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N A Cressie

Publications and source records attributed to N A Cressie.

6 recordsLinked to original sources
PubMed1988

Analysis of the time distribution and time sequence of behavioral acts.

A technique for analyzing the temporal structure between various initiations of a particular behavioral act has been developed using a parameter known as the K-function, the cornerstone of recent statistical research on spatial point processes and patterns. The technique has been extended to the study of the joint relationship of separate acts. Bootstrap methods are used to estimate the uncertainty in these measures. The usefulness of these techniques is demonstrated using data from studies of rats exposed to phenytoin and nitrous oxide.

Animals↗
PubMed1984

Use of the one sample t-test in the real world.

This work discusses how Student's t-tests might still be validly applied to medical data that may violate the usual statistical assumptions. Here the one sample t-test, which includes as a special case the paired comparisons t-test, is treated in detail. Practical "rules-of-thumb" are given, along with their applications to various examples, so that readers will easily be able to use them on their own data sets.

Deferoxamine↗
PubMed1983

Properties and interpretation of the Woolf and Scatchard plots in analysing data from steroid receptor assays.

The Woolf plot has been shown to have superior statistical properties compared with the Scatchard plot in analysing data from steroid receptor assays. This paper examines the properties of the Woolf plot, with a view to aiding its interpretation and improving familiarity with it so that its use may become more widespread. The Woolf plot contains the same information as the Scatchard plot, and deviations from linearity of the plot due to positive cooperativity, second binding sites, or non-specific binding are readily identifiable, and are described. It is emphasised, however, that the range of incubating concentrations should be chosen to give an even spread of data points on the plot. There is shown to be a relatively stable error distribution along the Woolf plot, and the implications of this for analysis of the data points are discussed. This error distribution is associated with consistently better fitting of a straight line to the data points when they are presented on the Woolf, as opposed to the Scatchard scale. This has further implications in the definition of receptor positivity, and in determining the reliability of a receptor assay result. Interpretation of the Woolf plot is easy, with the receptor site concentration being obtained from the slope of the plot, and the dissociation constant from the intersection of the extrapolated line with the abscissa. Familiarity with the plot should lead to its wider use.

Binding, Competitive↗
PubMed1981

Analysing data from hormone-receptor assays.

Assay results for hormone receptors in human breast cancer are generally plotted in the form of a Scatchard plot. Usually a line is fitted to the data points by least squares regression and thence the concentration of binding sites present in the cancer is calculated. The subsequent treatment of the patient with hormones depends on this value, so a good estimate of it is necessary. In this study, three methods of representing the data, namely the Scatchard plot, the reciprocal plot and the Woolf plot, were investigated, and three ways of fitting lines to the data points of each graph, namely least squares regression, an unweighted robust procedure and a weighted robust procedure, were examined. When the data were well-behaved all plots gave similar answers for the concentration of binding sites, irrespective of the regression technique used. However, when there were up to three outlying points, the Scatchard plot, particularly with least squares regression analysis, performed poorly. The robust regression analyses yielded more consistent results on all plots; in particular the hitherto mistrusted reciprocal scale seemed to perform well under robust regression, but other evidence indicated instability in the plot. It is concluded that the most reliable way of representing binding data in these experiments is by a Woolf plot, and that the subsequent line fitting is made resistant by an unweighted robust regression analysis.

Breast Neoplasms↗