Publications (3)4.73 Total impact
Article: Assessing nonsuperiority, noninferiority, or equivalence when comparing two regression models over a restricted covariate region.[show abstract] [hide abstract]
ABSTRACT: In many scientific problems the purpose of the comparison of two regression models, which describe the relationship between a same response variable and several same covariates for two different groups, is to demonstrate that one model is no higher than the other by a negligible amount, or to demonstrate that the models have only negligible differences and so they can be regarded as describing practically the same relationship between the response variable and the covariates. In this article, methods based on one-sided pointwise confidence bands are proposed for assessing the nonsuperiority of one model to the other and for assessing the equivalence of two regression models. Examples from QT/QTc study and from drug stability study are used to illustrate the methods.Biometrics 03/2009; 65(4):1279-87. · 1.83 Impact Factor
Article: New approach to estimating variability in visual field data using an image processing technique.[show abstract] [hide abstract]
ABSTRACT: A new framework for evaluating pointwise sensitivity variation in computerised visual field data is demonstrated. A measure of local spatial variability (LSV) is generated using an image processing technique. Fifty five eyes from a sample of normal and glaucomatous subjects, examined on the Humphrey field analyser (HFA), were used to illustrate the method. Significant correlation between LSV and conventional estimates--namely, HFA pattern standard deviation and short term fluctuation, were found. LSV is not dependent on normals' reference data or repeated threshold determinations, thus potentially reducing test time. Also, the illustrated pointwise maps of LSV could provide a method for identifying areas of fluctuation commonly found in early glaucomatous field loss.British Journal of Ophthalmology 04/1995; 79(3):213-7. · 2.90 Impact Factor
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ABSTRACT: This paper shows how to construct confidence bands for the difference between two simple linear regression lines. These confidence bands provide directly the information on the magnitude of the difference between the regression lines over an interval of interest and, as a by-product, can be used as a formal test of the difference between the two regression lines. Various different shapes of confidence bands are illustrated, and particular attention is paid towards confidence bands whose construction only involves critical points from standard distributions so that they are consequently easy to construct.Journal of Statistical Planning and Inference.