Commentary: classification and cluster analysis.
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Biomedical subjects
Publications and source records attributed to B S Everitt.
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In a clinical trial one scale of pain relief is scored backwards relative to another (high on one corresponding to low on the other), with a consequent large negative correlation. But two derived scales of total pain, obtained by multiplying average pain relief on each scale by duration of pain (common to both pain relief measurements) gave an almost zero correlation. This apparent contradiction is explained by the inverse relationship between the pain relief scales and the large differences in duration of pain experienced by the patients.
Study 1 examined the reliability of the ratings assigned to the performance of five sign-and-symptom items drawn from tests of motor impairment in Parkinson's disease. Patients with Parkinson's disease of varying severity performed gait, rising from chair, and hand function items. Video recordings of these performances were rated by a large sample of experienced and inexperienced neurologists and by psychology undergraduates, using a four point scale. Inter-rater reliability was moderately high, being higher for gait than hand function items. Clinical experience proved to have no systematic effect on ratings or their reliability. The idiosyncrasy of particular performances was a major source of unreliable ratings. Study 2 examined the intercorrelation of several standard rating scales, comprised of sign-and-symptom items as well as activities of daily living. The correlation between scales was high, ranging from 0.70 to 0.83, despite considerable differences in item composition. Inter-item correlations showed that the internal cohesion of the tests was high, especially for the self-care scale. Regression analysis showed that the relationship between the scales could be efficiently captured by a small selection of test items, allowing the construction of a much briefer test.
Using a group of 55 psychotic subjects, 11 belief characteristics of delusions were recently assessed. The present study describes a cluster analysis of these data to investigate whether subjects showing characteristic patterns of delusional experience form relatively distinct groups. Three sub-groups were generated, each of which was given a descriptive label: hebephrenic, paranoid and depressed. The characteristics of these groups are described, in terms of associations with measures of mental state and belief content.
The McGill Pain Questionnaire is in widespread use as a means of understanding the pain patient and monitoring treatment response. The current study consists of a replication of the construction of the questionnaire through the use of maximally dissimilar methodology and statistical techniques. The study comprised two stages: (a) an attempt to replicate the grouping of words within the questionnaire; and (b) an investigation of the intensity relationships of words within each subgroup. A direct grouping technique was used for stage (a), whereby 90 subjects sorted the words into semantically similar groups. A similarity matrix was constructed in terms of the number of times each word was associated with each of the other 78 words and subjected to cluster analysis. Inspection of the 20-group solution revealed considerable similarity with the original questionnaire. The intensity relationships were examined by asking a further group of 20 subjects to rate words on analogue scales. The results suggest a unidimensional solution to be inappropriate for a proportion of the subgroups. While there was a close resemblance with the MPQ, there was evidence for reducing the number of subgroups, as a 16-group solution offered a sensible and statistically parsimonious amalgamation. The implications of this work for the use of questionnaire methods are discussed.
Arguments concerning the nature of depressive disorders have involved as a central issue the question of the bimodality or otherwise of the distribution of some variable expressing variation in symptomatology. The implications of a particular type of frequency distribution along this dimension, whether uni- or bi-modal, have been misunderstood by a number of workers, and an attempt is made to clarify the situation.
The purpose of this note is to indicate how the disagreement between Tennant & Bebbington and Brown & Harris has arisen. The difference between the 2 pairs of authors is due, at least in part, to their use of different models for the analysis of the data in question. There can be no final answer as to which model is correct - the data are simply open to more than one interpretation. Nevertheless, it is interesting that the use of a multiplicative model, seemingly ignored by Brown & Harris, leads to a simple description of the data in which the 'vulnerability factor' and the 'provoking agent' may be considered to act independently on the response. Consequently, in stating that their data contain an interaction so obvious that it can be detected by 'visual inspection', Brown & Harris may have been somewhat rash.
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The cortical visual prosthesis provides one approach to the substitution of vision in blind people. Usable visual information is provided in the form of phosphenes, and in order to make use of the prosthesis the positions of the phosphenes in visual space must first be determined. Such phosphene maps have to be constructed from observations of the angle and distance between various pairs of phosphenes. Because of the variation in repeated observations of the same phosphene pair, some method is needed to provide the 'best' fitting map to the observations. By formulating the problem as one involving the minimization of a function of many variables, an algorithm is constructed which determines a two-dimensional co-ordinate for each phosphene by minimizing one of two criteria indicating the fit of the map to the observations. The minimization algorithm employed is, essentially, a 'steepest descent' procedure, and initial co-ordinate values are provided by a triangulation method.
Multivariate analyses are an aid to, not a substitute for critical thinking in the area of data analysis. Meaningful results can only be produced by these methods if careful consideration is given to questions of sample size, variable type, variable distribution etc., and accusations of subjectivity in interpretation can only be overcome by replication. The computer revolution has produced many problems for statisticans, not least of which is the ease with which experiments may access packages of programs for multivariate analysis, and so bypass a "difficult" (by which is meant one who will not do simply as he is told) statistician. Of course there are many abusers of univariate statistical methods. Here, however, the abuses are not likely to lead to such seriously misleading results as in the multivariate case. Perhaps a major cause of the continuing misuse of statistical methods is the insistence of many journal editors in psychology and related areas, on articles being laced with multivariate analyses, and on encouraging the pedantic use of signifance levels, i.e. the inevitable p less than minus, as if such inclusions lent an air of respectability to their journal which it might not otherwise have had. Research workers in these fields would be better encouraged to devote more time to an initial screening of their data using simple graphical techniques, to ensure that their data are at least approximately suitable for more complicated multivariate analyses.
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