The Design and Optimality of Survey Counts: A Unified Framework Via the Fisher Information Maximizer [0.03%]
基于Fisher信息最大化的抽样调查计数的设计与优化：统一框架
Xin Guo,Qiang Fu
Xin Guo
Grouped and right-censored (GRC) counts have been used in a wide range of attitudinal and behavioural surveys yet they cannot be readily analyzed or assessed by conventional statistical models. This study develops a unified regression frame...
Applying Responsive Survey Design to Small-Scale Surveys: Campus Surveys of Sexual Misconduct [0.03%]
适应性调查设计在小型调查中的应用——校园性骚扰调查
William G Axinn,James Wagner,Mick Couper et al.
William G Axinn et al.
Responsive survey design is a technique aimed at improving the efficiency or quality of surveys by using incoming data from the field to make design changes. The technique was pioneered on large national surveys, but the tools can also be a...
Robyn Rap,Pamela Paxton
Robyn Rap
Questions on voluntary association memberships have been used extensively in social scientific research for decades. Researchers generally assume that these respondent self-reports are accurate, but their measurement has never been assessed...
Matthew DeBell,Jon A Krosnick,Katie Gera et al.
Matthew DeBell et al.
Postelection surveys regularly overestimate voter turnout by 10 points or more. This article provides the first comprehensive documentation of the turnout gap in three major ongoing surveys (the General Social Survey, Current Population Sur...
The Potential for Using a Shortened Version of the Everyday Discrimination Scale in Population Research with Young Adults: A Construct Validation Investigation [0.03%]
everyday discrimination量表简版在青年群体中使用的有效性研究
Aprile D Benner,Shanting Chen,Celeste C Fernandez et al.
Aprile D Benner et al.
Discrimination is associated with numerous psychological health outcomes over the life course. The nine-item Everyday Discrimination Scale (EDS) is one of the most widely used measures of discrimination; however, this nine-item measure may ...
Machine Learning as a Model for Cultural Learning: Teaching an Algorithm What it Means to be Fat [0.03%]
机器学习的文化教育模型：教会算法“肥胖”的含义
Alina Arseniev-Koehler,Jacob G Foster
Alina Arseniev-Koehler
Public culture is a powerful source of cognitive socialization; for example, media language is full of meanings about body weight. Yet it remains unclear how individuals process meanings in public culture. We suggest that schema learning is...
Kristian Bernt Karlson,Frank Popham,Anders Holm
Kristian Bernt Karlson
This article presents two ways of quantifying confounding using logistic response models for binary outcomes. Drawing on the distinction between marginal and conditional odds ratios in statistics, we define two corresponding measures of con...
The Age-Period-Cohort-Interaction Model for Describing and Investigating Inter-cohort Deviations and Intra-cohort Life-course Dynamics [0.03%]
用于描述和探究队列间偏差及队列内生命历程动态的年龄-时期-队列交互作用模型
Liying Luo,James S Hodges
Liying Luo
Social scientists have frequently sought to understand the distinct effects of age, period, and cohort, but disaggregation of the three dimensions is difficult because cohort = period - age. We argue that this technical difficulty reflects ...
Daniel Schneider,Kristen Harknett
Daniel Schneider
In this paper, we explore the use of Facebook targeted advertisements for the collection of survey data. We illustrate the potential of survey sampling and recruitment on Facebook through the example of building a large employee-employer li...
The Future Strikes Back: Using Future Treatments to Detect and Reduce Hidden Bias [0.03%]
未雨绸缪：利用未来疗法发现和减少隐藏偏差
Felix Elwert,Fabian T Pfeffer
Felix Elwert
Conventional advice discourages controlling for postoutcome variables in regression analysis. By contrast, we show that controlling for commonly available postoutcome (i.e., future) values of the treatment variable can help detect, reduce, ...