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Thomas Cook; Mansi Wadhwa; Jingwen Zheng – Society for Research on Educational Effectiveness, 2023
Context: A perennial problem in applied statistics is the inability to justify strong claims about cause-and-effect relationships without full knowledge of the mechanism determining selection into treatment. Few research designs other than the well-implemented random assignment study meet this requirement. Researchers have proposed partial…
Descriptors: Observation, Research Design, Causal Models, Computation
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Boers, Frank; Bryfonski, Lara; Faez, Farahnaz; McKay, Todd – Studies in Second Language Acquisition, 2021
Meta-analytic reviews collect available empirical studies on a specified domain and calculate the average effect of a factor. Educators as well as researchers exploring a new domain of inquiry may rely on the conclusions from meta-analytic reviews rather than reading multiple primary studies. This article calls for caution in this regard because…
Descriptors: Meta Analysis, Literature Reviews, Effect Size, Computation
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Ferron, John M.; Joo, Seanghwane – AERA Online Paper Repository, 2017
Single-case researchers frequently adopt a form of response-guided experimentation where decisions about the design of the study are made based on an ongoing visual analysis. For example, multiple-baseline researchers may delay the start of intervention until data document a stable baseline pattern so that baseline trends can be reliably extended,…
Descriptors: Research Design, Bias, Meta Analysis, Computation
Steenbergen-Hu, Saiying; Olszewski-Kubilius, Paula – Gifted Child Quarterly, 2016
This methodological brief introduces basic procedures and issues for conducting a high-quality meta-analysis in gifted education. Specifically, we discuss issues such as how to select a topic and formulate research problems, search for and identify qualified studies, code studies and extract data, choose and calculate effect sizes, analyze data,…
Descriptors: Meta Analysis, Academically Gifted, Research Methodology, Research Problems
Gelman, Andrew; Imbens, Guido – National Bureau of Economic Research, 2014
It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…
Descriptors: Regression (Statistics), Mathematical Models, Causal Models, Research Methodology
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Seifert, Tricia A.; Pascarella, Ernest T.; Erkel, Sherri I.; Goodman, Kathleen M. – New Directions for Institutional Research, 2010
In this chapter, the authors discuss the issue of research design in conducting inquiry on college impact and demonstrate the importance of longitudinal pretest-posttest designs in maximizing the internal validity of findings. They begin by discussing the strengths and weaknesses of different types of research design in the college impact…
Descriptors: Educational Research, Research Design, Pretests Posttests, Longitudinal Studies
Reardon, Sean F. – Society for Research on Educational Effectiveness, 2010
Instrumental variable estimators hold the promise of enabling researchers to estimate the effects of educational treatments that are not (or cannot be) randomly assigned but that may be affected by randomly assigned interventions. Examples of the use of instrumental variables in such cases are increasingly common in educational and social science…
Descriptors: Social Science Research, Least Squares Statistics, Computation, Correlation
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Schochet, Peter; Burghardt, John – Evaluation Review, 2007
This article discusses the use of propensity scoring in experimental program evaluations to estimate impacts for subgroups defined by program features and participants' program experiences. The authors discuss estimation issues and provide specification tests. They also discuss the use of an overlooked data collection design--obtaining predictions…
Descriptors: Program Effectiveness, Scoring, Experimental Programs, Control Groups
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Beretvas, S. Natasha – School Psychology Quarterly, 2005
This paper details the challenges encountered by authors summarizing evidence from a primary study to describe a treatment's effectiveness using an effect size (ES) estimate. Dilemmas that are encountered, including how to calculate and interpret the pertinent standardized mean difference ES for results from studies of various research designs,…
Descriptors: Effect Size, Research Methodology, Computation, Data Interpretation