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Kaycee L. Bills; Bradley Mills – Journal of Research Initiatives, 2022
Research of issues related to disability is consistently evolving in several social science related fields such as social work, psychology, sociology, and education. Disability research often employs large public datasets for researchers to conduct secondary analysis. However, these datasets come with many limitations that can impact the overall…
Descriptors: Statistical Analysis, Research Problems, Disabilities, Research
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Johnson, Roger W. – Journal of Statistics and Data Science Education, 2022
For ease of instruction in the classroom, the one-way analysis of variance F statistic is rewritten in terms of pairwise differences in individual sample means instead of differences of individual sample means from the overall sample mean. Likewise, the Kruskal-Wallis statistic may be rewritten in terms of pairwise differences in individual…
Descriptors: Statistics Education, Statistical Analysis, Hypothesis Testing, Sampling
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Gwet, Kilem L. – Educational and Psychological Measurement, 2021
Cohen's kappa coefficient was originally proposed for two raters only, and it later extended to an arbitrarily large number of raters to become what is known as Fleiss' generalized kappa. Fleiss' generalized kappa and its large-sample variance are still widely used by researchers and were implemented in several software packages, including, among…
Descriptors: Sample Size, Statistical Analysis, Interrater Reliability, Computation
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Riley, Richard D.; Collins, Gary S.; Hattle, Miriam; Whittle, Rebecca; Ensor, Joie – Research Synthesis Methods, 2023
Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…
Descriptors: Computation, Meta Analysis, Participant Characteristics, Data
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Trafimow, David; Wang, Cong; Wang, Tonghui – Educational and Psychological Measurement, 2020
Previous researchers have proposed the a priori procedure, whereby the researcher specifies, prior to data collection, how closely she wishes the sample means to approach corresponding population means, and the degree of confidence of meeting the specification. However, an important limitation of previous research is that researchers sometimes are…
Descriptors: Sampling, Statistical Analysis, Equations (Mathematics), Differences
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Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2022
This article develops new closed-form variance expressions for power analyses for commonly used difference-in-differences (DID) and comparative interrupted time series (CITS) panel data estimators. The main contribution is to incorporate variation in treatment timing into the analysis. The power formulas also account for other key design features…
Descriptors: Comparative Analysis, Statistical Analysis, Sample Size, Measurement Techniques
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Shieh, Gwowen – Journal of Experimental Education, 2019
The analysis of covariance (ANCOVA) is a useful statistical procedure that incorporates covariate features into the adjustment of treatment effects. The consequences of omitted prognostic covariates on the statistical inferences of ANCOVA are well documented in the literature. However, the corresponding influence on sample-size calculations for…
Descriptors: Sample Size, Statistical Analysis, Computation, Accuracy
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Arnholt, Alan T. – Teaching Statistics: An International Journal for Teachers, 2019
Understanding and computing power and the relationship between sample size and power are facilitated via a Shiny app. The Shiny app allows students to solve various scenarios by entering different parameters or moving sliders.
Descriptors: Statistical Analysis, Sample Size, Computer Oriented Programs, Mathematics Instruction
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Li, Wei; Konstantopoulos, Spyros – Journal of Experimental Education, 2019
Education experiments frequently assign students to treatment or control conditions within schools. Longitudinal components added in these studies (e.g., students followed over time) allow researchers to assess treatment effects in average rates of change (e.g., linear or quadratic). We provide methods for a priori power analysis in three-level…
Descriptors: Research Design, Statistical Analysis, Sample Size, Effect Size
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White, Simon R.; Bonnett, Laura J. – Teaching Statistics: An International Journal for Teachers, 2019
The statistical concept of sampling is often given little direct attention, typically reduced to the mantra "take a random sample". This low resource and adaptable activity demonstrates sampling and explores issues that arise due to biased sampling.
Descriptors: Statistical Bias, Sampling, Statistical Analysis, Learning Activities
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Moerbeek, Mirjam; Safarkhani, Maryam – Journal of Educational and Behavioral Statistics, 2018
Data from cluster randomized trials do not always have a pure hierarchical structure. For instance, students are nested within schools that may be crossed by neighborhoods, and soldiers are nested within army units that may be crossed by mental health-care professionals. It is important that the random cross-classification is taken into account…
Descriptors: Randomized Controlled Trials, Classification, Research Methodology, Military Personnel
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What Works Clearinghouse, 2018
Underlying all What Works Clearinghouse (WWC) products are WWC Study Review Guides, which are intended for use by WWC certified reviewers to assess studies against the WWC evidence standards. As part of an ongoing effort to increase transparency, promote collaboration, and encourage widespread use of the WWC standards, the Institute of Education…
Descriptors: Guides, Research Design, Research Methodology, Program Evaluation
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Fugard, Andrew J. B.; Potts, Henry W. W. – International Journal of Social Research Methodology, 2015
Thematic analysis is frequently used to analyse qualitative data in psychology, healthcare, social research and beyond. An important stage in planning a study is determining how large a sample size may be required, however current guidelines for thematic analysis are varied, ranging from around 2 to over 400 and it is unclear how to choose a value…
Descriptors: Sample Size, Research Methodology, Qualitative Research, Computation
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Liu, Xiaofeng Steven; Loudermilk, Brandon; Simpson, Thomas – Measurement in Physical Education and Exercise Science, 2014
Sample size can be chosen to achieve a specified width in a confidence interval. The probability of obtaining a narrow width given that the confidence interval includes the population parameter is defined as the power of the confidence interval, a concept unfamiliar to many practitioners. This article shows how to utilize the Statistical Analysis…
Descriptors: Sample Size, Statistical Analysis, Confidence Testing, Intervals
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Seastrom, Marilyn – Institute of Education Sciences, 2017
The Every Student Succeeds Act (ESSA) of 2015 (Public Law 114-95) requires each state to create a plan for its statewide accountability system. In particular, ESSA calls for state plans that include strategies for reporting education outcomes by grade for all students and for economically disadvantaged students, students from major racial and…
Descriptors: Accountability, Best Practices, Information Security, Sample Size
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