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John Mart V. DelosReyes; Miguel A. Padilla – Journal of Experimental Education, 2024
Estimating confidence intervals (CIs) for the correlation has been a challenge because the correlation sampling distribution changes depending on the correlation magnitude. The Fisher z-transformation was one of the first attempts at estimating correlation CIs but has historically shown to not have acceptable coverage probability if data were…
Descriptors: Research Problems, Correlation, Intervals, Computation
Terry A. Beehr; Minseo Kim; Ian W. Armstrong – International Journal of Social Research Methodology, 2024
Previous research extensively studied reasons for and ways to avoid low response rates, but it largely ignored the primary research issue of the degree to which response rates matter, which we address. Methodological survey research on response rates has been concerned with how to increase responsiveness and with the effects of response rates on…
Descriptors: Surveys, Response Rates (Questionnaires), Effect Size, Research Methodology
Hasan Tutar; Mehmet Sahin; Teymur Sarkhanov – Qualitative Research Journal, 2024
Purpose: The lack of a definite standard for determining the sample size in qualitative research leaves the research process to the initiative of the researcher, and this situation overshadows the scientificity of the research. The primary purpose of this research is to propose a model by questioning the problem of determining the sample size,…
Descriptors: Research Problems, Sample Size, Qualitative Research, Models
Kaycee L. Bills; Bradley Mills – Journal of Research Initiatives, 2022
Research of issues related to disability is consistently evolving in several social science related fields such as social work, psychology, sociology, and education. Disability research often employs large public datasets for researchers to conduct secondary analysis. However, these datasets come with many limitations that can impact the overall…
Descriptors: Statistical Analysis, Research Problems, Disabilities, Research
Ting Dai; Yang Du; Jennifer Cromley; Tia Fechter; Frank Nelson – Journal of Experimental Education, 2024
Simple matrix sampling planned missing (SMS PD) design, introduce missing data patterns that lead to covariances between variables that are not jointly observed, and create difficulties for analyses other than mean and variance estimations. Based on prior research, we adopted a new multigroup confirmatory factor analysis (CFA) approach to handle…
Descriptors: Research Problems, Research Design, Data, Matrices
Wei Li; Yanli Xie; Dung Pham; Nianbo Dong; Jessaca Spybrook; Benjamin Kelcey – Asia Pacific Education Review, 2024
Cluster randomized trials (CRTs) are commonly used to evaluate the causal effects of educational interventions, where the entire clusters (e.g., schools) are randomly assigned to treatment or control conditions. This study introduces statistical methods for designing and analyzing two-level (e.g., students nested within schools) and three-level…
Descriptors: Research Design, Multivariate Analysis, Randomized Controlled Trials, Hierarchical Linear Modeling
Duane Knudson – Measurement in Physical Education and Exercise Science, 2025
Small sample sizes contribute to several problems in research and knowledge advancement. This conceptual replication study confirmed and extended the inflation of type II errors and confidence intervals in correlation analyses of small sample sizes common in kinesiology/exercise science. Current population data (N = 18, 230, & 464) on four…
Descriptors: Kinesiology, Exercise, Biomechanics, Movement Education
Mthuli, Syanda Alpheous; Ruffin, Fayth; Singh, Nikita – International Journal of Social Research Methodology, 2022
Qualitative research sample size determination has always been a contentious and confusing issue. Studies are often vague when explaining the processes and justifications that have been used to determine sample size and strategy. Some provide no mention of sampling at all, whilst others rely too heavily on the concept of saturation for determining…
Descriptors: Qualitative Research, Sample Size, Sampling, Research Problems
Yan Xia; Selim Havan – Educational and Psychological Measurement, 2024
Although parallel analysis has been found to be an accurate method for determining the number of factors in many conditions with complete data, its application under missing data is limited. The existing literature recommends that, after using an appropriate multiple imputation method, researchers either apply parallel analysis to every imputed…
Descriptors: Data Interpretation, Factor Analysis, Statistical Inference, Research Problems
Semih Asiret; Seçil Ömür Sünbül – International Journal of Psychology and Educational Studies, 2023
In this study, it was aimed to examine the effect of missing data in different patterns and sizes on test equating methods under the NEAT design for different factors. For this purpose, as part of this study, factors such as sample size, average difficulty level difference between the test forms, difference between the ability distribution,…
Descriptors: Research Problems, Data, Test Items, Equated Scores
Goretzko, David – Educational and Psychological Measurement, 2022
Determining the number of factors in exploratory factor analysis is arguably the most crucial decision a researcher faces when conducting the analysis. While several simulation studies exist that compare various so-called factor retention criteria under different data conditions, little is known about the impact of missing data on this process.…
Descriptors: Factor Analysis, Research Problems, Data, Prediction
Bulus, Metin; Koyuncu, Ilhan – Participatory Educational Research, 2021
This study systematically reviews randomly selected 155 experimental studies in education field originated in the Republic of Turkey between 2010 and 2020. Indiscriminate choice of sample size in recent publications prompted us to evaluate their statistical power and precision. First, above and beyond our review, we could not identify any…
Descriptors: Foreign Countries, Educational Research, Statistical Analysis, Sample Size
Myunghwan Hwang; Soyeon Kim; Hyejin Kim; Joohee Han; Hee-Kyung Lee – English Teaching, 2024
This paper evaluates the use of Factor Analysis (FA) in English education research in Korea and suggests improvements in methodology. A detailed coding protocol was used to review 179 FA cases from 12 major English education journals (2014-2023). The review identified several key issues, including small sample sizes and lenient criteria for sample…
Descriptors: Factor Analysis, English (Second Language), Second Language Learning, Second Language Instruction
Wendy Chan; Jimin Oh; Katherine Wilson – Society for Research on Educational Effectiveness, 2022
Background: Over the past decade, research on the development and assessment of tools to improve the generalizability of experimental findings has grown extensively (Tipton & Olsen, 2018). However, many experimental studies in education are based on small samples, which may include 30-70 schools while inference populations to which…
Descriptors: Educational Research, Research Problems, Sample Size, Research Methodology
Peer reviewedDongho Shin – Grantee Submission, 2024
We consider Bayesian estimation of a hierarchical linear model (HLM) from small sample sizes. The continuous response Y and covariates C are partially observed and assumed missing at random. With C having linear effects, the HLM may be efficiently estimated by available methods. When C includes cluster-level covariates having interactive or other…
Descriptors: Bayesian Statistics, Computation, Hierarchical Linear Modeling, Data Analysis

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