发布求助
文献互助 智能选刊 最新文献

Journal of Survey Statistics and Methodology最新文献

筛选
英文 中文
On The Robustness Of Respondent-Driven Sampling Estimators To Measurement Error. 调查对象驱动抽样估计器对测量误差的鲁棒性研究。
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-04-01 DOI: 10.1093/jssam/smab056
Ian E Fellows
{"title":"On The Robustness Of Respondent-Driven Sampling Estimators To Measurement Error.","authors":"Ian E Fellows","doi":"10.1093/jssam/smab056","DOIUrl":"https://doi.org/10.1093/jssam/smab056","url":null,"abstract":"<p><p>Respondent-driven sampling (RDS) is a popular method of conducting surveys in hard to reach populations where strong assumptions are required in order to make valid statistical inferences. In this paper we investigate the assumption that network degrees are measured accurately by the RDS survey and find that there is likely significant measurement error present in typical studies. We prove that most RDS estimators remain consistent under an imperfect measurement model with little to no added bias, though the variance of the estimators does increase.</p>","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"10 2","pages":"377-396"},"PeriodicalIF":2.1,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014508/pdf/smab056.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10483066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
On The Robustness Of Respondent-Driven Sampling Estimators To Measurement Error. 论被调查者驱动的抽样估计对测量误差的稳健性。
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-03-11 DOI: 10.1093/jssam/smac004
Ian E. Fellows
{"title":"On The Robustness Of Respondent-Driven Sampling Estimators To Measurement Error.","authors":"Ian E. Fellows","doi":"10.1093/jssam/smac004","DOIUrl":"https://doi.org/10.1093/jssam/smac004","url":null,"abstract":"Respondent-driven sampling (RDS) is a popular method of conducting surveys in hard to reach populations where strong assumptions are required in order to make valid statistical inferences. In this paper we investigate the assumption that network degrees are measured accurately by the RDS survey and find that there is likely significant measurement error present in typical studies. We prove that most RDS estimators remain consistent under an imperfect measurement model with little to no added bias, though the variance of the estimators does increase.","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"10 2 1","pages":"377-396"},"PeriodicalIF":2.1,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45789287","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: 2
Panel Conditioning in a German Probability-Based Longitudinal Study: A Comparison of Respondents with Different Levels of Survey Experience 德国基于概率的纵向研究中的面板调节:不同调查经验水平的受访者的比较
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-02-22 DOI: 10.31235/osf.io/vd5xp
Fabienne Kraemer, Henning Silber, Bella Struminskaya, M. Bošnjak, J. Kossmann, Bernd Weiss
{"title":"Panel Conditioning in a German Probability-Based Longitudinal Study: A Comparison of Respondents with Different Levels of Survey Experience","authors":"Fabienne Kraemer, Henning Silber, Bella Struminskaya, M. Bošnjak, J. Kossmann, Bernd Weiss","doi":"10.31235/osf.io/vd5xp","DOIUrl":"https://doi.org/10.31235/osf.io/vd5xp","url":null,"abstract":"Learning effects due to repeated interviewing, which are referred to as panel conditioning, are a major threat to response quality in later waves of a panel study. Up to date, research has not provided a clear picture regarding the circumstances, mechanisms, and dimensions of potential panel conditioning effects. Especially the effects of conditioning frequency, that is, different levels of experience within a panel, on response quality are underexplored. Against this background, we investigated the effects of panel conditioning by using data from the GESIS Panel, a German mixed-mode probability-based panel study. Using two refreshment samples, we compared three panel cohorts with differing levels of experience with respect to several response quality indicators related to the mechanisms of reflection, satisficing, and social desirability. Overall, we find evidence for both negative (i.e., disadvantageous for response quality) as well as positive (i.e., advantageous for response quality) panel conditioning. Highly experienced respondents were more likely to satisfice by selecting mid-point responses or by speeding through the questionnaire. They also had a higher probability of refusing to answer sensitive questions than less experienced panel members. However, more experienced respondents were also more likely to optimize the response processes by needing less time compared to panelists with lower experience levels (when controlling for speeding). In contrast, we did not find significant differences with respect to the number of “don’t know” responses, non-differentiation, the selection of first response categories, and the number of non-triggered filter questions. Of the observed differences, speeding showed the highest magnitude with an average increase of 5.9 percentage points for highly experienced panel members compared to low experienced panelists.","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":" ","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44830407","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
Inference from Nonrandom Samples Using Bayesian Machine Learning. 使用贝叶斯机器学习从非随机样本推断。
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-01-20 eCollection Date: 2023-04-01 DOI: 10.1093/jssam/smab049
Yutao Liu, Andrew Gelman, Qixuan Chen
{"title":"Inference from Nonrandom Samples Using Bayesian Machine Learning.","authors":"Yutao Liu,&nbsp;Andrew Gelman,&nbsp;Qixuan Chen","doi":"10.1093/jssam/smab049","DOIUrl":"10.1093/jssam/smab049","url":null,"abstract":"<p><p>We consider inference from nonrandom samples in data-rich settings where high-dimensional auxiliary information is available both in the sample and the target population, with survey inference being a special case. We propose a regularized prediction approach that predicts the outcomes in the population using a large number of auxiliary variables such that the ignorability assumption is reasonable and the Bayesian framework is straightforward for quantification of uncertainty. Besides the auxiliary variables, we also extend the approach by estimating the propensity score for a unit to be included in the sample and also including it as a predictor in the machine learning models. We find in simulation studies that the regularized predictions using soft Bayesian additive regression trees yield valid inference for the population means and coverage rates close to the nominal levels. We demonstrate the application of the proposed methods using two different real data applications, one in a survey and one in an epidemiologic study.</p>","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"11 2","pages":"433-455"},"PeriodicalIF":2.1,"publicationDate":"2022-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10080218/pdf/smab049.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9637930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
OUP accepted manuscript OUP接受稿件
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-01-01 DOI: 10.1093/jssam/smac009
{"title":"OUP accepted manuscript","authors":"","doi":"10.1093/jssam/smac009","DOIUrl":"https://doi.org/10.1093/jssam/smac009","url":null,"abstract":"","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61006227","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
OUP accepted manuscript OUP接受稿件
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-01-01 DOI: 10.1093/jssam/smac002
{"title":"OUP accepted manuscript","authors":"","doi":"10.1093/jssam/smac002","DOIUrl":"https://doi.org/10.1093/jssam/smac002","url":null,"abstract":"","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61006491","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: 1
OUP accepted manuscript OUP接受稿件
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-01-01 DOI: 10.1093/jssam/smac003
{"title":"OUP accepted manuscript","authors":"","doi":"10.1093/jssam/smac003","DOIUrl":"https://doi.org/10.1093/jssam/smac003","url":null,"abstract":"","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61006522","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
OUP accepted manuscript OUP接受稿件
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-01-01 DOI: 10.1093/jssam/smac011
{"title":"OUP accepted manuscript","authors":"","doi":"10.1093/jssam/smac011","DOIUrl":"https://doi.org/10.1093/jssam/smac011","url":null,"abstract":"","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61006373","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: 1
OUP accepted manuscript OUP接受稿件
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-01-01 DOI: 10.1093/jssam/smac005
{"title":"OUP accepted manuscript","authors":"","doi":"10.1093/jssam/smac005","DOIUrl":"https://doi.org/10.1093/jssam/smac005","url":null,"abstract":"","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61006569","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: 2
OUP accepted manuscript OUP接受稿件
IF 2.1 4区 数学
Journal of Survey Statistics and Methodology Pub Date : 2022-01-01 DOI: 10.1093/jssam/smac014
{"title":"OUP accepted manuscript","authors":"","doi":"10.1093/jssam/smac014","DOIUrl":"https://doi.org/10.1093/jssam/smac014","url":null,"abstract":"","PeriodicalId":17146,"journal":{"name":"Journal of Survey Statistics and Methodology","volume":"1 1","pages":""},"PeriodicalIF":2.1,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"61006749","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: 3
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信