NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 9 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Noma, Hisashi; Hamura, Yasuyuki; Gosho, Masahiko; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…
Descriptors: Network Analysis, Meta Analysis, Regression (Statistics), Error of Measurement
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Dogan, C. Deha – Eurasian Journal of Educational Research, 2017
Background: Most of the studies in academic journals use p values to represent statistical significance. However, this is not a good indicator of practical significance. Although confidence intervals provide information about the precision of point estimation, they are, unfortunately, rarely used. The infrequent use of confidence intervals might…
Descriptors: Sampling, Statistical Inference, Periodicals, Intervals
Peer reviewed Peer reviewed
Direct linkDirect link
Zakszeski, Brittany N.; Hojnoski, Robin L.; Wood, Brenna K. – Topics in Early Childhood Special Education, 2017
Classroom engagement is important to young children's academic and social development. Accurate methods of capturing this behavior are needed to inform and evaluate intervention efforts. This study compared the accuracy of interval durations (i.e., 5 s, 10 s, 15 s, 20 s, 30 s, and 60 s) of momentary time sampling (MTS) in approximating the…
Descriptors: Intervals, Time, Sampling, Learner Engagement
Peer reviewed Peer reviewed
Direct linkDirect link
Ledford, Jennifer R.; Ayres, Kevin M.; Lane, Justin D.; Lam, Man Fung – Journal of Special Education, 2015
Momentary time sampling (MTS), whole interval recording (WIR), and partial interval recording (PIR) are commonly used in applied research. We discuss potential difficulties with analyzing data when these systems are used and present results from a pilot simulation study designed to determine the extent to which these issues are likely to be…
Descriptors: Intervals, Research Methodology, Sampling, Time
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Arzumanyan, George; Halcoussis, Dennis; Phillips, G. Michael – American Journal of Business Education, 2015
This paper presents the Agresti & Coull "Adjusted Wald" method for computing confidence intervals and margins of error for common proportion estimates. The presented method is easily implementable by business students and practitioners and provides more accurate estimates of proportions particularly in extreme samples and small…
Descriptors: Business Administration Education, Error of Measurement, Error Patterns, Intervals
Peer reviewed Peer reviewed
Direct linkDirect link
Reardon, Sean F.; Ho, Andrew D. – Journal of Educational and Behavioral Statistics, 2015
In an earlier paper, we presented methods for estimating achievement gaps when test scores are coarsened into a small number of ordered categories, preventing fine-grained distinctions between individual scores. We demonstrated that gaps can nonetheless be estimated with minimal bias across a broad range of simulated and real coarsened data…
Descriptors: Achievement Gap, Performance Factors, Educational Practices, Scores
Reardon, Sean F.; Ho, Andrew D. – Grantee Submission, 2015
Ho and Reardon (2012) present methods for estimating achievement gaps when test scores are coarsened into a small number of ordered categories, preventing fine-grained distinctions between individual scores. They demonstrate that gaps can nonetheless be estimated with minimal bias across a broad range of simulated and real coarsened data…
Descriptors: Achievement Gap, Performance Factors, Educational Practices, Scores
Peer reviewed Peer reviewed
Direct linkDirect link
Kim, Se-Kang – International Journal of Testing, 2010
The aim of the current study is to validate the invariance of major profile patterns derived from multidimensional scaling (MDS) by bootstrapping. Profile Analysis via Multidimensional Scaling (PAMS) was employed to obtain profiles and bootstrapping was used to construct the sampling distributions of the profile coordinates and the empirical…
Descriptors: Intervals, Multidimensional Scaling, Profiles, Evaluation
Peer reviewed Peer reviewed
Direct linkDirect link
Bonnett, Douglas G. – Psychological Methods, 2008
Most psychology journals now require authors to report a sample value of effect size along with hypothesis testing results. The sample effect size value can be misleading because it contains sampling error. Authors often incorrectly interpret the sample effect size as if it were the population effect size. A simple solution to this problem is to…
Descriptors: Intervals, Hypothesis Testing, Effect Size, Sampling