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Sperandei, Sandro; Bastos, Leonardo Soares; Ribeiro-Alves, Marcelo; Reis, Arianne; Bastos, Francisco Inácio – International Journal of Social Research Methodology, 2023
The aim of this study is to investigate the impact of different logistic regression estimators applied to RDS studies via simulation and the analysis of empirical data. Four simulated populations were created with different connectivity characteristics. Each simulated individual received two attributes, one of them associated to the infection…
Descriptors: Regression (Statistics), Recruitment, Sampling, Simulation
Groth, Randall; Rickards, Megan; Roehm, Elizabeth – Statistics Education Research Journal, 2023
In this report, we analyze students' learning of compound probability by describing connections they generated while engaged with tasks involving two independent events. Several of their connections were compatible with the development of expertise, such as recognizing the need to determine sample spaces across a variety of situations and noting…
Descriptors: Statistics Education, Probability, Concept Formation, Sampling
Cheng, Siwei – Sociological Methods & Research, 2023
One of the most important developments in the current era of social sciences is the growing availability and diversity of data, big and small. Social scientists increasingly combine information from multiple data sets in their research. While conducting statistical analyses with linked data is relatively straightforward, borrowing information…
Descriptors: Social Science Research, Statistical Analysis, Statistical Distributions, Statistical Bias
Wendy Chan; Jimin Oh; Chen Li; Jiexuan Huang; Yeran Tong – Society for Research on Educational Effectiveness, 2023
Background: The generalizability of a study's results continues to be at the forefront of concerns in evaluation research in education (Tipton & Olsen, 2018). Over the past decade, statisticians have developed methods, mainly based on propensity scores, to improve generalizations in the absence of random sampling (Stuart et al., 2011; Tipton,…
Descriptors: Generalizability Theory, Probability, Scores, Sampling
Pashley, Nicole E.; Miratrix, Luke W. – Journal of Educational and Behavioral Statistics, 2022
Several branches of the potential outcome causal inference literature have discussed the merits of blocking versus complete randomization. Some have concluded it can never hurt the precision of estimates, and some have concluded it can hurt. In this article, we reconcile these apparently conflicting views, give a more thorough discussion of what…
Descriptors: Research Design, Experimental Groups, Control Groups, Sampling
Molina, José Luis; Lubbers, Miranda J.; Hâncean, Marian-Gabriel; Fradejas-García, Ignacio – Field Methods, 2022
Thanks to the latest developments in network-oriented sampling, it is now possible to measure "transnational social fields," or emergent social structures that connect places or regions in different countries. These structures are instrumental in explaining sociocultural phenomena like the emergence of ethnic or demographic enclaves,…
Descriptors: Social Structure, Sociocultural Patterns, Sampling, Foreign Countries
Judith Schoonenboom – Journal of Mixed Methods Research, 2024
Fetters et al.'s (2013) mixed methods integration framework uses construction metaphors: building, connecting, merging, and embedding. In a similar vein, this article uses an architectural metaphor and introduces design patterns as building blocks for mixed methods research design. A design pattern embeds one specific design decision into its…
Descriptors: Mixed Methods Research, Research Design, Comparative Analysis, Figurative Language
Eva Shin; Caitlin Ravichandran; Danielle Renzi; Barbara R. Pober; Christopher J. McDougle; Robyn P. Thom – Journal of Autism and Developmental Disorders, 2024
Purpose: This study describes participant diversity in Williams syndrome (WS) intervention studies. Methods: A literature search was conducted to identify prospective treatment studies including participants with WS. Data was extracted on the reporting of and information provided on age, sex, cognitive ability, socioeconomic status, race, and…
Descriptors: Genetic Disorders, Disabilities, Cognitive Ability, Socioeconomic Status
Meng Qiu; Ke-Hai Yuan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Latent class analysis (LCA) is a widely used technique for detecting unobserved population heterogeneity in cross-sectional data. Despite its popularity, the performance of LCA is not well understood. In this study, we evaluate the performance of LCA with binary data by examining classification accuracy, parameter estimation accuracy, and coverage…
Descriptors: Classification, Sample Size, Monte Carlo Methods, Social Science Research
Jiaying Xiao; Chun Wang; Gongjun Xu – Grantee Submission, 2024
Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…
Descriptors: Error of Measurement, Models, Evaluation Methods, Item Analysis
Afshar, Hassan Soodmand; Ranjbar, Naser – Iranian Journal of Language Teaching Research, 2023
The quality of mixing methods has been widely debated in the field of applied linguistics (AL) and the integration of data from both quantitative and qualitative research paradigms has always been open to controversy. The present study was aimed at recognizing the status quo of MMR in AL, investigating the nature of various sections of MMR…
Descriptors: Mixed Methods Research, Applied Linguistics, Research Reports, Sampling
Paganin, Sally; Paciorek, Christopher J.; Wehrhahn, Claudia; Rodríguez, Abel; Rabe-Hesketh, Sophia; de Valpine, Perry – Journal of Educational and Behavioral Statistics, 2023
Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions based on Dirichlet process mixtures (DPMs) offer a more flexible representation of the unknown distribution of the latent trait. However, the use of such models in the IRT…
Descriptors: Bayesian Statistics, Item Response Theory, Guidance, Evaluation Methods
van Aert, Robbie C. M. – Research Synthesis Methods, 2023
The partial correlation coefficient (PCC) is used to quantify the linear relationship between two variables while taking into account/controlling for other variables. Researchers frequently synthesize PCCs in a meta-analysis, but two of the assumptions of the common equal-effect and random-effects meta-analysis model are by definition violated.…
Descriptors: Correlation, Meta Analysis, Sampling, Simulation
Blasko, Alyssa M.; Morin, Kristi L.; Bauer, Kathleen; Johnson, Kelsey M.; Enriquez, Grace B.; Hunsicker, Lindsey E.; Tasik, Emily J.; Renz, Theodore E., III – Journal of Special Education, 2023
Most disability research is conducted in high-income countries, despite much of the world's population living in low- and middle-income countries. Given the flexible nature of qualitative research, studies using this methodology have the potential to provide important insights into how disability is perceived across the globe. The aim of the…
Descriptors: Foreign Countries, Disabilities, Research, Research Methodology
Is the Acknowledgment of Earned Entitlement Effect Robust across Experimental Modes and Populations?
Barr, Abigail; Miller, Luis; Ubeda, Paloma – Sociological Methods & Research, 2023
We present a set of studies the objective of which was to test the robustness of the acknowledgment of earned entitlement effect across different experimental modes and populations. We present three sets of results. The first is derived from a between-subject analysis of two independent, but comparable samples of nonstudent adults. One sample…
Descriptors: Robustness (Statistics), Sampling, Surveys, Validity

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