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Kyle Cox; Ben Kelcey; Hannah Luce – Journal of Experimental Education, 2024
Comprehensive evaluation of treatment effects is aided by considerations for moderated effects. In educational research, the combination of natural hierarchical structures and prevalence of group-administered or shared facilitator treatments often produces three-level partially nested data structures. Literature details planning strategies for a…
Descriptors: Randomized Controlled Trials, Monte Carlo Methods, Hierarchical Linear Modeling, Educational Research
Sarkar, Jyotirmoy; Rashid, Mamunur – Educational Research Quarterly, 2017
The standard deviation (SD) of a random sample is defined as the square-root of the sample variance, which is the "mean" squared deviation of the sample observations from the sample mean. Here, we interpret the sample SD as the square-root of twice the mean square of all pairwise half deviations between any two sample observations. This…
Descriptors: Sample Size, Sampling, Visualization, Geometric Concepts
Liu, Xiaofeng Steven – Journal of Experimental Education, 2010
The noncentrality parameter for a contrast test in a one-way analysis of variance is based on the dot product of 2 vectors whose geometric meaning in a Euclidian space offers mnemonic hints about its constituents. Additionally, the noncentrality parameters for a set of orthogonal contrasts sum up to the noncentrality parameter for the omnibus…
Descriptors: Statistical Analysis, Geometric Concepts, Mnemonics, Sample Size
Konstantopoulos, Spyros – Practical Assessment, Research & Evaluation, 2009
Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…
Descriptors: Social Science Research, Effect Size, Computation, Tables (Data)

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