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Showing 1 to 15 of 36 results Save | Export
Christopher Martin Amissah – ProQuest LLC, 2024
Measurement of latent constructs is one of the most challenging tasks in psychological research. Unlike physical variables, latent constructs are not directly observable but are inferred through individuals' responses to a set of items often referred to as measurement instruments, tests, surveys, or assessments. For decades, exploratory factor…
Descriptors: Models, Psychological Studies, Replication (Evaluation), Factor Analysis
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Su, Shiyang; Wang, Chun; Weiss, David J. – Educational and Psychological Measurement, 2021
S-X[superscript 2] is a popular item fit index that is available in commercial software packages such as "flex"MIRT. However, no research has systematically examined the performance of S-X[superscript 2] for detecting item misfit within the context of the multidimensional graded response model (MGRM). The primary goal of this study was…
Descriptors: Statistics, Goodness of Fit, Test Items, Models
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Pérez-Ferreirós, Alexandra; Kalén, Anton; Gómez, Miguel-Ángel; Rey, Ezequiel – Research Quarterly for Exercise and Sport, 2019
In basketball, game-related statistics are the most common measure of performance. However, the literature assessing their reliability is scarce. Purpose: Analyze the number of games required to obtain a good relative and absolute reliability of teams' game-related statistics. Method: A total of 884 games from the 2015-2016 to 2017-2018 seasons of…
Descriptors: Team Sports, Statistics, Reliability, Foreign Countries
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Trafimow, David; MacDonald, Justin A. – Educational and Psychological Measurement, 2017
Typically, in education and psychology research, the investigator collects data and subsequently performs descriptive and inferential statistics. For example, a researcher might compute group means and use the null hypothesis significance testing procedure to draw conclusions about the populations from which the groups were drawn. We propose an…
Descriptors: Statistical Inference, Statistics, Data Collection, Equations (Mathematics)
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Phillips, Gary W.; Jiang, Tao – Practical Assessment, Research & Evaluation, 2016
Power analysis is a fundamental prerequisite for conducting scientific research. Without power analysis the researcher has no way of knowing whether the sample size is large enough to detect the effect he or she is looking for. This paper demonstrates how psychometric factors such as measurement error and equating error affect the power of…
Descriptors: Error of Measurement, Statistical Analysis, Equated Scores, Sample Size
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Inzunsa Cazares, Santiago – North American Chapter of the International Group for the Psychology of Mathematics Education, 2016
This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…
Descriptors: Qualitative Research, College Students, Inferences, Logical Thinking
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Bonett, Douglas G.; Price, Robert M. – Journal of Educational and Behavioral Statistics, 2012
Adjusted Wald intervals for binomial proportions in one-sample and two-sample designs have been shown to perform about as well as the best available methods. The adjusted Wald intervals are easy to compute and have been incorporated into introductory statistics courses. An adjusted Wald interval for paired binomial proportions is proposed here and…
Descriptors: Computation, Statistical Analysis, Data, Sample Size
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Hightower, Christy; Scott, Kerry – Issues in Science and Technology Librarianship, 2012
Many librarians use data from surveys to make decisions about how to spend money or allocate staff, often making use of popular online tools like Survey Monkey. In this era of reduced budgets, low staffing, stiff competition for new resources, and increasingly complex choices, it is especially important that librarians know how to get strong,…
Descriptors: Librarians, Surveys, Statistical Inference, Statistics
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Liu, Xiaofeng Steven – International Journal of Mathematical Education in Science and Technology, 2012
The statistical power of a significance test is closely related to the length of the confidence interval (i.e. estimate precision). In the case of a "Z" test, the length of the confidence interval can be expressed as a function of the statistical power. (Contains 1 figure and 1 table.)
Descriptors: Statistical Analysis, Intervals, Statistical Significance, Statistics
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Olinsky, Alan; Schumacher, Phyllis; Quinn, John – International Journal for Mathematics Teaching and Learning, 2012
In this paper, we discuss the importance of teaching power considerations in statistical hypothesis testing. Statistical power analysis determines the ability of a study to detect a meaningful effect size, where the effect size is the difference between the hypothesized value of the population parameter under the null hypothesis and the true value…
Descriptors: Testing, Sample Size, Hypothesis Testing, Statistics
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Stack, Sue; Watson, Jane – Australian Mathematics Teacher, 2013
There is considerable research on the difficulties students have in conceptualising individual concepts of probability and statistics (see for example, Bryant & Nunes, 2012; Jones, 2005). The unit of work developed for the action research project described in this article is specifically designed to address some of these in order to help…
Descriptors: Secondary School Mathematics, Grade 10, Mathematical Concepts, Probability
Valliant, Richard; Dever, Jill A.; Kreuter, Frauke – Springer, 2013
Survey sampling is fundamentally an applied field. The goal in this book is to put an array of tools at the fingertips of practitioners by explaining approaches long used by survey statisticians, illustrating how existing software can be used to solve survey problems, and developing some specialized software where needed. This book serves at least…
Descriptors: Sampling, Surveys, Computer Software, College Students
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Norman, Geoff – Advances in Health Sciences Education, 2010
Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The…
Descriptors: Likert Scales, Statistical Analysis, Data, Sample Size
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Curran-Everett, Douglas – Advances in Physiology Education, 2010
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This fifth installment of "Explorations in Statistics" revisits power, a concept fundamental to the test of a null hypothesis. Power is the probability that we reject the null hypothesis when it is false. Four…
Descriptors: Statistics, Statistical Analysis, Probability, Hypothesis Testing
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Strayer, Jeremy F. – Mathematics Teacher, 2013
Statistical studies are referenced in the news every day, so frequently that people are sometimes skeptical of reported results. Often, no matter how large a sample size researchers use in their studies, people believe that the sample size is too small to make broad generalizations. The tasks presented in this article use simulations of repeated…
Descriptors: Sampling, Sample Size, Research Methodology, Statistical Analysis
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