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Yi, Zhihui; Schreiber, James B.; Paliliunas, Dana; Barron, Becky F.; Dixon, Mark R. – Journal of Behavioral Education, 2021
The recent commentary by Beaujean and Farmer (2020) on the original paper by Dixon et al. (2019) serves a cautionary tale of selective p-values, the law of small N sizes, and the type-II error. We believe these authors have crafted a somewhat questionable argument in which only 57% of the original Dixon et al. data were re-analyzed, based on a…
Descriptors: Research Problems, Data Analysis, Statistical Analysis, Probability
John R. Donoghue; Carol Eckerly – Applied Measurement in Education, 2024
Trend scoring constructed response items (i.e. rescoring Time A responses at Time B) gives rise to two-way data that follow a product multinomial distribution rather than the multinomial distribution that is usually assumed. Recent work has shown that the difference in sampling model can have profound negative effects on statistics usually used to…
Descriptors: Scoring, Error of Measurement, Reliability, Scoring Rubrics
Braun, Henry – International Journal of Educational Methodology, 2021
This article introduces the concept of the carrying capacity of data (CCD), defined as an integrated, evaluative judgment of the credibility of specific data-based inferences, informed by quantitative and qualitative analyses, leavened by experience. The sequential process of evaluating the CCD is represented schematically by a framework that can…
Descriptors: Data Use, Social Sciences, Data Analysis, Data Interpretation
John Jerrim; Alex Jones – School Effectiveness and School Improvement, 2024
School inspections are a common feature of many education systems. These may be informed by quantitative background data about schools. It is recognised that there are pros and cons of using such quantitative information as part of the inspection process, though these have rarely been succinctly set out. This paper seeks to fill this gap by…
Descriptors: Inspection, Foreign Countries, Statistical Analysis, Educational Quality
François, Karen; Monteiro, Carlos; Allo, Patrick – Statistics Education Research Journal, 2020
In the contemporary society a massive amount of data is generated continuously by various means, and they are called Big-Data sets. Big Data has potential and limits which need to be understood by statisticians and statistics consumers, therefore it is a challenge to develop Big-Data Literacy to support the needs of constructive, concerned, and…
Descriptors: Data Collection, Data Analysis, Statistical Analysis, Comprehension
Cheung, Mike W.-L. – Research Synthesis Methods, 2019
Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…
Descriptors: Structural Equation Models, Meta Analysis, Statistical Analysis, Data Analysis
Mau, Steffen – International Studies in Sociology of Education, 2020
The process of quantification is a powerful development shaping many domains of life today. In the area of education, for example, performance measurement, testing and ranking have become common tools of governance. Quantification is not a neutral way of describing society, but a process of valorisation. It has three sociologically relevant…
Descriptors: Statistical Analysis, Social Influences, Research Methodology, Evaluation Methods
Harwell, Michael – Mid-Western Educational Researcher, 2018
The importance of data analysis software in graduate programs in education and post-graduate educational research is self-evident. However the role of this software in facilitating supererogated statistical practice versus "cookbookery" is unclear. The need to rigorously document the role of data analysis software in students' graduate…
Descriptors: Graduate Study, Data Analysis, Computer Software, Educational Research
Vaisey, Stephen; Miles, Andrew – Sociological Methods & Research, 2017
The recent change in the general social survey (GSS) to a rotating panel design is a landmark development for social scientists. Sociological methodologists have argued that fixed-effects (FE) models are generally the best starting point for analyzing panel data because they allow analysts to control for unobserved time-constant heterogeneity. We…
Descriptors: Surveys, Data, Statistical Analysis, Models
Singer, Judith D. – Journal of Research on Educational Effectiveness, 2019
The arc of quantitative educational research should not be etched in stone but should adapt and change over time. In this article, I argue that it is time for a reshaping by offering my personal view of the past, present and future of our field. Educational research--and research in the social and life sciences--is at a crossroads. There are many…
Descriptors: Educational Research, Research Methodology, Longitudinal Studies, Evaluation
Zane, Len – Honors in Practice, 2020
Many of the numbers used to assess students are statistical in nature. The theoretical context underlying the production of a typical number or statistic used in student assessment is presented. The author urges readers to recognize objective data as subjective information and to carefully consider the numbers that often determine admission,…
Descriptors: Student Evaluation, Statistical Analysis, Honors Curriculum, Admission Criteria
McGill, Ryan J. – International Journal of School & Educational Psychology, 2017
For the appraisal of single-case intervention data, school psychologists have been encouraged to focus most, if not all, of their interpretive weight on the visual inspection of graphed data. However, existing software programs provide practitioners with limited features for systematic visual inspection. R (R Development Core Team, 2014) is a…
Descriptors: Intervention, Data, Graphs, Computer Software
Yamaguchi, Kazuo – Sociological Methods & Research, 2016
This article describes (1) the survey methodological and statistical characteristics of the nonrandomized method for surveying sensitive questions for both cross-sectional and panel survey data and (2) the way to use the incompletely observed variable obtained from this survey method in logistic regression and in loglinear and log-multiplicative…
Descriptors: Data Analysis, Surveys, Statistical Analysis, Regression (Statistics)
Leavy, Aisling; Hourigan, Mairead – Teaching Statistics: An International Journal for Teachers, 2016
We argue that the development of statistical literacy is greatly supported by engaging students in carrying out statistical investigations. We describe the use of driving questions and interesting contexts to motivate two statistical investigations. The PPDAC cycle is use as an organizing framework to support the process statistical investigation.
Descriptors: Statistics, Statistical Analysis, Literacy, Questioning Techniques
Rupp, André A.; van Rijn, Peter W. – Measurement: Interdisciplinary Research and Perspectives, 2018
We review the GIDNA and CDM packages in R for fitting cognitive diagnosis/diagnostic classification models. We first provide a summary of their core capabilities and then use both simulated and real data to compare their functionalities in practice. We found that the most relevant routines in the two packages appear to be more similar than…
Descriptors: Educational Assessment, Cognitive Measurement, Measurement, Computer Software