Cognitive and interpersonal abilities related to the primary activities of R&D managers

This study attempted to identify the primary activities performed by R&D managers at different supervisory levels, and the cognitive and interpersonal ability requirements that underlie these activities. A task inventory containing 244 managerial tasks was completed by 117 R&D managers in nine organizations. The 48 tasks which managers rated as having spent the most time were factor analyzed, resulting in the identification of three primary activities: project management, personnel supervision, and strategic planning. Furthermore, these activities varied with supervisory level, with R&D managers performing a wider range of these activities with the progression from first-line to upper-level management.Thirty R&D managers later rated the degree to which 19 cognitive and interpersonal abilities were required for performing these primary activities. Strategic planning was rated as requiring significantly higher levels of oral expression, logical reasoning, originality, fluency of ideas, oral defense, and resistance to premature judgement than was required for the other two primary activities. Personnel supervision required a higher level of social sensitivity than was required for the other two activities. Project management required high levels of information ordering, oral fact- finding ability, problem sensitivity, and oral and written comprehension. Implications of the findings for understanding R&D managerial performance and personnel staffing functions are discussed.     

Effects of Category Order on Answers in Mail and Telephone Surveys1

Abstract Past research suggests that mail surveys encourage a primacy effect, which is a tendency to choose the first answers from a list, whereas telephone surveys encourage a recency effect, a tendency to choose the last answers from a list. This paper summarizes results from 82 new experiments conducted in 12 separate surveys in seven states. Only four of 33 mail survey comparisons exhibited significant primacy effects, while five of 26 experiments in telephone surveys exhibited recency effects. In addition, only three of 23 cross-method comparisons produced a significant primacy/recency effect in the expected manner. The conclusion is that the prevalence of primacy and recency effects has been over-estimated by past research and a new theoretical approach that takes into account multiple causation is needed for examining these effects.     

The State of the Field in UK Management Research: Reflections of the Research Assessment Exercise (RAE) Panel

This paper reviews the state of the field of the sub-disciplines within UK management research, based upon the submissions of 94 UK higher education institutions to the Business and Management Studies Panel in the UK's 2001 Research Assessment Exercise (RAE). It offers observations on the UK model of the assessment of quality in, and funding of, research conducted in publicly funded higher education institutions.     

Odd-Burr generalized family of distributions with some applications

We study a new family of continuous distributions with two extra shape parameters called the Burr generalized family of distributions. We investigate the shapes of the density and hazard rate function. We derive explicit expressions for some of its mathematical quantities. The estimation of the model parameters is performed by maximum likelihood. We prove the flexibility of the new family by means of applications to two real data sets. Furthermore, we propose a new extended regression model based on the logarithm of the Burr generalized distribution. This model can be very useful to the analysis of real data and provide more realistic fits than other special regression models.     

Joint models for mixed categorical outcomes: a study of HIV risk perception and disease status in Mozambique

Two types of bivariate models for categorical response variables are introduced to deal with special categories such as ‘unsure’ or ‘unknown’ in combination with other ordinal categories, while taking additional hierarchical data structures into account. The latter is achieved by the use of different covariance structures for a trivariate random effect. The models are applied to data from the INSIDA survey, where interest goes to the effect of covariates on the association between HIV risk perception (quadrinomial with an ‘unknown risk’ category) and HIV infection status (binary). The final model combines continuation-ratio with cumulative link logits for the risk perception, together with partly correlated and partly shared trivariate random effects for the household level. The results indicate that only age has a significant effect on the association between HIV risk perception and infection status. The proposed models may be useful in various fields of application such as social and biomedical sciences, epidemiology and public health.     

The generalized odd half-Cauchy family of distributions: Properties and applications

We introduce and study general mathematical properties of a new generator of continuous distributions with one extra parameter called the generalized odd half-Cauchy family. We present some special models and investigate the asymptotics and shapes. The new density function can be expressed as a linear mixture of exponentiated densities based on the same baseline distribution. We derive a power series for the quantile function. We discuss the estimation of the model parameters by maximum likelihood and prove empirically the flexibility of the new family by means of two real data sets.     

Paired comparisons analysis: an axiomatic approach to ranking methods

In this paper we present an axiomatic analysis of several ranking methods for general tournaments. We find that the ranking method obtained by applying maximum likelihood to the (Zermelo-)Bradley-Terry model, the most common method in statistics and psychology, is one of the ranking methods that perform best with respect to the set of properties under consideration. A less known ranking method, generalised row sum, performs well too. We also study, among others, the fair bets ranking method, widely studied in social choice, and the least squares method.     

A new regression model for bimodal data and applications in agriculture

We define the odd log-logistic exponential Gaussian regression with two systematic components, which extends the heteroscedastic Gaussian regression and it is suitable for bimodal data quite common in the agriculture area. We estimate the parameters by the method of maximum likelihood. Some simulations indicate that the maximum-likelihood estimators are accurate. The model assumptions are checked through case deletion and quantile residuals. The usefulness of the new regression model is illustrated by means of three real data sets in different areas of agriculture, where the data present bimodality.     

Open Dialogue: Frequently Asked Questions

Open Dialogue is an approach to working with people and their families experiencing psychosocial distress. Interest in Open Dialogue in Australia has been growing recently, raising questions about its adaption and implementation to local contexts. This article is an attempt to answer some of the frequently asked questions we have encountered in training and discussions about Open Dialogue. We attempt to provide responses to questions of how Open Dialogue is different to what is done already, how it fits with current approaches, how you know if you are doing it, whether it is passive or just about doing reflections, issues about including the social network, and concerns about the evidence base. This article aims to present a variety of viewpoints in relation to these questions and to hopefully further discussions on how Open Dialogue can be implemented and adapted to Australian health care and social care contexts.     

The generalized log-gamma mixture model with covariates: local influence and residual analysis

In a sample of censored survival times, the presence of an immune proportion of individuals who are not subject to death, failure or relapse, may be indicated by a relatively high number of individuals with large censored survival times. In this paper the generalized log-gamma model is modified for the possibility that long-term survivors may be present in the data. The model attempts to separately estimate the effects of covariates on the surviving fraction, that is, the proportion of the population for which the event never occurs. The logistic function is used for the regression model of the surviving fraction. Inference for the model parameters is considered via maximum likelihood. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. Finally, a data set from the medical area is analyzed under the log-gamma generalized mixture model. A residual analysis is performed in order to select an appropriate model. The authors would like to thank the editor and referees for their helpful comments. This work was supported by CNPq, Brazil.