Statistics and Public Policy最新文献_第9页

On the Distribution of Worker Productivity: The Case of Teacher Effectiveness and Student Achievement 论工人生产力的分布——以教师效能与学生成就为例

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2016.1271733

Dan Goldhaber, R. Startz

{"title":"On the Distribution of Worker Productivity: The Case of Teacher Effectiveness and Student Achievement","authors":"Dan Goldhaber, R. Startz","doi":"10.1080/2330443X.2016.1271733","DOIUrl":"https://doi.org/10.1080/2330443X.2016.1271733","url":null,"abstract":"ABSTRACT It is common to assume that worker productivity is normally distributed, but this assumption is rarely, if ever, tested. We estimate the distribution of worker productivity, where individual productivity is measured with error, using the productivity of teachers as an example. We employ a nonparametric density estimator that explicitly accounts for measurement error using data from the Tennessee STAR experiment, and longitudinal data from North Carolina and Washington. Statistical tests show that the productivity distribution of teachers is not Gaussian, but the differences from the normal distribution tend to be small. Our findings confirm the existing empirical evidence that the differences in the effects of individual teachers on student achievement are large and the assumption that the differences in the upper and lower tails of the teacher performance distribution are far larger than in the middle of the distribution. Specifically, a 10 percentile point movement for teachers at the top (90th) or bottom (10th) deciles of the distribution is estimated to move student achievement by 8–17 student percentile ranks, as compared to a change of 2–7 student percentile ranks for a 10 percentile change in teacher productivity in the middle of the distribution.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2016.1271733","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49502010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Absence of Statistical and Scientific Ethos: The Common Denominator in Deficient Forensic Practices 统计和科学伦理的缺失：司法实践不足的共同污点

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2016.1270175

W. Tobin, H. Sheets, C. Spiegelman

{"title":"Absence of Statistical and Scientific Ethos: The Common Denominator in Deficient Forensic Practices","authors":"W. Tobin, H. Sheets, C. Spiegelman","doi":"10.1080/2330443X.2016.1270175","DOIUrl":"https://doi.org/10.1080/2330443X.2016.1270175","url":null,"abstract":"ABSTRACT Comparative Bullet Lead Analysis (CBLA) was discredited as a forensic discipline largely due to the absence of cross-discipline input, primarily metallurgical and statistical, during development and forensic/judicial application of the practice. Of particular significance to the eventual demise of CBLA practice was ignorance of the role of statistics in assessing probative value of claimed bullet “matches” at both the production and retail distribution levels, leading to overstated testimonial claims by expert witnesses. Bitemark comparisons have come under substantial criticism in the last few years, both due to exonerations based on DNA evidence and to research efforts questioning the claimed uniqueness of bitemarks. The fields of fire and arson investigation and of firearm and toolmark comparison are similar to CBLA and bitemarks in the absence of effective statistical support for these practices. The features of the first two disciplines are examined in systemic detail to enhance understanding as to why they became discredited forensic practices, and to identify aspects of the second two disciplines that pose significant concern to critics.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2016.1270175","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41885182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Defining Program Effects: A Distribution-Based Perspective 定义程序效果:基于分布的视角

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2017.1369914

J. Green, W. Stroup, Pamela S. Fellers

{"title":"Defining Program Effects: A Distribution-Based Perspective","authors":"J. Green, W. Stroup, Pamela S. Fellers","doi":"10.1080/2330443X.2017.1369914","DOIUrl":"https://doi.org/10.1080/2330443X.2017.1369914","url":null,"abstract":"ABSTRACT In an age of accountability, it is critical to define and estimate the effects of teacher education and professional development programs on student learning in ways that allow stakeholders to explore potential reasons for what is observed and to enhance program quality and fidelity. Across the suite of statistical models used for program evaluation, researchers consistently measure program effectiveness using the coefficients of fixed program effects. We propose that program effects are best characterized not as a single effect to be estimated, but as a distribution of teacher-specific effects. In this article, we first discuss this approach and then describe one way it could be used to define and estimate program effects within a value-added modeling context. Using an example dataset, we demonstrate how program effect estimates can be obtained using the proposed methodology and explain how distributions of these estimates provide additional information and insights about programs that are not apparent when only looking at average effects. By examining distributions of teacher-specific effects as proposed, researchers have the opportunity to more deeply investigate and understand the effects of programs on student success.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2017.1369914","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46920866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Response to Gelman and Azari (2017) 对Gelman和Azari的回应（2017）

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2017.1399845

Corrie V. Hunt

引用次数: 0

ADGN: An Algorithm for Record Linkage Using Address, Date of Birth, Gender, and Name ADGN:一种使用地址、出生日期、性别和姓名进行记录链接的算法

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2017.1389620

S. Ansolabehere, Eitan Hersh

引用次数: 37

What We Relearned and Learned from the 2016 Elections: Comment on Gelman and Azari 我们从2016年选举中学到了什么:评论格尔曼和阿扎里

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2017.1399842

R. Y. Shapiro

{"title":"What We Relearned and Learned from the 2016 Elections: Comment on Gelman and Azari","authors":"R. Y. Shapiro","doi":"10.1080/2330443X.2017.1399842","DOIUrl":"https://doi.org/10.1080/2330443X.2017.1399842","url":null,"abstract":"How soon we forget, and Gelman and Azari did not mention what baseball legend and language master Yogi Berra would have reminded us regarding the 2016 election polling: (1) “It’s ‘de ja vu’ all over again!” And (2) “...But the similarities are different!” (see Shapiro 2017a). This election hearkened back to the 1936 and especially the 1948 elections in which pollsters—as both pollsters and pundits—demonstrated unadulterated arrogance or hubris. In 1936 the folks atThe LiteraryDigestmagazine flaunted the prediction based on their multiple million ballot straw poll (that had been mailed to their subscribers and names from telephone, car registration and other lists—which had a distinctively upper status bias) that Alfred Landon would defeat President Franklin Roosevelt. The poll had gotten the winner right in every election from 1916 through FDR in 1932, so what could go wrong? Everything, thanks to the political realignment in which lower status voters missed in the straw poll disproportionately broke toward the Democrat Roosevelt. That year the more “scientific” (that is, engaging in something closer, but still far from, probability sampling) pollsters George Gallup, Elmo Roper, and Archibald Crossley predicted an easy Roosevelt victory and put theDigest to shame (it went out of business not long afterward). But Crossley and Gallup—who was then and still is themost famous of the lot—still underestimatedRoosevelt’s vote (60.7%) by fully 7 percentage points (compared to the Digest’s 20 points), and Gallup continued to underestimate Roosevelt’s vote in the next two election. So something was still amiss in the polls. The question of poll accuracy during this time, as the pollsters announced their predictions, got some attention, including calls for congressional investigation of the polls (on this forgotten and not well-remembered point, see especially Fried (2012)","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2017.1399842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46500450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Unraveling 2016: Comments on Gelman and Azari's 19 Things 揭开2016：盖尔曼和阿扎尔的19件事评论

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2017.1399846

J. Victor

{"title":"Unraveling 2016: Comments on Gelman and Azari's 19 Things","authors":"J. Victor","doi":"10.1080/2330443X.2017.1399846","DOIUrl":"https://doi.org/10.1080/2330443X.2017.1399846","url":null,"abstract":"Scholars, pundits, and wonks will be studying the 2016 election for a long time. The sheer number of unprecedented elements of the 2016 U.S. elections produced some shock fatigue and left even seasoned election watchers scratching their heads (Fallows 2017). Drawing on insights from data science, statistics, and political science, Julia Azari and Andrew Gelman identify an impressive 19 potentially productive threads to pull on in our attempt to unravel the mysteries of 2016. There are so many features of the 2016 election that strayed from the status quo that, like a spoiled experimental design, it is challenging for scholars to explain exactly why the election turned in the surprising ways it did. To name just a few, 2016 included the first female major party candidate, the first modern election with evidence of undue foreign influence, the first election with a nominee who had no government or military experience of any kind, and the list goes on. While some may find the Gelman–Azari treatment dissatisfying for being too shallow on any individual point, too contrived, or just too long of a list, I submit that their holistic approach to breaking down the oddities of 2016 is necessary given the circumstances. Here, I focus on four of the items on their list—two that I find worth underscoring and strongly worthy of further exploration, and two that are perhaps too complex to pursue, even if perfectly valid.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2017.1399846","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44303524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rejoinder: How Special was 2016? 答辩:2016年有多特别?

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2017.1400298

Julia Azari, A. Gelman

{"title":"Rejoinder: How Special was 2016?","authors":"Julia Azari, A. Gelman","doi":"10.1080/2330443X.2017.1400298","DOIUrl":"https://doi.org/10.1080/2330443X.2017.1400298","url":null,"abstract":"Five responses from leading scholars of American politics have given us a great deal to think about. Several themes emerge from the responses. The first is the challenge of the addressing how relevant the 2016 election will be for understanding the future of American politics. Several of the discussants also challenge our thinking about the role of white working class pundits, and about how political scientists should think about demographics and politics more generally. In the study of comparative politics, the literature on case selection demands that scholars answer the question, “What kind of case is this?” before proceeding; see for example Gerring and Seawright (2008). Looking forward, is the 2016 typical with some unusual features, or will it in retrospect seem unusual? The answer to this question depends on the research question and the variables of interest. As a result, elections scholars may need to think more deeply about the kinds of questions we pursue and the theoretical assumptions we make. However, we must also wait to find out the impact of 2016 on subsequent contests. As we attempt to classify the 2016 election, we are stuck doing some guesswork. Noel urges scholars to ask how an outlier can sharpen our theories. Masket and Victor both pose the question of whether last year’s contest will turn out to have been anomalous or a new normal. Finally, Shapiro asks whether the election was really so unusual after all. These different classifications suggest not just different interpretations, but that the implications of 2016 depend on what the researcher seeks to explain.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2017.1400298","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42623862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Study of Salary Differentials by Gender and Discipline 性别与学科薪酬差异研究

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2017.1317223

L. Billard

{"title":"Study of Salary Differentials by Gender and Discipline","authors":"L. Billard","doi":"10.1080/2330443X.2017.1317223","DOIUrl":"https://doi.org/10.1080/2330443X.2017.1317223","url":null,"abstract":"ABSTRACT Although it is 45 years since legislation made gender discrimination on university campuses illegal, salary inequities continue to exist today. The seminal work in studying the existence of salary inequities is that of the American Association of University Professors (AAUP), by Scott (1977) and Gray (1980). Subsequently, innumerable analyses based on versions of their multiple regression model have been published. Salary is the dependent variable and is modeled to depend on various independent predictor variables such as years employed. Often, indicator terms, for gender and/or discipline are included in the model as independent predicator variables. Unfortunately, many of these studies are not well grounded in basic statistical science. The most glaring omission is the failure to include indicator by predictor interaction terms in the model when required. The present work draws attention to the broader implications of using these models incorrectly, and the difficulties that ensue when they are not built on an appropriate sound statistical framework. Another issue surrounds the inclusion of “tainted” predictor variables that are themselves gender-biased, the most contentious being the (intuitive) choice of rank. Therefore, a brief look at this issue is included; unfortunately, it is shown that rank still today seems to persist as a tainted variable.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2017.1317223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42262339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Superfund Locations and Potential Associations with Cancer Incidence in Florida 超级基金在佛罗里达州的位置及其与癌症发病率的潜在联系

IF 1.6

Statistics and Public Policy Pub Date : 2017-01-01 DOI: 10.1080/2330443X.2016.1267599

A. Kirpich, E. Leary

{"title":"Superfund Locations and Potential Associations with Cancer Incidence in Florida","authors":"A. Kirpich, E. Leary","doi":"10.1080/2330443X.2016.1267599","DOIUrl":"https://doi.org/10.1080/2330443X.2016.1267599","url":null,"abstract":"ABSTRACT Uncontrolled hazardous wastes sites have the potential to adversely impact human health and damage or disrupt ecological systems and the greater environment. Four decades have passed since the Superfund law was enacted, allowing increased exposure time to these potential health hazards while also allowing advancement of analysis techniques. Florida has the sixth highest number of Superfund sites in the US and, in 2016, Florida was projected to have the second largest number of new cancer cases in the US. We explore statewide cancer incidence in Florida from 1986 to 2010 to determine if differences or associations exist in counties containing Superfund sites compared to counties that do not. To investigate potential environmental associations with cancer incidence; results using spatial and nonspatial mixed models were compared. Using a Poisson–Gamma mixture model, our results provide some evidence of an association between cancer incidence rates and Superfund site hazard levels, as well as proxy measures of water contamination around Superfund sites. In addition, results build upon previously observed gender differences in cancer incidence rates and further indicate spatial differences for cancer incidence. Heterogeneity among cancer incidence rates were observed across Florida with some mild association with Superfund exposure proxies.","PeriodicalId":43397,"journal":{"name":"Statistics and Public Policy","volume":null,"pages":null},"PeriodicalIF":1.6,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/2330443X.2016.1267599","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46718814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6