TY - JOUR
T1 - Analysis of robust design experiments with time-dependent ordinal response characteristics
T2 - A quality improvement study from the horticulture industry
AU - Parsons, N. R.
AU - Gilmour, S. G.
AU - Edmondson, R. N.
PY - 2009/9
Y1 - 2009/9
N2 - An approach to the analysis of time-dependent ordinal quality score data from robust design experiments is developed and applied to an experiment from commercial horticultural research, using concepts of product robustness and longevity that are familiar to analysts in engineering research. A two-stage analysis is used to develop models describing the effects of a number of experimental treatments on the rate of post-sales product quality decline. The first stage uses a polynomial function on a transformed scale to approximate the quality decline for an individual experimental unit using derived coefficients and the second stage uses a joint mean and dispersion model to investigate the effects of the experimental treatments on these derived coefficients. The approach, developed specifically for an application in horticulture, is exemplified with data from a trial testing ornamental plants that are subjected to a range of treatments during production and home-life. The results of the analysis show how a number of control and noise factors affect the rate of post-production quality decline. Although the model is used to analyse quality data from a trial on ornamental plants, the approach developed is expected to be more generally applicable to a wide range of other complex production systems.
AB - An approach to the analysis of time-dependent ordinal quality score data from robust design experiments is developed and applied to an experiment from commercial horticultural research, using concepts of product robustness and longevity that are familiar to analysts in engineering research. A two-stage analysis is used to develop models describing the effects of a number of experimental treatments on the rate of post-sales product quality decline. The first stage uses a polynomial function on a transformed scale to approximate the quality decline for an individual experimental unit using derived coefficients and the second stage uses a joint mean and dispersion model to investigate the effects of the experimental treatments on these derived coefficients. The approach, developed specifically for an application in horticulture, is exemplified with data from a trial testing ornamental plants that are subjected to a range of treatments during production and home-life. The results of the analysis show how a number of control and noise factors affect the rate of post-production quality decline. Although the model is used to analyse quality data from a trial on ornamental plants, the approach developed is expected to be more generally applicable to a wide range of other complex production systems.
KW - Joint mean-dispersion model
KW - Ordinal scores
KW - Proportional odds model
KW - Robust product design
KW - Two-stage analysis
UR - http://www.scopus.com/inward/record.url?scp=70349817371&partnerID=8YFLogxK
U2 - 10.1080/02664760802566796
DO - 10.1080/02664760802566796
M3 - Article
AN - SCOPUS:70349817371
SN - 0266-4763
VL - 36
SP - 1037
EP - 1054
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
IS - 9
ER -