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Martyna Daria Swiatczak; Michael Baumgartner – Sociological Methods & Research, 2025
In this paper, we investigate the conditions under which data imbalances, a common data characteristic that occurs when factor values are unevenly distributed, are problematic for the performance of Coincidence Analysis (CNA). We further examine how such imbalances relate to fragmentation and noise in data. We show that even extreme data…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Statistical Distributions
Dorie, Vincent; Hill, Jennifer; Shalit, Uri; Scott, Marc; Cervone, Daniel – Grantee Submission, 2018
Statisticians have made great progress in creating methods that reduce our reliance on parametric assumptions. However this explosion in research has resulted in a breadth of inferential strategies that both create opportunities for more reliable inference as well as complicate the choices that an applied researcher has to make and defend.…
Descriptors: Statistical Inference, Simulation, Causal Models, Research Methodology
Ding, Peng; Dasgupta, Tirthankar – Grantee Submission, 2017
Fisher randomization tests for Neyman's null hypothesis of no average treatment effects are considered in a finite population setting associated with completely randomized experiments with more than two treatments. The consequences of using the F statistic to conduct such a test are examined both theoretically and computationally, and it is argued…
Descriptors: Statistical Analysis, Statistical Inference, Causal Models, Error Patterns
Ali, Usama S.; Walker, Michael E. – ETS Research Report Series, 2014
Two methods are currently in use at Educational Testing Service (ETS) for equating observed item difficulty statistics. The first method involves the linear equating of item statistics in an observed sample to reference statistics on the same items. The second method, or the item response curve (IRC) method, involves the summation of conditional…
Descriptors: Difficulty Level, Test Items, Equated Scores, Causal Models
Imbens, Guido W.; Rubin, Donald B. – Cambridge University Press, 2015
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding…
Descriptors: Causal Models, Statistical Inference, Statistics, Social Sciences
Sun, Shuyan; Pan, Wei – Journal of Experimental Education, 2013
Regression discontinuity design is an alternative to randomized experiments to make causal inference when random assignment is not possible. This article first presents the formal identification and estimation of regression discontinuity treatment effects in the framework of Rubin's causal model, followed by a thorough literature review of…
Descriptors: Regression (Statistics), Computation, Accuracy, Causal Models
Wang, Tianyou; Lee, Won-Chan; Brennan, Robert L.; Kolen, Michael J. – Applied Psychological Measurement, 2008
This article uses simulation to compare two test equating methods under the common-item nonequivalent groups design: the frequency estimation method and the chained equipercentile method. An item response theory model is used to define the true equating criterion, simulate group differences, and generate response data. Three linear equating…
Descriptors: Equated Scores, Item Response Theory, Simulation, Comparative Analysis
Rosenthal, James A. – Springer, 2011
Written by a social worker for social work students, this is a nuts and bolts guide to statistics that presents complex calculations and concepts in clear, easy-to-understand language. It includes numerous examples, data sets, and issues that students will encounter in social work practice. The first section introduces basic concepts and terms to…
Descriptors: Statistics, Data Interpretation, Social Work, Social Science Research
Prodromou, Theodosia; Pratt, Dave – Statistics Education Research Journal, 2006
Our primary goal is to design a micro world which aspires to research thinking-in-change about distribution. Our premise, in line with a constructivist approach and our prior research, is that thinking about distribution must develop from causal meanings already established. This study reports on a design research study of how students appear to…
Descriptors: Constructivism (Learning), Secondary School Students, Foreign Countries, Computer Software