扩散的因果推理

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-07-25 DOI: 10.1177/0081175018785216

Weihua An

引用次数: 6

The Problem of Underdetermination in Model Selection 模型选择中的欠确定问题

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-07-13 DOI: 10.1177/0081175018786762

Michael Schultz

引用次数: 1

We Ran 9 Billion Regressions: Eliminating False Positives through Computational Model Robustness 我们运行了90亿次回归:通过计算模型稳健性消除误报

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-07-13 DOI: 10.1177/0081175018777988

John Muñoz, Cristobal Young

{"title":"We Ran 9 Billion Regressions: Eliminating False Positives through Computational Model Robustness","authors":"John Muñoz, Cristobal Young","doi":"10.1177/0081175018777988","DOIUrl":"https://doi.org/10.1177/0081175018777988","url":null,"abstract":"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. Computational model robustness analysis addresses this challenge by estimating all possible models from a theoretically informed model space. We use large-scale random noise simulations to show (1) the problem of excess false positive errors under model uncertainty and (2) that computational robustness analysis can identify and eliminate false positives caused by model uncertainty. We also draw on a series of empirical applications to further illustrate issues of model uncertainty and estimate instability. Computational robustness analysis offers a method for relaxing modeling assumptions and improving the transparency of applied research.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2018-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018777988","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44889259","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}

引用次数: 37

Estimating Income Statistics from Grouped Data: Mean-constrained Integration over Brackets 从分组数据估计收入统计:括号上的均值约束整合

IF 3 2区社会学

Sociological Methodology Pub Date : 2018-07-09 DOI: 10.1177/0081175018782579

P. Jargowsky, Christopher A. Wheeler

{"title":"Estimating Income Statistics from Grouped Data: Mean-constrained Integration over Brackets","authors":"P. Jargowsky, Christopher A. Wheeler","doi":"10.1177/0081175018782579","DOIUrl":"https://doi.org/10.1177/0081175018782579","url":null,"abstract":"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. The distribution of households within the brackets is unknown, and highest incomes are often included in an open-ended top bracket, such as “$200,000 and above.” Common approaches to this estimation problem include calculating midpoint estimators with an assumed Pareto distribution in the top bracket and fitting a flexible multiple-parameter distribution to the data. The authors describe a new method, mean-constrained integration over brackets (MCIB), that is far more accurate than those methods using only the bracket counts and the overall mean of the data. On the basis of an analysis of 297 metropolitan areas, MCIB produces estimates of the standard deviation, Gini coefficient, and Theil index that are correlated at 0.997, 0.998, and 0.991, respectively, with the parameters calculated from the underlying individual record data. Similar levels of accuracy are obtained for percentiles of the distribution and the shares of income by quintiles of the distribution. The technique can easily be extended to other distributional parameters and inequality statistics.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2018-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018782579","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46483285","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}

引用次数: 11