Pub Date : 2019-08-01Epub Date: 2018-08-30DOI: 10.1177/0081175018793460
Benjamin F Jarvis
This comment reconsiders advice offered by Bruch and Mare regarding sampling choice sets in conditional logistic regression models of residential mobility. Contradicting Bruch and Mare's advice, past econometric research shows that no statistical correction is needed when using simple random sampling of unchosen alternatives to pare down respondents' choice sets. Using data on stated residential preferences contained in the Los Angeles portion of the Multi-City Study of Urban Inequality, it is shown that following Bruch and Mare's advice-to implement a statistical correction for simple random choice set sampling-leads to biased coefficient estimates. This bias is all but eliminated if the sampling correction is omitted.
{"title":"ESTIMATING MULTINOMIAL LOGIT MODELS WITH SAMPLES OF ALTERNATIVES.","authors":"Benjamin F Jarvis","doi":"10.1177/0081175018793460","DOIUrl":"https://doi.org/10.1177/0081175018793460","url":null,"abstract":"<p><p>This comment reconsiders advice offered by Bruch and Mare regarding sampling choice sets in conditional logistic regression models of residential mobility. Contradicting Bruch and Mare's advice, past econometric research shows that no statistical correction is needed when using simple random sampling of unchosen alternatives to pare down respondents' choice sets. Using data on stated residential preferences contained in the Los Angeles portion of the Multi-City Study of Urban Inequality, it is shown that following Bruch and Mare's advice-to implement a statistical correction for simple random choice set sampling-leads to biased coefficient estimates. This bias is all but eliminated if the sampling correction is omitted.</p>","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018793460","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38980161","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}
Pub Date : 2019-08-01DOI: 10.1177/0081175019860236
P. Oliver
Protest Event and Political Discourse Approaches.” Mobilization 4(2):203–21. Kriesi, Hanspeter, Swen Hutter, and Abel Bojar. 2019. “Contentious Episode Analysis.” Mobilization 24(3). Kriesi, Hanspeter, Ruud Koopmans, Jan Willem Duyvendak, and Marco Giugni. 1995. New Social Movements in Western Europe. Minneapolis: University of Minnesota Press. McAdam, Doug. 1982. Political Process and the Development of Black Insurgency 1930–1970. Chicago: University of Chicago Press. Tarrow, Sidney. 1989. Democracy and Disorder: Protest and Politics in Italy 1965– 1974. Oxford, UK: Oxford University Press. Taylor, Charles L., and Michael C. Hudson. 1972. World Handbook of Political and Social Indicators. New Haven, CT: Yale University Press. Tilly, Charles. 2008. Contentious Performances. Cambridge, UK: Cambridge University Press. Tilly, Charles, Louise Tilly, and Richard Tilly. 1975. The Rebellious Century, 1830– 1930. Cambridge, MA: Harvard University Press.
抗议事件和政治话语方法。”动员4(2):203 - 21所示。Kriesi, Hanspeter，斯文·哈特和Abel Bojar, 2019。“争议事件分析”。动员24(3)。Kriesi, Hanspeter, Ruud Koopmans, Jan Willem Duyvendak和Marco Giugni, 1995。西欧的新社会运动。明尼阿波利斯:明尼苏达大学出版社。道格·麦克亚当1982。1930-1970年黑人叛乱的政治进程和发展。芝加哥:芝加哥大学出版社。西德尼·塔罗1989。民主与无序:1965 - 1974年意大利的抗议与政治。英国牛津:牛津大学出版社。查尔斯·L·泰勒和迈克尔·c·哈德森1972。《世界政治和社会指标手册》。康涅狄格州纽黑文:耶鲁大学出版社。查尔斯·蒂莉，2008。有争议的表演。英国剑桥:剑桥大学出版社。Tilly, Charles, Louise Tilly和Richard Tilly, 1975。叛逆的世纪(1830 - 1930)剑桥，马萨诸塞州:哈佛大学出版社。
{"title":"Great Methods Reveal Their Own Limitations","authors":"P. Oliver","doi":"10.1177/0081175019860236","DOIUrl":"https://doi.org/10.1177/0081175019860236","url":null,"abstract":"Protest Event and Political Discourse Approaches.” Mobilization 4(2):203–21. Kriesi, Hanspeter, Swen Hutter, and Abel Bojar. 2019. “Contentious Episode Analysis.” Mobilization 24(3). Kriesi, Hanspeter, Ruud Koopmans, Jan Willem Duyvendak, and Marco Giugni. 1995. New Social Movements in Western Europe. Minneapolis: University of Minnesota Press. McAdam, Doug. 1982. Political Process and the Development of Black Insurgency 1930–1970. Chicago: University of Chicago Press. Tarrow, Sidney. 1989. Democracy and Disorder: Protest and Politics in Italy 1965– 1974. Oxford, UK: Oxford University Press. Taylor, Charles L., and Michael C. Hudson. 1972. World Handbook of Political and Social Indicators. New Haven, CT: Yale University Press. Tilly, Charles. 2008. Contentious Performances. Cambridge, UK: Cambridge University Press. Tilly, Charles, Louise Tilly, and Richard Tilly. 1975. The Rebellious Century, 1830– 1930. Cambridge, MA: Harvard University Press.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175019860236","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45811756","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}
Pub Date : 2019-08-01DOI: 10.1177/0081175019860239
Swen Hutter
{"title":"Exploring the Full Conceptual Potential of Protest Event Analysis","authors":"Swen Hutter","doi":"10.1177/0081175019860239","DOIUrl":"https://doi.org/10.1177/0081175019860239","url":null,"abstract":"","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175019860239","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43591352","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}
Pub Date : 2019-08-01Epub Date: 2019-02-05DOI: 10.1177/0081175018820075
Jacob C Fisher
Social networks represent two different facets of social life: (1) stable paths for diffusion, or the spread of something through a connected population, and (2) random draws from an underlying social space, which indicate the relative positions of the people in the network to one another. The dual nature of networks creates a challenge - if the observed network ties are a single random draw, is it realistic to expect that diffusion only follows the observed network ties? This study takes a first step towards integrating these two perspectives by introducing a social space diffusion model. In the model, network ties indicate positions in social space, and diffusion occurs proportionally to distance in social space. Practically, the simulation occurs in two parts. First, positions are estimated using a statistical model (in this example, a latent space model). Then, second, the predicted probabilities of a tie from that model - representing the distances in social space - or a series of networks drawn from those probabilities - representing routine churn in the network - are used as weights in a weighted averaging framework. Using longitudinal data from high school friendship networks, I explore the properties of the model. I show that the model produces smoothed diffusion results, which predict attitudes in future waves 10% better than a diffusion model using the observed network, and up to 5% better than diffusion models using alternative, non-model-based smoothing approaches.
{"title":"Social Space Diffusion: Applications of a Latent Space Model to Diffusion with Uncertain Ties.","authors":"Jacob C Fisher","doi":"10.1177/0081175018820075","DOIUrl":"https://doi.org/10.1177/0081175018820075","url":null,"abstract":"<p><p>Social networks represent two different facets of social life: (1) stable paths for diffusion, or the spread of something through a connected population, and (2) random draws from an underlying social space, which indicate the relative positions of the people in the network to one another. The dual nature of networks creates a challenge - if the observed network ties are a single random draw, is it realistic to expect that diffusion only follows the observed network ties? This study takes a first step towards integrating these two perspectives by introducing a social space diffusion model. In the model, network ties indicate positions in social space, and diffusion occurs proportionally to distance in social space. Practically, the simulation occurs in two parts. First, positions are estimated using a statistical model (in this example, a latent space model). Then, second, the predicted probabilities of a tie from that model - representing the distances in social space - or a series of networks drawn from those probabilities - representing routine churn in the network - are used as weights in a weighted averaging framework. Using longitudinal data from high school friendship networks, I explore the properties of the model. I show that the model produces smoothed diffusion results, which predict attitudes in future waves 10% better than a diffusion model using the observed network, and up to 5% better than diffusion models using alternative, non-model-based smoothing approaches.</p>","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175018820075","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"25583523","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}
Pub Date : 2019-08-01DOI: 10.1177/0081175019863783
Laura K. Nelson
{"title":"To Measure Meaning in Big Data, Don’t Give Me a Map, Give Me Transparency and Reproducibility","authors":"Laura K. Nelson","doi":"10.1177/0081175019863783","DOIUrl":"https://doi.org/10.1177/0081175019863783","url":null,"abstract":"","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175019863783","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46674333","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}
Pub Date : 2019-08-01DOI: 10.1177/0081175019860238
Zachary C. Steinert-Threlkeld
A Look at How the New York Times, the Wall Street Journal, the Washington Post, and BuzzFeed Compare.” The Atlantic. Retrieved June 17, 2019. https:// www.theatlantic.com/technology/archive/2016/05/how-many-stories-do-newspaperspublish-per-day/483845/. Soule, Sarah, and Jennifer Earl. 2005. “A Movement Society Evaluated: Collective Protest in the United States, 1960–1986.” Mobilization: An International Quarterly 10(3):345–64.
{"title":"The Future of Event Data Is Images","authors":"Zachary C. Steinert-Threlkeld","doi":"10.1177/0081175019860238","DOIUrl":"https://doi.org/10.1177/0081175019860238","url":null,"abstract":"A Look at How the New York Times, the Wall Street Journal, the Washington Post, and BuzzFeed Compare.” The Atlantic. Retrieved June 17, 2019. https:// www.theatlantic.com/technology/archive/2016/05/how-many-stories-do-newspaperspublish-per-day/483845/. Soule, Sarah, and Jennifer Earl. 2005. “A Movement Society Evaluated: Collective Protest in the United States, 1960–1986.” Mobilization: An International Quarterly 10(3):345–64.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175019860238","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44521644","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}
Pub Date : 2019-07-23DOI: 10.1177/0081175019862839
David Melamed, Michael Vuolo
In multilevel data, cross-classified data structures are common. For example, this occurs when individuals move to different regions in longitudinal data or students go to different secondary schools than their primary school peers. In both cases, the data structure is no longer fully nested. Estimating cross-classified multilevel models is computationally intensive, so researchers have used several shortcuts to decrease run time. We consider how these shortcuts affect parameter estimates. In particular, we compare parameter estimates from fully nested and cross-classified models using a series of Monte Carlo simulations. When the outcome is continuous, we identify systematic differences in estimated standard errors and some differences in the estimated variance components. When the outcome is binary, we also find differences in the estimated coefficients. Accordingly, we caution researchers to avoid fully nested model specifications when cross-classification exists but suggest some limited conditions under which parameter estimates are unlikely to be different.
{"title":"Assessing Differences between Nested and Cross-Classified Hierarchical Models","authors":"David Melamed, Michael Vuolo","doi":"10.1177/0081175019862839","DOIUrl":"https://doi.org/10.1177/0081175019862839","url":null,"abstract":"In multilevel data, cross-classified data structures are common. For example, this occurs when individuals move to different regions in longitudinal data or students go to different secondary schools than their primary school peers. In both cases, the data structure is no longer fully nested. Estimating cross-classified multilevel models is computationally intensive, so researchers have used several shortcuts to decrease run time. We consider how these shortcuts affect parameter estimates. In particular, we compare parameter estimates from fully nested and cross-classified models using a series of Monte Carlo simulations. When the outcome is continuous, we identify systematic differences in estimated standard errors and some differences in the estimated variance components. When the outcome is binary, we also find differences in the estimated coefficients. Accordingly, we caution researchers to avoid fully nested model specifications when cross-classification exists but suggest some limited conditions under which parameter estimates are unlikely to be different.","PeriodicalId":48140,"journal":{"name":"Sociological Methodology","volume":null,"pages":null},"PeriodicalIF":3.0,"publicationDate":"2019-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/0081175019862839","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45444964","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号