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Julian Schuessler; Peter Selb – Sociological Methods & Research, 2025
Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of…
Descriptors: Data Collection, Graphs, Error of Measurement, Statistical Bias
Shiyu Zhang; James Wagner – Sociological Methods & Research, 2024
Adaptive survey design refers to using targeted procedures to recruit different sampled cases. This technique strives to reduce bias and variance of survey estimates by trying to recruit a larger and more balanced set of respondents. However, it is not well understood how adaptive design can improve data and survey estimates beyond the…
Descriptors: Surveys, Research Design, Response Rates (Questionnaires), Demography
Dana Garbarski; Jennifer Dykema; Cameron P. Jones; Tiffany S. Neman; Nora Cate Schaeffer; Dorothy Farrar Edwards – Field Methods, 2024
Ethnoracial identity refers to the racial and ethnic categories that people use to classify themselves and others. How it is measured in surveys has implications for understanding inequalities. Yet how people self-identify may not conform to the categories standardized survey questions use to measure ethnicity and race, leading to potential…
Descriptors: Ethnicity, Racial Identification, Classification, Error of Measurement
Buckley, Jeffrey; Hyland, Tomás; Seery, Niall – International Journal of Technology and Design Education, 2023
Technology education research is a growing field, with the rate of growth increasing over the last 2 decades. As the field grows, it is paramount that credibility is maintained in published findings. To date there is no evidence to suggest a lack trust is warranted, however in the midst of the replication crisis there is need to ensure continued…
Descriptors: Technology Education, Educational Research, Replication (Evaluation), Credibility
Simsek, Ahmet Salih – International Journal of Assessment Tools in Education, 2023
Likert-type item is the most popular response format for collecting data in social, educational, and psychological studies through scales or questionnaires. However, there is no consensus on whether parametric or non-parametric tests should be preferred when analyzing Likert-type data. This study examined the statistical power of parametric and…
Descriptors: Error of Measurement, Likert Scales, Nonparametric Statistics, Statistical Analysis
Davidow, Jason H.; Ye, Jun; Edge, Robin L. – International Journal of Language & Communication Disorders, 2023
Background: Speech-language pathologists often multitask in order to be efficient with their commonly large caseloads. In stuttering assessment, multitasking often involves collecting multiple measures simultaneously. Aims: The present study sought to determine reliability when collecting multiple measures simultaneously versus individually.…
Descriptors: Graduate Students, Measurement, Reliability, Group Activities
Lottridge, Sue; Burkhardt, Amy; Boyer, Michelle – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Sue Lottridge, Amy Burkhardt, and Dr. Michelle Boyer provide an overview of automated scoring. Automated scoring is the use of computer algorithms to score unconstrained open-ended test items by mimicking human scoring. The use of automated scoring is increasing in educational assessment programs because it allows…
Descriptors: Computer Assisted Testing, Scoring, Automation, Educational Assessment
Keusch, Florian; Bähr, Sebastian; Haas, Georg-Christoph; Kreuter, Frauke; Trappmann, Mark – Sociological Methods & Research, 2023
Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often. While smartphones are commonly used in some groups of individuals, smartphone penetration is significantly lower in other groups. In addition, different operating systems (OSs) limit how mobile data…
Descriptors: National Surveys, Computer Software, Telecommunications, Handheld Devices
Adrian Adams; Lauren Barth-Cohen – CBE - Life Sciences Education, 2024
In undergraduate research settings, students are likely to encounter anomalous data, that is, data that do not meet their expectations. Most of the research that directly or indirectly captures the role of anomalous data in research settings uses post-hoc reflective interviews or surveys. These data collection approaches focus on recall of past…
Descriptors: Undergraduate Students, Physics, Science Instruction, Laboratory Experiments
Keusch, Florian; Leonard, Mariel M.; Sajons, Christoph; Steiner, Susan – Sociological Methods & Research, 2021
Researchers attempting to survey refugees over time face methodological issues because of the transient nature of the target population. In this article, we examine whether applying smartphone technology could alleviate these issues. We interviewed 529 refugees and afterward invited them to four follow-up mobile web surveys and to install a…
Descriptors: Handheld Devices, Telecommunications, Ownership, Computer Software
Rosenberg, Molly; Townes, Ashley; Taylor, Shaneil; Luetke, Maya; Herbenick, Debby – Journal of American College Health, 2019
Objective: To understand how missing data may influence conclusions drawn from campus sexual assault surveys. Methods: We systematically reviewed 40 surveys from 2010-2016. We constructed a pseudo-population of the total population targeted across schools, creating records proportional to the respective response rate and reported sexual assault…
Descriptors: Sexual Abuse, Crime, Student Surveys, Incidence
Fellers, Pamela S.; Kuiper, Shonda – Journal of Statistics Education, 2020
Increasingly students, particularly those in the social sciences, work with survey data collected through a more complex sampling method than a simple random sample. Failing to understand how to properly approach survey data can lead to inaccurate results. In this article, we describe a series of online data visualization applications and…
Descriptors: Statistics, Introductory Courses, Teaching Methods, Concept Formation
Ching, Cynthia Carter; Hagood, Danielle – Journal of Science Education and Technology, 2019
This paper connects the technological practice of activity monitor gaming to the Next Generation Science Standards (NGSS) science and engineering practice of "analyzing and interpreting data," and to the foundational constructionist idea of personal meaning. In our larger study, eighth-grade students, ages 12-14, wore physical activity…
Descriptors: Middle School Students, Grade 8, Educational Games, Academic Standards
Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…
Descriptors: Error of Measurement, Monte Carlo Methods, Data Collection, Simulation
Buelens, Bart; van den Brakel, Jan A. – Sociological Methods & Research, 2015
Mixed-mode surveys are known to be susceptible to mode-dependent selection and measurement effects, collectively referred to as mode effects. The use of different data collection modes within the same survey may reduce selectivity of the overall response but is characterized by measurement errors differing across modes. Inference in sample surveys…
Descriptors: Error of Measurement, Surveys, Crime, Victims