Int. J. of Data Science   »   2016 Vol.1, No.4

 

 

Title: Resistant measures in assessing the adequacy of split-plot design models

 

Authors: Ikwuoche J. David; Osebekwin E. Asiribo; Hussaini G. Dikko

 

Addresses:
Department of Mathematics, Ahmadu Bello University, Zaria 800001, Nigeria
Department of Mathematics, Ahmadu Bello University, Zaria 800001, Nigeria
Department of Mathematics, Ahmadu Bello University, Zaria 800001, Nigeria

 

Abstract: This paper assesses the adequacy of model fit of the split-plot design models, that is the whole plot (WP) sub-design model with WP error and the split-plot (SP) sub-design model with SP error for comparing the effectiveness of resistant measures that use medians instead of means, resulting in a coefficient that is more resistant to outliers or extreme data points. This paper presents empirical application of four measures of model adequacy check and they are coefficient of determination (R2), modelling efficiency (MEF) statistic, prediction coefficient of determination (R2prod), and mean square error prediction (MSEP). These four measures were explored using their mean and median form. A 2(1+3) replicated two-level SP design and a 31 × 42 replicated mixed level SP design were used for computing the measures of model adequacy of fit for each WP and SP sub-design models. These measures in their median form described the predictive performance of each WP and SP sub-design models adequately.

 

Keywords: modelling efficiency; mean square error; MSE prediction; whole plot errors; split-plot errors; model adequacy; split-plot design; model fit; resistant measures; medians.

 

DOI: 10.1504/IJDS.2016.10002333

 

Int. J. of Data Science, 2016 Vol.1, No.4, pp.382 - 396

 

Available online: 05 Jan 2017

 

 

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