Analysis of the Bovine Spongiform Encephalopathy Maternal Cohort Study: Evidence for Direct Maternal Transmission

In an initial exploratory analysis of the bovine spongiform encephalopathy (BSE) maternal cohort study data we demonstrate several confounding effects in the study design. Given these effects, we assess a variety of statistical models to determine the relative contributions of direct maternal transmission of the aetiological agent of BSE and of genetic susceptibility to the observed maternally enhanced risk of BSE in the offspring of affected dams. To control for the substantial between-herd variation in the risk of exposure to the BSE agent, it is essential that analyses take into account the matched pair structure of the data. Maternal exposure is estimated to be most important in animals born within 150 days of disease onset in their dams. The analysis of a full survival likelihood model indicates that the hypothesis of maternal transmission with no genetic variation in susceptibility fits the data significantly better than the hypothesis of genetically variable susceptibility with no maternal transmission. However, models incorporating both maternal transmission and genetically variable susceptibility fit the data significantly better than pure maternal transmission models. Although genetic susceptibility cannot be excluded as the cause of the cohort study results in the absence of detailed genotyping, the analysis of these study data suggest that low level maternal transmission of BSE is, at least in part, responsible for the significantly enhanced risk of BSE in the offspring of affected dams. Similar results indicating significant maternal transmission in the later stages of the dam incubation period are obtained from the independent analysis of data on the dam–offspring relationships among confirmed BSE cases.     

Hong Kong managers' perceptions of American business values

This report describes empirical research conducted to study the research question, “To what extent do foreign managers' own cultural values influence their perceptions of the corporate values of companies in other cultures?” Using the authors' “Business Values Questionnaire,” business managers from Hong Kong gave their perceptions of publicly stated corporate values of very large U.S. service companies. A similar United States sample was used as a comparison group. Results gave partial support to the authors' hypotheses that an individual's own cultural values influence perceived values of another culture.     

Long- and short-term affective states in happiness: Model,paradigm and experimental evidence

The present paper evaluates relevant findings on long- and short-term affective states in subjective well-being and argues for a componential model that combines the two into the more general concept of happiness. Two age parameters, one for long-term and one for short-term affect are added to the simple model to account for age changes in happiness. Measures of long- and short-term affect are presented, as is a paradigm for separating the components. Support for the simple model is provided by an experimental investigation with 64 college students who were exposed to positive and/or negative mood induction. As expected, the induction had substantially greater effect on short- than on long-term affect measures, particularly the negative induction procedure. These findings are consistent with predictions. However, multiple age cohorts will have to be assessed within a longitudinal framework to obtain values for the age parameters.     

CORRECTING FOR MEASUREMENT ERROR IN AN EXPOSURE-RESPONSE RELATIONSHIP BASED ON DICHOTOMISING A CONTINUOUS DEPENDENT VARIABLE

Random error in a continuous outcome variable does not affect its regression on a predictor. However, when a continuous outcome variable is dichotomised, random measurement error results in a flatter exposure-response relationship with a higher intercept. Although this consequence is similar to the effect of misclassification in a binary outcome variable, it cannot be corrected using techniques appropriate for binary data. Conditional distributions of the measurements of the continuous outcome variable can be corrected if the reliability coefficient of the measurements can be estimated. An unbiased estimate of the exposure-response relationship is then easily calculated. This procedure is demonstrated using data on the relationship between smoking and the development of airway obstruction.     

Grounded theory research: Procedures,canons, and evaluative criteria

Using grounded theory as an example, this paper examines three methodological questions that are generally applicable to all qualitative methods. How should the usual scientific canons be reinterpreted for qualitative research? How should researchers report the procedures and canons used in their research? What evaluative criteria should be used in judging the research products? We propose that the criteria should be adapted to fit the procedures of the method. We demonstrate how this can be done for grounded theory and suggest criteria for evaluating studies following this approach. We argue that other qualitative researchers might be similarly specific about their procedures and evaluative criteria.     

Rejoinder to 'Ahmed, M.S. (1998). A note on regression-type estimators using multiple auxiliary information.'

In the estimators t ₃ , t ₄ , t ₅ of Mukerjee, Rao & Vijayan (1987), b _{y x} and b _{y z} are partial regression coefficients of y on x and z , respectively, based on the smaller sample. With the above interpretation of b _{y x} and b _{y z} in t ₃ , t ₄ , t ₅ , all the calculations in Mukerjee at al. (1987) are correct. In this connection, we also wish to make it explicit that b _{x z} in t ₅ is an ordinary and not a partial regression coefficient. The 'corrected' MSEs of t ₃ , t ₄ , t ₅ , as given in Ahmed (1998 Section 3) are computed assuming that our b _{y x} and b _{y z} are ordinary and not partial regression coefficients. Indeed, we had no intention of giving estimators using the corresponding ordinary regression coefficients which would lead to estimators inferior to those given by Kiregyera (1984). We accept responsibility for any notational confusion created by us and express regret to readers who have been confused by our notation. Finally, in consideration of the above, it may be noted that Tripathi & Ahmed's (1995) estimator t ₀ , quoted also in Ahmed (1998), is no better than t ₅ of Mukerjee at al. (1987).