Accounting for time-dependent treatment use when developing a prognostic model from observational data: A review of methods

Failure to account for time-dependent treatment use when developing a prognostic model can result in biased future predictions. We reviewed currently available methods to account for treatment use when developing a prognostic model. First, we defined the estimands targeted by each method and examined their mechanisms of action with directed acyclic graphs (DAGs). Next, methods were implemented in data from 1,906 patients; 325 received selective β-blockers (SBBs) during follow-up. We demonstrated seven Cox regression modeling strategies: (a) ignoring SBB treatment; (b) excluding SBB users or (c) censoring them when treated; (d) inverse probability of treatment weighting after censoring (IPCW), including SBB treatment as (e) a binary or (f) a time-dependent covariate; and (g) marginal structural modeling (MSM). Using DAGs, we demonstrated IPCW and MSM have the best properties and target a similar estimand. In the case study, compared to (a), approaches (b) and (e) provided predictions that were 1% and 2% higher on average. Performance (c-statistic, Brier score, calibration slope) varied minimally between approaches. Our review of methods confirmed that ignoring treatment is theoretically inferior, but differences between the prediction models obtained using different methods can be modest in practice. Future simulation studies and applications are needed to assess the value of applying IPCW or MSM to adjust for treatments in different treatment and disease settings.     

Estimation of the Pareto law from underreported data: A further analysis

Estimation of parameters of the Pareto income distribution is discussed for the situation when data are underreported, i.e., observed with negative random bias. Specifically it is proved that maximum likelihood estimates are consistent and asymptotically normal in large samples, and formulae for the large-sample standard errors are given. The large-sample theory illustrates how some important results from mathematical statistics apply to non-standard statistical models.     

Lessons from innovation empirical studies in the manufacturing sector: A systematic review of the literature from 1993–2003

What is innovation and what determines its development in manufacturing firms? The literature on the topic has evolved exponentially during the last decades. However, the divergence of the research results makes it so that the innovation process is still poorly understood. Relying on a systematic review of empirical studies published between 1993 and 2003, this article propose and discuss a framework which brings together a set of variables related to the innovation process and the internal and contextual factors driving it. The ensuing results highlight several avenues which would help managers and policy makers to better foster innovation and researchers to better channel their efforts in studying the phenomenon.     

Problems in the estimation and interpretation of the reliability of survey data

In this paper I discuss several of the difficulties involved in estimating the reliability of survey measurement. Reliability is defined on the basis of classical true-score theory, as the correlational consistency of multiple measures of the same construct, net of true change. This concept is presented within the framework of a theoretical discussion of the sources of error in survey data and the design requirements for separating response variation into components representing such response consistency and measurement errors. Discussion focuses on the potential sources of random and nonrandom errors, including “invalidity” of measurement, the term frequently used to refer to components of method variance. Problems with the estimation of these components are enumerated and discussed with respect to both cross-sectional and panel designs. Empirical examples are given of the estimation of the quantities of interest, which are the basis of a discussion of the interpretational difficulties encountered in reliability estimation. Data are drawn from the ISR's Quality of Life surveys, the National Election Studies and the NORC's General Social Surveys. The general conclusion is that both cross-sectional and panel estimates of measurement reliability are desirable, but for the purposes of isolating the random component of error, panel designs are probably the most advantageous.     

A Flexible Tool for Model Building: the Relevant Transformation of the Inputs Network Approach (RETINA)*

A new method, called Relevant Transformation of the Inputs Network Approach is proposed as a tool for model building. It is designed around flexibility (with nonlinear transformations of the predictors of interest), selective search within the range of possible models, out‐of‐sample forecasting ability and computational simplicity. In tests on simulated data, it shows both a high rate of successful retrieval of the data generating process, which increases with the sample size and a good performance relative to other alternative procedures. A telephone service demand model is built to show how the procedure applies on real data.     

特高压输电线路电晕可听噪声研究综述

随着特高压交直流输电网的建设,电晕可听噪声引起环保纠纷也日趋增多,因此,研究输电线路电晕可听噪声的来源、形成机理以及相关降噪措施,对构建环境友好型社会具有重要意义。文章通过对以往研究成果的归纳总结,综合分析了特高压输电线路正/负极性电晕可听噪声特征,湿度、降雨及污秽对电晕可听噪声的影响机制和电晕可听噪声的测量方法,并探讨了输电线路降噪的相关技术路线。     

A cautionary note on methods of comparing programmatic efficiency between two or more groups of DMUs in data envelopment analysis

In some applications of data envelopment analysis (DEA) there may be doubt as to whether all the DMUs form a single group with a common efficiency distribution. The Mann–Whitney rank statistic has been used to evaluate if two groups of DMUs come from a common efficiency distribution under the assumption of them sharing a common frontier and to test if the two groups have a common frontier. These procedures have subsequently been extended using the Kruskal–Wallis rank statistic to consider more than two groups. This technical note identifies problems with the second of these applications of both the Mann–Whitney and Kruskal–Wallis rank statistics. It also considers possible alternative methods of testing if groups have a common frontier, and the difficulties of disaggregating managerial and programmatic efficiency within a non-parametric framework.      

The inventory performance of forecasting methods: Evidence from the M3 competition data

Forecasting competitions have been a major driver not only of improvements in forecasting methods’ performances, but also of the development of new forecasting approaches. However, despite the tremendous value and impact of these competitions, they do suffer from the limitation that performances are measured only in terms of the forecast accuracy and bias, ignoring utility metrics. Using the monthly industry series of the M3 competition, we empirically explore the inventory performances of various widely used forecasting techniques, including exponential smoothing, ARIMA models, the Theta method, and approaches based on multiple temporal aggregation. We employ a rolling simulation approach and analyse the results for the order-up-to policy under various lead times. We find that the methods that are based on combinations result in superior inventory performances, while the Naïve, Holt, and Holt-Winters methods perform poorly.     

Estimating the impact of regional policy: A review of applied research methods

This paper provides a critical review of the methodological approaches that have been used to estimate the impacts of regional economic policies. A considerable variety of approaches are examined, ranging from questionnaire studies through single- and multiple-equation regression models to cost-benefits analysis, and attention is focused on the pros and cons of these approaches and the reliability of the impact assessments derived. The paper concludes with some suggestions for further research in this field.     

A review of techniques for treating missing data in OM survey research

The treatment of missing data has been overlooked by the OM literature, while other fields such as marketing, organizational behavior, economics, statistics and psychometrics have paid more attention to the issue. A review of 103 survey-based articles published in the Journal of Operations Management between 1993 and 2001 shows that listwise deletion, which is often the least accurate technique of dealing with missing data, is heavily utilized by OM researchers. The paper also discusses the research implications of missing data, types of missing data and concludes with recommendations on which techniques should be used under different circumstances in order to improve the treatment of missing data in OM survey research.     

Timing and duration effects in residence histories and other longitudinal data: Part 1. Stochastic and statistical models; Part 2. Studies of duration effects in Norway, 1965-1971

The author describes an attempt to fit stochastic models to individual life histories. "In particular, [he] is concerned with the application of semi-Markov processes to the study of the timing of moves and duration of residence effects in the migration histories of Norwegian men over the period 1965-1971." In the second part of the article, the results of 11 studies using data on Norwegian men are presented     

On the determinants of data breaches: A cointegration analysis

Decisions in Economics and Finance - Cyber risks and particularly data breaches constitute one of the new frontiers of risk modeling for insurers across the world. We use the cointegration...     

A decomposition analysis of managerial efficiency for the insurance companies: A data envelopment analysis approach

The insurance industry worldwide has become less fragmented through liberalization reforms. Yet, following the transformational changes, there is little empirical evidence on identifying the determinants of managerial efficiency. This paper employs a truncated regression analysis to determine the factors driving managerial efficiency of Malaysian insurers. Overall and divisional efficiencies are derived using data envelopment analysis. The decomposition analysis reveals that the observed inefficiency is mainly caused by investment capability division. The regression findings reveal that determinants of efficiency have dissimilar impacts on overall and divisional efficiencies. This study broadly supports financial liberalization as a means of promoting managerial efficiency.     

浅析会计电算化工作中出现的问题及对策

会计电算化对我国企业的发展起到了极大的推动作用,但是随着会计电算化的飞速发展,实践工作中也出现了一些新的问题,阻碍了会计电算化向更深层次的发展,文章针对这些问题进行了阐述并提出相应的对策。     

Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods

As the penetration of solar energy generation into power systems keeps rising, intra-hour solar forecasting (IHSF) is becoming increasingly important for the secure and economical operation of a power system. One major difficulty in providing very accurate IHSF emanates from rapid cloud changes in the sky. The ground-based sky image (GSI) provides the intuitive information of intra-hour cloud changes and has thus been widely utilized in studies on IHSF. This paper presents a systematic review of the state-of-the-art of ground-based sky image-based intra-hour solar forecasting (GSI-IHSF). To our knowledge, we first propose a generic framework of GSI-IHSF consisting of four modules, i.e., sky image acquisition, sky image preprocessing, cloud forecasting, and solar forecasting. Then, as for each module, this paper introduces its core function, shows the major challenges, briefly reviews several extensively used techniques, summarizing research trends. Finally, this paper offers a prospect of GSI-IHSF research, discusses recent advances that demonstrate the potential for a great improvement in forecast accuracy, pointing out some new requirements and challenges that should be further investigated in the future.     

Estimating efficiencies from frontier models with panel data: A comparison of parametric,non-parametric and semi-parametric methods with bootstrapping

The aim of this article is first to review how the standard econometric methods for panel data may be adapted to the problem of estimating frontier models and (in)efficiencies. The aim is to clarify the difference between the fixed and random effect model and to stress the advantages of the latter. Then a semi-parametric method is proposed (using a non-parametric method as a first step), the message being that in order to estimate frontier models and (in)efficiences with panel data, it is an appealing method. Since analytic sampling distributions of efficiencies are not available, a bootstrap method is presented in this framework. This provides a tool allowing to assess the statistical significance of the obtained estimators. All the methods are illustrated in the problem of estimating the inefficiencies of 19 railway companies observed over a period of 14 years (1970–1983).Article presented at the ORSA/TIMS joint national meeting, Productivity and Global Competition, Philadelphia, October 29–31, 1990. An earlier version of the paper was presented at the European Workshop on Efficiency and Productivity Measurement in the Service Industries held at CORE, October 20–21, 1989. Helpful comments of Jacques Mairesse, Benoît Mulkay, Sergio Perelman, Michel Mouchart, Shawna Grosskopf and Rolf Färe, at various stages of the paper, are gratefully acknowledged.