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| Journal of Experimental… | 5 |
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Showing all 5 results
Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2011
Sample size determination is an important issue in planning research. In the context of one-way fixed-effect analysis of variance, the conventional sample size formula cannot be applied for the heterogeneous variance cases. This study discusses the sample size requirement for the Welch test in the one-way fixed-effect analysis of variance with…
Descriptors: Sample Size, Monte Carlo Methods, Statistical Analysis, Heterogeneous Grouping
Luh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2009
The sample size determination is an important issue for planning research. However, limitations in size have seldom been discussed in the literature. Thus, how to allocate participants into different treatment groups to achieve the desired power is a practical issue that still needs to be addressed when one group size is fixed. The authors focused…
Descriptors: Sample Size, Research Methodology, Evaluation Methods, Simulation
Luh, Wei-Ming; Olejnik, Stephen; Guo, Jiin-Huarng – Journal of Experimental Education, 2008
Formulas to determine the necessary sample sizes for parametric tests of group comparisons are available from several sources and appropriate when population distributions are normal. However, in the context of nonnormal population distributions, researchers recommend Yuen's trimmed mean test, but formulas to determine sample sizes have not been…
Descriptors: Sample Size, Computer Simulation, Statistical Analysis, Tests
Peer reviewedLuh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2005
To deal with nonnormal and heterogeneous data for the one-way fixed effect analysis of variance model, the authors adopted a trimmed means method in conjunction with Hall's invertible transformation into a heteroscedastic test statistic (Alexander-Govern test or Welch test). The results of simulation experiments showed that the proposed technique…
Descriptors: Robustness (Statistics), Computer Simulation, Educational Research, Error Patterns
Peer reviewedLuh, Wei-Ming; Guo, Jiin-Huarng – Journal of Experimental Education, 2002
Used Johnson's transformation (N. Johnson, 1978) with approximate test statistics to test the homogeneity of simple linear regression slopes in the presence of nonnormality and Type I, Type II or complete heteroscedasticity. Computer simulations show that the proposed techniques can control Type I error under various circumstances. (SLD)
Descriptors: Computer Simulation, Error of Measurement, Regression (Statistics)

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