Proposals for evaluating the regularity of a scientist'sresearch output

Evaluating the career of individual scientists according to their scientific output is a common bibliometric problem. Two aspects are classically taken into account: overall productivity and overall diffusion/impact, which can be measured by a plethora of indicators that consider publications and/or citations separately or synthesise these two quantities into a single number (e.g. h-index). A secondary aspect, which is sometimes mentioned in the rules of competitive examinations for research position/promotion, is time regularity of one researcher's scientific output. Despite the fact that it is sometimes invoked, a clear definition of regularity is still lacking. We define it as the ability of generating an active and stable research output over time, in terms of both publications/ quantity and citations/diffusion. The goal of this paper is introducing three analysis tools to perform qualitative/quantitative evaluations on the regularity of one scientist's output in a simple and organic way. These tools are respectively (1) the PY/CY diagram, (2) the publication/citation Ferrers diagram and (3) a simplified procedure for comparing the research output of several scientists according to their publication and citation temporal distributions (Borda's ranking). Description of these tools is supported by several examples

Reliable estimation of prediction uncertainty for physico-chemical property models

The predictions of parameteric property models and their uncertainties are sensitive to systematic errors such as inconsistent reference data, parametric model assumptions, or inadequate computational methods. Here, we discuss the calibration of property models in the light of bootstrapping, a sampling method akin to Bayesian inference that can be employed for identifying systematic errors and for reliable estimation of the prediction uncertainty. We apply bootstrapping to assess a linear property model linking the 57Fe Moessbauer isomer shift to the contact electron density at the iron nucleus for a diverse set of 44 molecular iron compounds. The contact electron density is calculated with twelve density functionals across Jacob's ladder (PWLDA, BP86, BLYP, PW91, PBE, M06-L, TPSS, B3LYP, B3PW91, PBE0, M06, TPSSh). We provide systematic-error diagnostics and reliable, locally resolved uncertainties for isomer-shift predictions. Pure and hybrid density functionals yield average prediction uncertainties of 0.06-0.08 mm/s and 0.04-0.05 mm/s, respectively, the latter being close to the average experimental uncertainty of 0.02 mm/s. Furthermore, we show that both model parameters and prediction uncertainty depend significantly on the composition and number of reference data points. Accordingly, we suggest that rankings of density functionals based on performance measures (e.g., the coefficient of correlation, r2, or the root-mean-square error, RMSE) should not be inferred from a single data set. This study presents the first statistically rigorous calibration analysis for theoretical Moessbauer spectroscopy, which is of general applicability for physico-chemical property models and not restricted to isomer-shift predictions. We provide the statistically meaningful reference data set MIS39 and a new calibration of the isomer shift based on the PBE0 functional.Comment: 49 pages, 9 figures, 7 table

Factors contributing to successful public private partnership projects - Comparing Hong Kong with Australia and the United Kingdom

Purpose: With the increasing interest in Public Private Partnership (PPP) there is a need to investigate the factors contributing to successful delivery of PPP projects. Design/methodology/approach: An empirical questionnaire survey was conducted in Hong Kong and Australia. The survey respondents were asked to rate eighteen factors which contribute to delivering successful PPP projects. Findings: The findings from this survey were further compared with the results achieved by a previous researcher (Li, 2003) in a similar survey conducted in the United Kingdom. The comparison showed that amongst the top five success factors ranked by Hong Kong respondents, three were also ranked highly by the Australians and British. These success factors included: ‘Commitment and responsibility of public and private sectors’; ‘Strong and good private consortium’; and ‘Appropriate risk allocation and risk sharing’. Originality/value: These success factors were therefore found to be important for contributing to successful PPP projects irrespective of geographical locations

Determining the Success of NCAA Basketball Teams through Team Characteristics

Every year much of the nation becomes engulfed in the NCAA basketball postseason tournament more affectionately known as “March Madness.” The tournament has received the name because of the ability for any team to win a single game and advance to the next round. The purpose of this study is to determine whether concrete statistical measures can be used to predict the final outcome of the tournament. The data collected in the study include 13 independent variables ranging from the 2003-2004 season up until the current 2009-2010 season. Different tests were run in an attempt to achieve the most accurate predictive model. First, the data were input into Excel and ordinary least squares regressions were run for each year. Then the data were compiled into one file and an ordinary least squares regression was run on that collection of data in Excel. Next, the data were input into Minitab and a stepwise regression was run in order to keep only the significant independent variables. Following that, a regression analysis was run in Minitab. The coefficients from that regression analysis were input into a file with the 2009-2010 data in an attempt to test the model’s results against the actual results. All of the models developed, except one for the year 2005-2006, were determined to be significant. There were 6 significant independent variables determined. The final results showed that although the model developed through the study was significant, the ability to accurately predict the outcomes is very difficult

Assessing Hedge Fund Performance: Does the Choice of Measures Matter?

In this paper, we conducted a comparative study of ten measures documented as the most used by researchers and practionners: Sharpe, Sortino, Calmar, Sterling, Burke, modified Stutzer, modified Sharpe, upside potential ratio, Omega and AIRAP. This study was carried out in two stages on a sample of 149 hedge funds. First, we examined the modifications of funds' relative performance in terms of ranks and deciles when the performance measure changes. Despite strong positive correlations between funds' rankings established by different measures, numerous significant modifications were observed. Second, we studied the stability/persistence of the ten measures in question. Our results show that some measures are more stable or persistent than the others in measuring hedge fund performance.hedge funds; performance evaluation; performance measure; Sharpe ratio

Regularity in the research output of individual scientists: An empirical analysis by recent bibliometric tools

This paper proposes an empirical analysis of several scientists based on their time regularity, defined as the ability of generating an active and stable research output over time, in terms of both quantity/publications and impact/citations. In particular, we empirically analyse three recent bibliometric tools to perform qualitative/quantitative evaluations under the new perspective of regularity. These tools are respectively (1) the PY/CY diagram, (2) the publication/citation Ferrers diagram and triad indicators, and (3) a year-by-year comparison of the scientists' output (Borda's ranking). Results of the regularity analysis are then compared with those obtained under the classical perspective of overall production. The proposed evaluation tools can be applied to competitive examinations for research position/promotion, as complementary instruments to the commonly adopted bibliometric technique

Comparing efficiency of health systems across industrialized countries: a panel analysis.

BackgroundRankings from the World Health Organization (WHO) place the US health care system as one of the least efficient among Organization for Economic Cooperation and Development (OECD) countries. Researchers have questioned this, noting simplistic or inappropriate methodologies, poor measurement choice, and poor control variables. Our objective is to re-visit this question by using newer modeling techniques and a large panel of OECD data.MethodsWe primarily use the OECD Health Data for 25 OECD countries. We compare results from stochastic frontier analysis (SFA) and fixed effects models. We estimate total life expectancy as well as life expectancy at age 60. We explore a combination of control variables reflecting health care resources, health behaviors, and economic and environmental factors.ResultsThe US never ranks higher than fifth out of all 36 models, but is also never the very last ranked country though it was close in several models. The SFA estimation approach produces the most consistent lead country, but the remaining countries did not maintain a steady rank.DiscussionOur study sheds light on the fragility of health system rankings by using a large panel and applying the latest efficiency modeling techniques. The rankings are not robust to different statistical approaches, nor to variable inclusion decisions.ConclusionsFuture international comparisons should employ a range of methodologies to generate a more nuanced portrait of health care system efficiency