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Kenneth A. Frank; Qinyun Lin; Spiro J. Maroulis – Grantee Submission, 2024
In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…
Descriptors: Causal Models, Statistical Inference, Observation, Educational Policy
Wilhelmina van Dijk; Cynthia U. Norris; Sara A. Hart – Grantee Submission, 2022
Randomized control trials are considered the pinnacle for causal inference. In many cases, however, randomization of participants in social work research studies is not feasible or ethical. This paper introduces the co-twin control design study as an alternative quasi-experimental design to provide evidence of causal mechanisms when randomization…
Descriptors: Twins, Research Design, Randomized Controlled Trials, Quasiexperimental Design
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Ulriksen, Marianne S.; Dadalauri, Nina – International Journal of Social Research Methodology, 2016
Single case studies can provide vital contributions to theory-testing in social science studies. Particularly, by applying the process-tracing method, case studies can test theoretical frameworks through a rigorous research design that ensures substantial empirical leverage. While most scholarly contributions on process-tracing focus on either…
Descriptors: Case Studies, Hypothesis Testing, Social Science Research, Research Methodology
Reardon, Sean F.; Raudenbush, Stephen W. – Society for Research on Educational Effectiveness, 2011
The purpose of this paper is to clarify the assumptions that must be met if this--multiple site, multiple mediator--strategy, hereafter referred to as "MSMM," is to identify the average causal effects (ATE) in the populations of interest. The authors' investigation of the assumptions of the multiple-mediator, multiple-site IV model demonstrates…
Descriptors: Educational Research, Social Science Research, Research Design, Causal Models
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Markus, Keith A. – Multivariate Behavioral Research, 2008
One can distinguish statistical models used in causal modeling from the causal interpretations that align them with substantive hypotheses. Causal modeling typically assumes an efficient causal interpretation of the statistical model. Causal modeling can also make use of mereological causal interpretations in which the state of the parts…
Descriptors: Research Design, Structural Equation Models, Data Analysis, Causal Models
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
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Carr, James E.; Austin, John – Teaching of Psychology, 1997
Provides a brief overview of single-subject research designs. This method exercises its power by examining changes in single subjects' responses over time across experimental conditions. Describes a classroom project in which students collect repeated measures of their own behavior and graph the data. (MJP)
Descriptors: Causal Models, Data Collection, Data Interpretation, Demonstrations (Educational)
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Johnson, David E. – Teaching of Psychology, 1996
Provides an exercise for introducing research methods to undergraduates. The students view a graph revealing that left-handed people are underrepresented in older age groups. Small group discussions attempt to explain this phenomenon. A follow-up class discussion focuses on the different approaches and methods available for interpreting the data.…
Descriptors: Causal Models, Critical Thinking, Data Interpretation, Factor Analysis