The derivation of a brief Student Nurse Stress Index

The lack of an adequate measure of perceived sources of stress for student nurses led to the construction of the Student Nurse Stress Index (SNSI). Responses from 235 first-year student nurses to 35 items from the Beck and Srivastava Stress Inventory (Beck, and Srivastava, 1991), and 15 new items, were subjected to exploratory factor analysis using principal components analysis and oblimin rotation. A reliable 22-variable solution with a simple oblique structure including Academic load, Clinical sources, Interface worries, and Personal problems factors was obtained in this initial sample, and confirmed at an exploratory level in a further independent validation sample of 188 first-year students. Confirmatory factor analysis established the four-factor model in the first sample, but required that three variables load onto more than one factor. This more complex four-factor model was confirmed using independent data from the validation sample, and the total invariance of factor loadings and factor covariances of this more complex four-factor model was established in both data sets simultaneously using multi-sample techniques. The SNSI shows cross-sample factor congruence, good internal reliabilities, and concurrent and discriminant validity across a range of reporting conditions.     

Bayesian incorporation of repeated measurements in logistic discrimination

A common problem in medical statistics is the discrimination between two groups on the basis of diagnostic information. Information on patient characteristics is used to classify individuals into one of two groups: diseased or disease-free. This classification is often with respect to a particular disease. This discrimination has two probabilistic components: (1) the discrimination is not without error, and (2) in many cases the a priori chance of disease can be estimated. Logistic models (Cox 1970; Anderson 1972) provide methods for incorporating both of these components. The a posteriori probability of disease may be estimated for a patient on the basis of both current measurement of patient characteristics and prior information. The parameters of the logistic model may be estimated on the basis of a calibration trial. In practice, not one but several sets of measurements of one characteristic of the patient may be made on a questionable case. These measurements typically are correlated; they are far from independent. How should these correlated measurements be used? This paper presents a method for incorporating several sets of measurements in the classification of a case.     

The robustness and optimality of response surface designs

Recent work on extended optimality criteria for robust designs is applied to response surface problems. Methods of calculation are described and the criteria illustrated with several examples. The extended criteria discriminate among designs equivalent by other criteria.     

Inference Based on Conditional Moment Inequalities

In this paper, we propose an instrumental variable approach to constructing confidence sets (CS's) for the true parameter in models defined by conditional moment inequalities/equalities. We show that by properly choosing instrument functions, one can transform conditional moment inequalities/equalities into unconditional ones without losing identification power. Based on the unconditional moment inequalities/equalities, we construct CS's by inverting Cramér–von Mises‐type or Kolmogorov–Smirnov‐type tests. Critical values are obtained using generalized moment selection (GMS) procedures. We show that the proposed CS's have correct uniform asymptotic coverage probabilities. New methods are required to establish these results because an infinite‐dimensional nuisance parameter affects the asymptotic distributions. We show that the tests considered are consistent against all fixed alternatives and typically have power against n^−1/2‐local alternatives to some, but not all, sequences of distributions in the null hypothesis. Monte Carlo simulations for five different models show that the methods perform well in finite samples.     

Graphical Display of Means

A graphical procedure for the display of treatment means that enables one to determine the statistical significance of the observed differences is presented. It is shown that the widely used least significant difference and honestly significant difference statistics can be used to construct plots in which any two means whose uncertainty intervals do not overlap are significantly different at the assigned probability level. It is argued that these plots, because of their straightforward decision rules, are more effective than those that show the observed means with standard errors or confidence limits. Several examples of the proposed displays are included to illustrate the procedure.     

Was Blumer a cognitivist? Assessing an ethnomethodological critique

A major target of criticism for ethnomethodology has been cognitivism. In its broadest sense this term refers to any account of human behaviour that treats psychological features of agents – including beliefs, attitudes, and interpretations – as factors explaining their behaviour. While much criticism of cognitivism has been directed at neuroscientists and philosophical materialists, the range of targets has been wider than this, even including sociologists such as Herbert Blumer and symbolic interactionists. In this article I outline this criticism of Blumer and assess it. My conclusion is that, despite some misreading, his work does fall into the broad category of cognitivism. However, I question the grounds for the ethnomethodological critique.