Journal of Survey Statistics and Methodology最新文献_第4页

Pseudo-Bayesian Small-Area Estimation 伪贝叶斯小面积估计

IF 2.1 4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-06-19 DOI: 10.1093/jssam/smad012

G. Datta, Juhyung Lee, Jiacheng Li

{"title":"Pseudo-Bayesian Small-Area Estimation","authors":"G. Datta, Juhyung Lee, Jiacheng Li","doi":"10.1093/jssam/smad012","DOIUrl":"https://doi.org/10.1093/jssam/smad012","url":null,"abstract":"\u0000 In sample surveys, a subpopulation is referred to as a “small area” or “small domain” if it does not have a large enough sample that alone will yield an adequately accurate estimate of a characteristic. In small-area estimation, the sample size from various subpopulations is often too small to accurately estimate its mean, and so one borrows strength from similar subpopulations through an appropriate model based on relevant covariates. The empirical best linear unbiased prediction (EBLUP) method has been the dominant frequentist model-based approach in small-area estimation. This method relies on estimation of model parameters based on the marginal distribution of the data. As an alternative to this method, the observed best prediction (OBP) method estimates the parameters by minimizing an objective function that is implied by the total mean squared prediction error. We use this objective function in the Fay–Herriot model to construct a pseudo-posterior distribution for the model parameters under nearly noninformative priors for them. Data analysis and simulation show that the pseudo-Bayesian estimators (PBEs) compete favorably with the OBPs and EBLUPs. The PBE estimates are robust to mean misspecification and have good frequentist properties. Being Bayesian by construction, they automatically avoid negative estimates of standard errors, enjoy a dual justification, and provide an attractive alternative to practitioners.","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48464247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Maximum Entropy Design by a Markov Chain Process 马尔可夫链过程的最大熵设计

4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-06-14 DOI: 10.1093/jssam/smad010

Yves Tillé, Bardia Panahbehagh

引用次数: 0

A Comprehensive Overview of Unit-Level Modeling of Survey Data for Small Area Estimation Under Informative Sampling 信息抽样下小面积估算调查数据的单位级建模综述

4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-06-14 DOI: 10.1093/jssam/smad020

Paul A Parker, Ryan Janicki, Scott H Holan

引用次数: 2

Comparison of Unit-Level Small Area Estimation Modeling Approaches for Survey Data Under Informative Sampling 信息抽样下调查数据单位级小面积估算建模方法比较

4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-06-14 DOI: 10.1093/jssam/smad022

Paul A Parker, Ryan Janicki, Scott H Holan

引用次数: 1

Leveraging Predictive Modelling from Multiple Sources of Big Data to Improve Sample Efficiency and Reduce Survey Nonresponse Error 利用多来源大数据的预测建模，提高样本效率，减少调查无响应误差

IF 2.1 4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-06-10 DOI: 10.1093/jssam/smad016

David Dutwin, Patrick Coyle, I. Bilgen, N. English

{"title":"Leveraging Predictive Modelling from Multiple Sources of Big Data to Improve Sample Efficiency and Reduce Survey Nonresponse Error","authors":"David Dutwin, Patrick Coyle, I. Bilgen, N. English","doi":"10.1093/jssam/smad016","DOIUrl":"https://doi.org/10.1093/jssam/smad016","url":null,"abstract":"\u0000 Big data has been fruitfully leveraged as a supplement for survey data—and sometimes as its replacement—and in the best of worlds, as a “force multiplier” to improve survey analytics and insight. We detail a use case, the big data classifier (BDC), as a replacement to the more traditional methods of targeting households in survey sampling for given specific household and personal attributes. Much like geographic targeting and the use of commercial vendor flags, we detail the ability of BDCs to predict the likelihood that any given household is, for example, one that contains a child or someone who is Hispanic. We specifically build 15 BDCs with the combined data from a large nationally representative probability-based panel and a range of big data from public and private sources, and then assess the effectiveness of these BDCs to successfully predict their range of predicted attributes across three large survey datasets. For each BDC and each data application, we compare the relative effectiveness of the BDCs against historical sample targeting techniques of geographic clustering and vendor flags. Overall, BDCs offer a modest improvement in their ability to target subpopulations. We find classes of predictions that are consistently more effective, and others where the BDCs are on par with vendor flagging, though always superior to geographic clustering. We present some of the relative strengths and weaknesses of BDCs as a new method to identify and subsequently sample low incidence and other populations.","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45867293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Primer on the Data Cleaning Pipeline 数据清洗管道入门

4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-05-31 DOI: 10.1093/jssam/smad017

Rebecca C Steorts

引用次数: 1

Correction to: Improving Statistical Matching when Auxiliary Information is Available 修正:当辅助信息可用时，改进统计匹配

4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-05-30 DOI: 10.1093/jssam/smad023

引用次数: 0

Is there a Day of the Week Effect on Panel Response Rate to an Online Questionnaire Email Invitation? 对在线问卷邮件邀请的小组回复率是否有一周中的某一天的影响?

IF 2.1 4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-05-26 DOI: 10.1093/jssam/smad014

Chloe Howard, Lara M. Greaves, D. Osborne, C. Sibley

引用次数: 0

Interviewer Involvement in Respondent Selection Moderates the Relationship between Response Rates and Sample Bias in Cross-National Survey Projects in Europe 访谈者参与受访者选择调节回复率和样本偏差在欧洲跨国调查项目之间的关系

IF 2.1 4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-05-18 DOI: 10.1093/jssam/smad013

M. Kołczyńska, P. Jabkowski, S. Eckman

{"title":"Interviewer Involvement in Respondent Selection Moderates the Relationship between Response Rates and Sample Bias in Cross-National Survey Projects in Europe","authors":"M. Kołczyńska, P. Jabkowski, S. Eckman","doi":"10.1093/jssam/smad013","DOIUrl":"https://doi.org/10.1093/jssam/smad013","url":null,"abstract":"\u0000 Survey researchers and practitioners often assume that higher response rates are associated with a higher quality of survey data. However, the evidence for this claim in face-to-face surveys is mixed. To explain these mixed results, recent studies have proposed that interviewers’ involvement in respondent selection moderates the effect of response rates on data quality. Previous analyses based on data from the European Social Survey found that response rates are positively associated with data quality when interviewer involvement in respondent selection is minimal. However, the association between response rates and data quality is negative when interviewers are more involved in respondent selection through household frame creation or within-household selection of target persons. These studies have hypothesized that some interviewers deviate from prescribed selection procedures to select individuals with higher response propensities, which increase response rates while reducing data quality. We replicate these results with an extended dataset, including more recent European Social Survey rounds and three other European survey projects: the European Quality of Life Survey, European Values Study, and International Social Survey Programme. Based on our results, we recommend that surveys include procedures to verify respondent-selection practices into their fieldwork control procedures.","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46265346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of Covid-19 Prevalence Dynamics from Pooled Data 从汇总数据估计新冠肺炎患病率动态

IF 2.1 4区数学

Journal of Survey Statistics and Methodology Pub Date : 2023-05-12 DOI: 10.1093/jssam/smad011

Braden Scherting, A. Peel, R. Plowright, A. Hoegh

引用次数: 2