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Michael Borenstein – Research Synthesis Methods, 2024
In any meta-analysis, it is critically important to report the dispersion in effects as well as the mean effect. If an intervention has a moderate clinical impact "on average" we also need to know if the impact is moderate for all relevant populations, or if it varies from trivial in some to major in others. Or indeed, if the…
Descriptors: Meta Analysis, Error Patterns, Statistical Analysis, Intervention
Cairns, Maxwell; Prendergast, Luke A. – Research Synthesis Methods, 2022
As a measure of heterogeneity in meta-analysis, the coefficient of variation (CV) has been recently considered, providing researchers with a complement to the very popular I[superscript 2] measure. While I[superscript 2] measures the proportion of total variance that is due to variance of the random effects, the CV is the ratio of the standard…
Descriptors: Meta Analysis, Statistical Analysis, Intervals, Computation
Dan Soriano; Eli Ben-Michael; Peter Bickel; Avi Feller; Samuel D. Pimentel – Grantee Submission, 2023
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…
Descriptors: Statistical Analysis, Computation, Mathematical Formulas, Monte Carlo Methods
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
Rosenthal, Jeffrey S. – Teaching Statistics: An International Journal for Teachers, 2018
This article advocates that introductory statistics be taught by basing all calculations on a single simple margin-of-error formula and deriving all of the standard introductory statistical concepts (confidence intervals, significance tests, comparisons of means and proportions, etc) from that one formula. It is argued that this approach will…
Descriptors: Statistics, Introductory Courses, Computation, Statistical Analysis
Walkup, John R.; Key, Roger A.; Talbot, Patrick R. M. – Physics Education, 2019
A lab activity for teaching physics students the fundamentals of statistical analysis during the first few weeks of instruction is described. This activity involves students timing a pulse of light generated by an Arduino device of fixed duration with individual timers (e.g. stopwatch, iPhone timer). To select the most precise timing methods and…
Descriptors: Physics, Introductory Courses, Science Instruction, Laboratory Experiments
Jackson, Dan; Bowden, Jack; Baker, Rose – Research Synthesis Methods, 2015
Moment-based estimators of the between-study variance are very popular when performing random effects meta-analyses. This type of estimation has many advantages including computational and conceptual simplicity. Furthermore, by using these estimators in large samples, valid meta-analyses can be performed without the assumption that the treatment…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Computation, Evaluation Methods
Quinn, Anne – Mathematics Teacher, 2016
While looking for an inexpensive technology package to help students in statistics classes, the author found StatKey, a free Web-based app. Not only is StatKey useful for students' year-end projects, but it is also valuable for helping students learn fundamental content such as the central limit theorem. Using StatKey, students can engage in…
Descriptors: Statistics, Computer Oriented Programs, Technology Uses in Education, Teaching Methods
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
Larson-Hall, Jenifer; Plonsky, Luke – Language Learning, 2015
This paper presents a set of guidelines for reporting on five types of quantitative data issues: (1) Descriptive statistics, (2) Effect sizes and confidence intervals, (3) Instrument reliability, (4) Visual displays of data, and (5) Raw data. Our recommendations are derived mainly from various professional sources related to L2 research but…
Descriptors: Guidelines, Statistical Analysis, Language Research, Second Language Learning
Fraile, Rubén; Bosch-Morell, Francisco – Higher Education: The International Journal of Higher Education Research, 2015
Lecturer promotion and tenure decisions are critical both for university management and for the affected lecturers. Therefore, they should be made cautiously and based on reliable information. Student evaluations of teaching quality are among the most used and analysed sources of such information. However, to date little attention has been paid in…
Descriptors: History Instruction, Teacher Promotion, Tenure, College Faculty
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
Zientek, Linda Reichwein; Ozel, Z. Ebrar Yetkiner; Ozel, Serkan; Allen, Jeff – Career and Technical Education Research, 2012
Confidence intervals (CIs) and effect sizes are essential to encourage meta-analytic thinking and to accumulate research findings. CIs provide a range of plausible values for population parameters with a degree of confidence that the parameter is in that particular interval. CIs also give information about how precise the estimates are. Comparison…
Descriptors: Vocational Education, Effect Size, Intervals, Self Esteem
Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2011
Current standards of data presentation and analysis in biological journals often fall short of ideal. This is the first of a planned series of short articles, to be published in a number of journals, aiming to highlight the principles of clear data presentation and appropriate statistical analysis. This article considers the methods used to show…
Descriptors: Intervals, Statistical Analysis, Journal Articles, Periodicals
Shiyko, Mariya P.; Ram, Nilam – Multivariate Behavioral Research, 2011
Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread,…
Descriptors: Generalizability Theory, Intervals, Smoking, Self Efficacy