Selecting representative case vignettes for clinical judgement studies: Examples from two heart failure studies

In the Clinical Judgement Analysis (CJA) tradition there are strong arguments in favour of using representative case vignettes. Due to methodological and practical constraints, however, it is often necessary to make compromises regarding representativity. In this article, we discuss our experiences in working with these problems in connection with two studies about general practitioners heart failure diagnoses. CJA is a method for investigating and describing decision-making in which both judges and judgement situations are taken into consideration. This means that when we want to study physicians diagnoses, both the participating physicians as well as the case vignettes should be sampled to be representative for the diagnostic situation. If representativity is interpreted in a strictly statistical sense, the case vignettes should reflect a well identified population of patients regarding values, distribution and intercorrelations of the relevant patient characteristics (variables). Creating a set of representative case vignettes meeting all theoretical requirements will often be difficult. Selecting a relevant population and relevant variables, deciding about the appropriate number of variables and case vignettes, and deciding whether authentic patients or constructed case vignettes should be used are some of the problems that must be dealt with.     

Postal Surveys of Doctors’ Careers: Who Writes Comments and What do they Write About?

This study aimed to characterise the doctors who wrote comments at the end of a postal questionnaire about their careers, to quantify the frequency of negative comments, and to study relationships between the questionnaire content and the topics of comment. Graduates of all UK medical schools in 1999 were surveyed at the end of their pre-registration year. Structured questions about career intentions, current jobs and attitudes were accompanied by an invitation to write comments about any aspect of training, career choices or work. Comments were transcribed and coded according to theme and whether they were positive, negative or neutral. Numbers of comments on each theme, and of positive and negative comments, were counted. Bivariate analyses based on respondents answers to structured questions were used to characterise those who wrote comments on each theme. The survey response rate was 65%, and 40% of respondents wrote comments. Sixteen themes were identified. Ninety-four percent of those who commented said something negative or critical. Respondents who wrote comments differed in some characteristics from the whole cohort. The structured content of the questionnaire, particularly certain attitude statements, prompted the writing of comments on related themes, although not all attitudinal items acted in this way.     

The Diversity and Causality of Welfare State Reforms Explored with Fuzzy-Sets

The introduction of fuzzy-sets into social science has potentially improved our ability to study diversity by means of the so-called partial memberships. As a consequence, social phenomena can be studied empirically as a matter of degree and not longer as fixed types. A fuzzy-set is a set with elements whose membership grades can have any real value between 0 and 1. In order to illustrate the capacities of the fuzzy set logic and also to make the discussion less abstract, it will be applied to the study of welfare state reforms. The ‘grading capacity’ of fuzzy-sets makes it possible to study welfare states as partial members of different welfare state regimes at the same time. This approach reveals the diversity of welfare reforms better than traditional ways which are often inclined to picture a case as representative of one particular type which is a too crude classification. Fuzzy-sets are designed to capture the diversity in a way that leaves more room to map individual cases without falling into the trap of idiosyncrasy. An equally important ability of fuzzy-sets is to analyse causal relationships in a small-n design. The fuzzy-set logic can be used to determine necessary and sufficient conditions for an outcome. This takes the form of expressions which reveal multiple-conjunctural causation patterns. In this paper the conditions for welfare cutbacks and the effects on socio-economic performance will be examined.     

Mixture Models of Missing Data

This paper proposes a general framework for the analysis of survey data with missing observations. The approach presented here treats missing data as an unavoidable feature of any survey of the human population and aims at incorporating the unobserved part of the data into the analysis rather than trying to avoid it or make up for it. To handle coverage error and unit non-response, the true distribution is modeled as a mixture of an observable and of an unobservable component. Generally, for the unobserved component, its relative size (the no-observation rate) and its distribution are not known. It is assumed that the goal of the analysis is to assess the fit of a statistical model, and for this purpose the mixture index of fit is used. The mixture index of fit does not postulate that the statistical model of interest is able to account for the entire population rather, that it may only describe a fraction of it. This leads to another mixture representation of the true distribution, with one component from the statistical model of interest and another unrestricted one. Inference with respect to the fit of the model, with missing data taken into account, is obtained by equating these two mixtures and asking, for different no-observation rates, what is the largest fraction of the population where the statistical model may hold. A statistical model is deemed relevant for the population, if it may account for a large enough fraction of the population, assuming the true (if known) or a sufficiently small or a realistic no-observation rate.     

Explaining Differences in Economic Growth among OECD Countries

This paper re-examines the determinants of growth of GDP per capita using panel data for OECD countries for the period 1970–1999 with data averaged over five-year periods from new perspectives. First, we introduce indicators of innovation input and technological specialization simultaneously into the empirical growth equation. Second, we employ the system-GMM (Generalized-Method-of-Moments) panel estimator that controls for (a) the possible specification bias when variables are highly persistent over time and (b) the possible simultaneity bias. We find a large and statistically significant impact of business enterprise R&D (BERD) intensity on GDP per capita with an elasticity of 0.22. The share of high-technology exports is also significantly positively related to GDP per capita, but the magnitude suggests that BERD is more important than technological specialization in explaining the level of GDP per capita. Furthermore, we find that the budget deficit and government consumption (both measured as percentages of GDP) and the volatility of growth are significantly negatively related to GDP per capita.The authors would like to thank Gunther Tichy for helpful comments on an earlier draft of this article. We also thank the participants of the Austrian economic association conference (NOEG) and the Empirical Industrial Organization workshop at the WU WIEN for helpful comments. We gratefully acknowledge financial support from the OeNB Jubiläumsfonds Project and the Austrian Federal Ministry for Economy and Labor (BMWA).JEL codes: E62, H20, H50, O23, O40     

Attitudes Towards Paying Taxes in Austria: An Empirical Analysis

People mostly pay their taxes although there is a low probability of getting caught and being penalized. Thus, new attempts in the tax compliance literature try to go beyond standard economic theory. This paper examines citizens attitudes toward paying taxes – what is sometimes termed their tax morale, or the intrinsic motivation to pay taxes. Tax morale may be a key determinant to explain why people are honest. However, there are very few papers that explore the concept of tax morale theoretically and empirically. This study, based on the World Values Survey and the European Values Survey, therefore attempts to fill this gap in the literature, focusing on tax morale in Austria. Societal variables such as trust or pride have been identified as key determinants that shape tax morale in Austria. Furthermore, a lower perceived compliance leads to a decrease of tax morale, which indicates that social comparisons are relevant. The results also show a decrease of tax morale between 1990 and 1999, although Austrias taxpayers still have a very high tax morale compared to other European countries.     

Signalling cost with investment in compatibility

When buyers value products in terms of the expected compatibility between the current and the new vintage, firms can invest strategically in R&D to control for the switching costs. Open announcements of R&D budgets transmit information. The announcements determine the buyers' beliefs of the compatibility. As only an efficient firm finds it optimal to have a large R&D-budget, a firm can signal its unit cost. The likely outcome is a unique separating equilibrium if the marginal cost of R&D is low but the uncertainty over the rival's unit cost large. With high R&D cost, the dominating motive is to affect the rival's cost belief.     

Does Networking with Colleagues Matter in Enhancing Job Performance?

The present study empirically investigates the link between network properties and job performance using a sample of 121 middle managers from Beijing, China. The primary objective is to examine how characteristics of the person and the job moderate the effects of networks on self-rated performance. This study contributes to the network literature by investigating both the impact of network characteristics in terms of information accessibility and diversity on job performance and the interaction effects of gender, managerial rank, and functional areas of the ego with the network characteristics.     

How Network Strategies and Institutional Transitions Evolve in Asia

This article contributes to the literature on network strategies and institutional transitions in emerging economies in Asia by identifying a realistic, intermediate phase between the early and late phases of institutional transitions suggested by Peng (2003). Focusing on the intermediate phase, we advance two arguments based on network strength and network content. First, in terms of network strength, we leverage earlier insights that networks can be classified as strong ties and weak ties. Consequently, we suggest that as institutional transitions unfold, strong-tie-based networks, instead of being phased out, are being transformed into weak-ties-based networks. Second, from a network content standpoint, we argue that the various scale and scope of institutional transitions shape the content of different networks which focus on business-to-government (B2G) ties and business-to-business (B2B) relationships. Our propositions delineate how different transitions of political and legal institutions affect the evolution of B2G and B2B networks. Overall, we suggest that networks not only differ in strength but also in content, and that their evolution is driven by the impact of different dimensions of institutional transitions governing B2G and B2B relationships. Mike W. Peng (Ph.D., University of Washington) is a professor of global strategy at the University of Texas at Dallas, where he holds the university's first ever Provost's Distinguished Research Professorship. He was formerly an associate professor at the Fisher College of Business, The Ohio State University. He is the author of nearly 40 scholarly articles and three books, including, most recently, Global Strategy (2006). He has served on the editorial boards of AMJ, AMR, JIBS, and SMJ, and acted as a guest editor for JIBS and JMS. He is the first elected officer of the Global Strategy Interest Group at the Strategic Management Society. This is his fifth contribution to APJM. Jessie Qi Zhou is a Ph.D. candidate in international business at the Fisher College of Business, The Ohio State University. Her research interest includes strategy in emerging economies, network strategy, and organizational learning. Her main theoretical interest is institutional theory, with a focus on how institutional distance affects MNE strategies. The comparative analysis of firms' strategic choices across countries in response to different institutional environments is also of particular interest to her. Her work has been presented at the Academy of Management and Academy of International Business conferences.