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Abbasnasab Sardareh, Sedigheh; Brown, Gavin T. L.; Denny, Paul – Teaching Statistics: An International Journal for Teachers, 2021
Research students in social science disciplines frequently struggle to master statistical analysis. A contributing factor may be the statistical software that is used, as the design of such software may not address the needs of non-statisticians or non-computer programming students. Hence, decisions about which statistical software tools are most…
Descriptors: Comparative Analysis, Computer Software, Statistics, Introductory Courses
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McCoach, D. Betsy; Rifenbark, Graham G.; Newton, Sarah D.; Li, Xiaoran; Kooken, Janice; Yomtov, Dani; Gambino, Anthony J.; Bellara, Aarti – Journal of Educational and Behavioral Statistics, 2018
This study compared five common multilevel software packages via Monte Carlo simulation: HLM 7, M"plus" 7.4, R (lme4 V1.1-12), Stata 14.1, and SAS 9.4 to determine how the programs differ in estimation accuracy and speed, as well as convergence, when modeling multiple randomly varying slopes of different magnitudes. Simulated data…
Descriptors: Hierarchical Linear Modeling, Computer Software, Comparative Analysis, Monte Carlo Methods
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Wood, Eileen; Grant, Amy K.; Gottardo, Alexandra; Savage, Robert; Evans, Mary Ann – Early Childhood Education Journal, 2017
The primary goal of this research was to extend our understanding of the strengths and weaknesses inherent in online and offline early literacy software programs designed for young learners. A taxonomy of reading skills was used to contrast online software with offline closed system (compact disc) based programs with respect to number of skills…
Descriptors: Young Children, Courseware, Emergent Literacy, Comparative Analysis