Quantifying evidence for forensic authorship analysis

The judicial interest in ‘scientific’ evidence has driven recent work to quantify results for forensic linguistic authorship analysis. Through a methodological discussion and a worked example this paper examines the issues which complicate attempts to quantify results in work. The solution suggested to some of the difficulties is a sampling and testing strategy which helps to identify potentially useful, valid and reliable markers of authorship. An important feature of the sampling strategy is that these markers identified as being generally valid and reliable are retested for use in specific authorship analysis cases. The suggested approach for drawing quantified conclusions combines discriminant function analysis and Bayesian likelihood measures. The worked example starts with twenty comparison texts for each of three potential authors and then uses a progressively smaller comparison corpus, reducing to fifteen, ten, five and finally three texts per author. This worked example demonstrates how reducing the amount of data affects the way conclusions can be drawn. With greater numbers of reference texts quantified and safe attributions are shown to be possible, but as the number of reference texts reduces the analysis shows how the conclusion which should be reached is that no attribution can be made. The testing process at no point results in instances of a misattribution.

Insufficient discriminant validity:a comment on Bove, Pervan, Beatty and Shiu (2009)

Bove, Pervan, Beatty, and Shiu [Bove, LL, Pervan, SJ, Beatty, SE, Shiu, E. Service worker role in encouraging customer organizational citizenship behaviors. J Bus Res 2009;62(7):698–705.] develop and test a latent variable model of the role of service workers in encouraging customers' organizational citizenship behaviors. However, Bove et al. [Bove, LL, Pervan, SJ, Beatty, SE, Shiu, E. Service worker role in encouraging customer organizational citizenship behaviors. J Bus Res 2009;62(7):698–705.] claim support for hypothesized relationships between constructs that, due to insufficient discriminant validity regarding certain constructs, may be inaccurate. This research comment discusses what discriminant validity represents, procedures for establishing discriminant validity, and presents an example of inaccurate discriminant validity assessment based upon the work of Bove et al. [Bove, LL, Pervan, SJ, Beatty, SE, Shiu, E. Service worker role in encouraging customer organizational citizenship behaviors. J Bus Res 2009;62(7):698–705.]. Solutions to discriminant validity problems and a five-step procedure for assessing discriminant validity then conclude the paper. This comment hopes to motivate a review of discriminant validity issues and offers assistance to future researchers conducting latent variable analysis.

The analysis of organic matter in oil-shales

The organic matter in five oil shales (three from the Kimmeridge Clay sequence, one from the Oxford Clay sequence and one from the Julia Creek deposits in Australia) has been isolated by acid demineralisation, separated into kerogens and bitumens by solvent extraction and then characterised in some detail by chromatographic, spectroscopic and degradative techniques. Kerogens cannot be characterised as easily as bitumens because of their insolubility, and hence before any detailed molecular information can be obtained from them they must be degraded into lower molecular weight, more soluble components. Unfortunately, the determination of kerogen structures has all too often involved degradations that were far too harsh and which lead to destruction of much of the structural information. For this reason a number of milder more selective degradative procedures have been tested and used to probe the structure of kerogens. These are: 1. Lithium aluminium hydride reduction. - This procedure is commonly used to remove pyrite from kerogens and it may also increase their solubility by reduction of labile functional groups. Although reduction of the kerogens was confirmed, increases in solubility were correlated with pyrite content and not kerogen reduction. 2. O-methylation in the presence of a phase transfer catalyst. - By the removal of hydrogen bond interactions via O-methylation, it was possible to determine the contribution of such secondary interactions to the insolubility of the kerogens. Problems were encountered with the use of the phase transfer catalyst. 3. Stepwise alkaline potassium permanganate oxidation. - Significant kerogen dissolution was achieved using this procedure but uncontrolled oxidation of initial oxidation products proved to be a problem. A comparison with the peroxytrifluoroaceticacid oxidation of these kerogens was made. 4. Peroxytrifluoroacetic acid oxidation. - This was used because it preferentially degrades aromatic rings whilst leaving any benzylic positions intact. Considerable conversion of the kerogens into soluble products was achieved with this procedure. At all stages of degradation the products were fully characterised where possible using a variety of techniques including elemental analysis, solution state 1H and 13C nuclear magnetic resonance, solid state 13C nuclear magnetic resonance, gel-permeationchromatography, gas chromatography-mass spectroscopy, fourier transform infra-red spectroscopy and some ultra violet-visible spectroscopy.

A study of cluster analysis techniques and their applications

This thesis seeks to describe the development of an inexpensive and efficient clustering technique for multivariate data analysis. The technique starts from a multivariate data matrix and ends with graphical representation of the data and pattern recognition discriminant function. The technique also results in distances frequency distribution that might be useful in detecting clustering in the data or for the estimation of parameters useful in the discrimination between the different populations in the data. The technique can also be used in feature selection. The technique is essentially for the discovery of data structure by revealing the component parts of the data. lhe thesis offers three distinct contributions for cluster analysis and pattern recognition techniques. The first contribution is the introduction of transformation function in the technique of nonlinear mapping. The second contribution is the us~ of distances frequency distribution instead of distances time-sequence in nonlinear mapping, The third contribution is the formulation of a new generalised and normalised error function together with its optimal step size formula for gradient method minimisation. The thesis consists of five chapters. The first chapter is the introduction. The second chapter describes multidimensional scaling as an origin of nonlinear mapping technique. The third chapter describes the first developing step in the technique of nonlinear mapping that is the introduction of "transformation function". The fourth chapter describes the second developing step of the nonlinear mapping technique. This is the use of distances frequency distribution instead of distances time-sequence. The chapter also includes the new generalised and normalised error function formulation. Finally, the fifth chapter, the conclusion, evaluates all developments and proposes a new program. for cluster analysis and pattern recognition by integrating all the new features.

Statnote 25: Stepwise multiple regression

An investigator may also wish to select a small subset of the X variables which give the best prediction of the Y variable. In this case, the question is how many variables should the regression equation include? One method would be to calculate the regression of Y on every subset of the X variables and choose the subset that gives the smallest mean square deviation from the regression. Most investigators, however, prefer to use a ‘stepwise multiple regression’ procedure. There are two forms of this analysis called the ‘step-up’ (or ‘forward’) method and the ‘step-down’ (or ‘backward’) method. This Statnote illustrates the use of stepwise multiple regression with reference to the scenario introduced in Statnote 24, viz., the influence of climatic variables on the growth of the crustose lichen Rhizocarpon geographicum (L.)DC.