An Evaluation of Analysis Methods to Eliminate the Effect of Density Variation in Property Comparisons of Wood Composites
Keywords:
Wood composites, density variation, data analysis, indicator variable methodAbstract
The objective of this research was to evaluate commonly used data analysis methods in property comparisons of wood composites to eliminate the effect of the density variation among board test specimens and to suggest a more reasonable and robust method. The methods reviewed included average, specific strength, and analysis of covariance. The indicator variable method was also applied to the property comparison and compared to the other methods. The modulus of rupture of wood fiber/polymer fluff composites manufactured with different material combinations and press temperatures was tested in the experiment for evaluation of the different analysis methods. The results of this study indicated that the statistical analysis method employed was very important in the study of the physical and mechanical properties of wood composites. The specific strength method is limited to the analysis of strength comparison for the high density composites. The analysis of covariance can be applied to all the property comparisons for either high or low density composites in eliminating the density variation effect. However, error exists in the property comparison using the analysis of covariance method when the slopes of the regression lines of property vs. specific gravity (SG) are different for the different composites being tested. The indicator variable method is shown to be more reliable than the specific strength and analysis of covariance methods because it compares the linear regression lines of property vs. SG by testing both the intercept and slope based on the data in the whole specific gravity range of test specimens.References
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