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Babcock, Ben; Marks, Peter E. L.; van den Berg, Yvonne H. M.; Cillessen, Antonius H. N. – International Journal of Behavioral Development, 2022
A wide variety of methodological choices and situations can affect the quality of peer nomination measurements but have not received adequate study. This article begins by focusing on systematic nominator missingness as an example of one such situation. We reanalyzed findings from a recent study by Bukowski, Dirks, Commisso, Velàsquez, and Lopez…
Descriptors: Research Methodology, Peer Relationship, Statistical Analysis, Error Patterns
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Xie, Zilong; Reetzke, Rachel; Chandrasekaran, Bharath – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Speech-evoked neurophysiological responses are often collected to answer clinically and theoretically driven questions concerning speech and language processing. Here, we highlight the practical application of machine learning (ML)-based approaches to analyzing speech-evoked neurophysiological responses. Method: Two categories of ML-based…
Descriptors: Speech Language Pathology, Intervention, Communication Problems, Speech Impairments
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Maeda, Yukiko; Harwell, Michael R. – Mid-Western Educational Researcher, 2016
The "Q" test is regularly used in meta-analysis to examine variation in effect sizes. However, the assumptions of "Q" are unlikely to be satisfied in practice prompting methodological researchers to conduct computer simulation studies examining its statistical properties. Narrative summaries of this literature are available but…
Descriptors: Meta Analysis, Q Methodology, Effect Size, Research Methodology
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Bishara, Anthony J.; Hittner, James B. – Educational and Psychological Measurement, 2015
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Descriptors: Research Methodology, Monte Carlo Methods, Correlation, Simulation
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Bernard, Robert M.; Borokhovski, Eugene; Schmid, Richard F.; Tamim, Rana M. – Journal of Computing in Higher Education, 2014
This article contains a second-order meta-analysis and an exploration of bias in the technology integration literature in higher education. Thirteen meta-analyses, dated from 2000 to 2014 were selected to be included based on the questions asked and the presence of adequate statistical information to conduct a quantitative synthesis. The weighted…
Descriptors: Meta Analysis, Bias, Technology Integration, Higher Education
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Moses, Tim; Zhang, Wenmin – Journal of Educational and Behavioral Statistics, 2011
The purpose of this article was to extend the use of standard errors for equated score differences (SEEDs) to traditional equating functions. The SEEDs are described in terms of their original proposal for kernel equating functions and extended so that SEEDs for traditional linear and traditional equipercentile equating functions can be computed.…
Descriptors: Equated Scores, Error Patterns, Evaluation Research, Statistical Analysis
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Haardorfer, Regine; Gagne, Phill – Focus on Autism and Other Developmental Disabilities, 2010
Some researchers have argued for the use of or have attempted to make use of randomization tests in single-subject research. To address this tide of interest, the authors of this article describe randomization tests, discuss the theoretical rationale for applying them to single-subject research, and provide an overview of the methodological…
Descriptors: Research Design, Researchers, Evaluation Methods, Research Methodology
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Mrazik, Martin; Janzen, Troy M.; Dombrowski, Stefan C.; Barford, Sean W.; Krawchuk, Lindsey L. – Canadian Journal of School Psychology, 2012
A total of 19 graduate students enrolled in a graduate course conducted 6 consecutive administrations of the Wechsler Intelligence Scale for Children, 4th edition (WISC-IV, Canadian version). Test protocols were examined to obtain data describing the frequency of examiner errors, including administration and scoring errors. Results identified 511…
Descriptors: Intelligence Tests, Intelligence, Statistical Analysis, Scoring
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Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2009
The sample size determination is an important issue for planning research. However, limitations in size have seldom been discussed in the literature. Thus, how to allocate participants into different treatment groups to achieve the desired power is a practical issue that still needs to be addressed when one group size is fixed. The authors focused…
Descriptors: Sample Size, Research Methodology, Evaluation Methods, Simulation
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Battista, Michael; Smith, Margaret S.; Boerst, Timothy; Sutton, John; Confrey, Jere; White, Dorothy; Knuth, Eric; Quander, Judith – Journal for Research in Mathematics Education, 2009
Recent federal education policies and reports have generated considerable debate about the meaning, methods, and goals of "scientific research" in mathematics education. Concentrating on the critical problem of determining which educational programs and practices reliably improve students' mathematics achievement, these policies and reports focus…
Descriptors: Scientific Research, Mathematics Education, Research Methodology, Mathematics Achievement
Schochet, Peter Z. – Mathematica Policy Research, Inc., 2008
Studies that examine the impacts of education interventions on key student, teacher, and school outcomes typically collect data on large samples and on many outcomes. In analyzing these data, researchers typically conduct multiple hypothesis tests to address key impact evaluation questions. Tests are conducted to assess intervention effects for…
Descriptors: Hypothesis Testing, Guidelines, Outcomes of Education, Evaluation Methods
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Nordstokke, David W.; Zumbo, Bruno D. – Journal of Educational Research & Policy Studies, 2007
The central messages of this paper are that (a) unequal variances may be more prevalent than typically imagined in educational and policy research, and (b) when considering tests of equal variances one needs to be cautious about what is being referred to as "Levene's test" because Levene's test is actually a family of techniques. Depending on…
Descriptors: Statistical Analysis, Educational Policy, Educational Research, Computer Software
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Bookstein, Abrham – Library Quarterly, 1974
Discusses three types of faults which commonly occur in statistical sampling. (JG)
Descriptors: Error Patterns, Library Research, Research Methodology, Sampling
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Bird, Kevin D. – Multivariate Behavioral Research, 1975
Generalizations of the Scheffe, Tukey, and Bonferroni-t techniques are presented, each of which controls the experimentwise error rate for a particular type of partially or fully planned analysis. All three procedures provide more power than multivariate analysis of variance (MANOVA) tests. (Author/BJG)
Descriptors: Analysis of Variance, Error Patterns, Hypothesis Testing, Research Methodology
Ottenbacher, Kenneth J. – American Journal on Mental Retardation, 1991
An analysis of 41 recently published articles in the "American Journal on Mental Retardation" and the "Journal of Mental Deficiency Research" found a higher than expected probability of Type I research errors, suggesting that approximately 20 percent of the statistically significant results may be erroneous. (DB)
Descriptors: Error Patterns, Mental Retardation, Meta Analysis, Research Methodology
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