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Showing 1 to 15 of 25 results Save | Export
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Stanley, T. D.; Doucouliagos, Hristos – Research Synthesis Methods, 2023
Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…
Descriptors: Correlation, Statistical Bias, Error Patterns, Error Correction
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Brunner, Martin; Keller, Lena; Stallasch, Sophie E.; Kretschmann, Julia; Hasl, Andrea; Preckel, Franzis; Lüdtke, Oliver; Hedges, Larry V. – Research Synthesis Methods, 2023
Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…
Descriptors: Meta Analysis, Surveys, Research Design, Educational Research
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Banjanovic, Erin S.; Osborne, Jason W. – Practical Assessment, Research & Evaluation, 2016
Confidence intervals for effect sizes (CIES) provide readers with an estimate of the strength of a reported statistic as well as the relative precision of the point estimate. These statistics offer more information and context than null hypothesis statistic testing. Although confidence intervals have been recommended by scholars for many years,…
Descriptors: Computation, Statistical Analysis, Effect Size, Sampling
Vaske, Jerry J. – Sagamore-Venture, 2019
Data collected from surveys can result in hundreds of variables and thousands of respondents. This implies that time and energy must be devoted to (a) carefully entering the data into a database, (b) running preliminary analyses to identify any problems (e.g., missing data, potential outliers), (c) checking the reliability and validity of the…
Descriptors: Surveys, Theories, Hypothesis Testing, Effect Size
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Koran, Jennifer – Measurement and Evaluation in Counseling and Development, 2016
Proactive preliminary minimum sample size determination can be useful for the early planning stages of a latent variable modeling study to set a realistic scope, long before the model and population are finalized. This study examined existing methods and proposed a new method for proactive preliminary minimum sample size determination.
Descriptors: Factor Analysis, Sample Size, Models, Sampling
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Lai, Mark H. C.; Kwok, Oi-Man – Journal of Educational and Behavioral Statistics, 2014
Multilevel modeling techniques are becoming more popular in handling data with multilevel structure in educational and behavioral research. Recently, researchers have paid more attention to cross-classified data structure that naturally arises in educational settings. However, unlike traditional single-level research, methodological studies about…
Descriptors: Hierarchical Linear Modeling, Differences, Effect Size, Computation
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Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas – Educational and Psychological Measurement, 2014
An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…
Descriptors: Sampling, Test Items, Effect Size, Scaling
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Haber, Mason G.; Mazzotti, Valerie L.; Mustian, April L.; Rowe, Dawn A.; Bartholomew, Audrey L.; Test, David W.; Fowler, Catherine H. – Review of Educational Research, 2016
Students with disabilities experience poorer post-school outcomes compared with their peers without disabilities. Existing experimental literature on "what works" for improving these outcomes is rare; however, a rapidly growing body of research investigates correlational relationships between experiences in school and post-school…
Descriptors: Meta Analysis, Predictor Variables, Success, Postsecondary Education
Hedges, Larry V.; Pustejovsky, James E.; Shadish, William R. – Online Submission, 2012
Single case designs are a set of research methods for evaluating treatment effects by assigning different treatments to the same individual and measuring outcomes over time and are used across fields such as behavior analysis, clinical psychology, special education, and medicine. Emerging standards for single case designs have focused attention on…
Descriptors: Research Design, Effect Size, Meta Analysis, Computation
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Skidmore, Susan Troncoso; Thompson, Bruce – Journal of Experimental Education, 2011
In the present Monte Carlo simulation study, the authors compared bias and precision of 7 sampling error corrections to the Pearson r[superscript 2] under 6 x 3 x 6 conditions (i.e., population ρ values of 0.0, 0.1, 0.3, 0.5, 0.7, and 0.9, respectively; population shapes normal, skewness = kurtosis = 1, and skewness = -1.5 with kurtosis =…
Descriptors: Monte Carlo Methods, Sampling, Error Correction, Statistical Bias
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Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2012
In this article, the authors talk about variation and how variation between measurements may be reduced if sampling is not random. They also talk about replication and its variants. A replicate is a repeated measurement from the same experimental unit. An experimental unit is the smallest part of an experiment or a study that can be subject to a…
Descriptors: Multivariate Analysis, Classroom Communication, Sampling, Physiology
Itang'ata, Mukaria J. J. – ProQuest LLC, 2013
Often researchers face situations where comparative studies between two or more programs are necessary to make causal inferences for informed policy decision-making. Experimental designs employing randomization provide the strongest evidence for causal inferences. However, many pragmatic and ethical challenges may preclude the use of randomized…
Descriptors: Comparative Analysis, Probability, Statistical Bias, Monte Carlo Methods
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Leventhal, Tama; Brooks-Gunn, Jeanne – Developmental Psychology, 2011
This study used data from the Project on Human Development in Chicago Neighborhoods, a multilevel, longitudinal study of children sampled from 80 diverse neighborhoods, to explore associations among changes in neighborhood poverty from 1990 to 2000 and changes in youth's internalizing problems and property and violent offenses over 6 years (N =…
Descriptors: Neighborhoods, Violence, Poverty, Effect Size
Wilson, Celia M. – ProQuest LLC, 2010
Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…
Descriptors: Monte Carlo Methods, Measurement, Multivariate Analysis, Error of Measurement
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Hedges, Larry V.; Rhoads, Christopher – National Center for Special Education Research, 2010
This paper provides a guide to calculating statistical power for the complex multilevel designs that are used in most field studies in education research. For multilevel evaluation studies in the field of education, it is important to account for the impact of clustering on the standard errors of estimates of treatment effects. Using ideas from…
Descriptors: Research Design, Field Studies, Computers, Effect Size
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