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Showing 1 to 15 of 21 results Save | Export
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Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
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AlWahaibi, Ibrahim Said Humaid; AlHadabi, Dawood Abdul Malik Yahya AlHadabi; AlKharusi, Hussain Ali Talib – Cypriot Journal of Educational Sciences, 2020
The present study aimed at clarifying the various shortcomings of the Cohen's criteria for the interpretation of the values of the practical significance indicators. The hypothetical data were used for two experimental and control groups and calculating the paired-samples t-test. To clarify the inadequacy of Cohen's criteria in interpreting…
Descriptors: Statistical Analysis, Statistical Significance, Equations (Mathematics), Computation
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Lenz, A. Stephen – Measurement and Evaluation in Counseling and Development, 2020
A guide for professional counselors and counseling researchers for calculating and interpreting Percent Improvement as an indicator of clinical significance is provided. Strategies for reporting findings are described and illustrated. Guidelines for contextualizing discussions of clinical significance within the boundaries of psychometric evidence…
Descriptors: Counseling, Research, Computation, Improvement
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Pavelko, Stacey L.; Owens, Robert E., Jr. – Perspectives of the ASHA Special Interest Groups, 2023
Purpose: The purposes of this tutorial are (a) to describe a method of language sample analysis (LSA) referred to as SUGAR (Sampling Utterances and Grammatical Analysis Revised) and (b) to offer step-by-step instructions detailing how to collect, transcribe, analyze, and interpret the results of a SUGAR language sample. Method: The tutorial begins…
Descriptors: Sampling, Language Tests, Data Collection, Data Analysis
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Bi, Henry H. – Assessment & Evaluation in Higher Education, 2018
There are no absolute standards regarding what teaching evaluation ratings are satisfactory. It is also problematic to compare teaching evaluation ratings with the average or with a cutoff number to determine whether they are adequate. In this paper, we use average and standard deviation charts (X[overbar]-S charts), which are based on the theory…
Descriptors: Robustness (Statistics), Data Interpretation, Rating Scales, Computation
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Boedeker, Peter – Practical Assessment, Research & Evaluation, 2017
Hierarchical linear modeling (HLM) is a useful tool when analyzing data collected from groups. There are many decisions to be made when constructing and estimating a model in HLM including which estimation technique to use. Three of the estimation techniques available when analyzing data with HLM are maximum likelihood, restricted maximum…
Descriptors: Hierarchical Linear Modeling, Maximum Likelihood Statistics, Bayesian Statistics, Computation
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Blackwell, Matthew; Honaker, James; King, Gary – Sociological Methods & Research, 2017
Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…
Descriptors: Error of Measurement, Monte Carlo Methods, Data Collection, Simulation
Gobert, Janice D.; Moussavi, Raha; Li, Haiying; Sao Pedro, Michael; Dickler, Rachel – Grantee Submission, 2018
This chapter addresses students' data interpretation, a key NGSS inquiry practice, with which students have several different types of difficulties. In this work, we unpack the difficulties associated with data interpretation from those associated with warranting claims. We do this within the context of Inq-ITS (Inquiry Intelligent Tutoring…
Descriptors: Scaffolding (Teaching Technique), Data Interpretation, Intelligent Tutoring Systems, Science Instruction
Alison K. Cohen – Sage Research Methods Cases, 2014
This case study presents an example of using a generalized linear model with a log-linear link to calculate an adjusted risk ratio to be able to assess the association between educational attainment and obesity in a cohort study of American adults. Both risk ratios and odds ratios can be calculated based on cohort study data, and risk ratios are…
Descriptors: Models, Computation, Risk, Educational Attainment
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Andrade, Luisa; Fernández, Felipe – Universal Journal of Educational Research, 2016
As literature has reported, it is usual that university students in statistics courses, and even statistics teachers, interpret the confidence level associated with a confidence interval as the probability that the parameter value will be between the lower and upper interval limits. To confront this misconception, class activities have been…
Descriptors: Conflict, College Students, Statistics, Probability
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Schild, Anne H. E.; Voracek, Martin – Research Synthesis Methods, 2015
Research has shown that forest plots are a gold standard in the visualization of meta-analytic results. However, research on the general interpretation of forest plots and the role of researchers' meta-analysis experience and field of study is still unavailable. Additionally, the traditional display of effect sizes, confidence intervals, and…
Descriptors: Graphs, Visualization, Meta Analysis, Data Interpretation
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Wind, Stefanie A.; Engelhard, George, Jr.; Wesolowski, Brian – Educational Assessment, 2016
When good model-data fit is observed, the Many-Facet Rasch (MFR) model acts as a linking and equating model that can be used to estimate student achievement, item difficulties, and rater severity on the same linear continuum. Given sufficient connectivity among the facets, the MFR model provides estimates of student achievement that are equated to…
Descriptors: Evaluators, Interrater Reliability, Academic Achievement, Music Education
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Scheerens, Jaap; Luyten, Hans; van den Berg, Stéphanie M.; Glas, Cees A. W. – Educational Research and Evaluation, 2015
As expectations of the economic impact of educational attainment are soaring (Hanushek & Woessmann, 2009) and conjectures about successful national educational reforms (Mourshed, Chijioke, & Barber, 2010) are welcomed by educational policy-makers in many countries, a careful assessment of the empirical evidence for these kinds of claims is…
Descriptors: Foreign Countries, Educational Attainment, Educational Change, Comparative Education
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Hoekstra, Rink; Johnson, Addie; Kiers, Henk A. L. – Educational and Psychological Measurement, 2012
The use of confidence intervals (CIs) as an addition or as an alternative to null hypothesis significance testing (NHST) has been promoted as a means to make researchers more aware of the uncertainty that is inherent in statistical inference. Little is known, however, about whether presenting results via CIs affects how readers judge the…
Descriptors: Computation, Statistical Analysis, Hypothesis Testing, Statistical Significance
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Suleman, Qaiser; Hussain, Ishtiaq – Journal of Education and Practice, 2016
The purpose of the research paper was to investigate the effect of eclectic learning approach on the academic achievement and retention of students in English at elementary level. A sample of forty students of 8th grade randomly selected from Government Boys High School Khurram District Karak was used. It was an experimental study and that's why…
Descriptors: Elementary School Students, Academic Achievement, School Holding Power, Pretests Posttests
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