Cohpasisons of improved bonferroni and sidak/slepian bounds with applications to normal markov processes

The recent literature contains theorems improving on both the standard Bonferroni inequality (Hoover (1990)) and the Sidak/Slepian inequalities (Glaz and Johnson (1984)), The application of these improved theorems to upper bounds for non coverage of simultaneous confidence intervals on multivariate normal variables is explored. The improved Bonferroni upper bounds always hold, while improved Sidak/Slepian bounds only apply to special cases. It is shown that improved Sidak/Slepian bounds will always hold for Normal Markov Processes, a commonly occuring and easily identifiable class of multivariate normal variables. The improved Sidak/Slepian upper bound, if it applies, is proven to be superior to the computationally equivalent improved Bonferroni bound. This improvement, however, is not great when both methods are used to determine upper bounds for Type I error in the range of .01 to .10.     

Projecting From Advance Data Using Propensity Modeling: An Application to Income and Tax Statistics

This article proposes and evaluates two new methods of reweighting preliminary data to obtain estimates more closely approximating those derived from the final data set. In our motivating example, the preliminary data are an early sample of tax returns, and the final data set is the sample after all tax returns have been processed. The new methods estimate a predicted propensity for late filing for each return in the advance sample and then poststratify based on these propensity scores. Using advance and complete sample data for 1982, we demonstrate that the new methods produce advance estimates generally much closer to the final estimates than those derived from the current advance estimation techniques. The results demonstrate the value of propensity modeling, a general-purpose methodology that can be applied to a wide range of problems, including adjustment for unit nonresponse and frame undercoverage as well as statistical matching.     

Alternative Approximations to Value-At-Risk: A Comparison

This article compares three value-at-risk (VaR) approximation methods suggested in the literature: Cornish and Fisher (1937 Cornish, E.A., Fisher, R.A. (1937). Moments and cumulants in the specification of distributions. Revue de l’Institut International de Statistique 5:307–320.[Crossref] , [Google Scholar]), Sillitto (1969 Sillitto, G.P. (1969). Derivation of approximants to the inverse distribution function of a continuous univariate population from the order statistics of a sample. Biometrika 56:641–650.[Crossref], [Web of Science ®] , [Google Scholar]), and Liu (2010 Liu, W.-H. (2010). Estimation and testing of portfolio value-at-risk based on L-comoment matrices. Journal of Futures Markets 30:897–908.[Crossref], [Web of Science ®] , [Google Scholar]). Simulation results are obtained for three families of distributions: student-t, skewed-normal, and skewed-t. We recommend the Sillitto approximation as the best method to evaluate the VaR when the financial return has an unknown, skewed, and heavy-tailed distribution.     

Deriving the Normal and Exponential Densities Using EDA Techniques

This paper shows how students in an introductory statistics course discover mathematical expressions for the normal and exponential density functions. Techniques of exploratory data analysis (EDA) are applied to large data sets, the key idea being a straight-line fit to an appropriate reexpression of the histogram.     

Additional results for 'Sequential design approaches for bioequivalence studies with crossover designs'

In 2008, this group published a paper on approaches for two‐stage crossover bioequivalence (BE) studies that allowed for the reestimation of the second‐stage sample size based on the variance estimated from the first‐stage results. The sequential methods considered used an assumed GMR of 0.95 as part of the method for determining power and sample size. This note adds results for an assumed GMR = 0.90. Two of the methods recommended for GMR = 0.95 in the earlier paper have some unacceptable increases in Type I error rate when the GMR is changed to 0.90. If a sponsor wants to assume 0.90 for the GMR, Method D is recommended. Copyright © 2011 John Wiley & Sons, Ltd.     

Trust: Missing Piece(s) in the Safety Puzzle

While trust is increasingly recognized as a factor that impacts on safety behavior, the exact nature of trust and its role in shaping organizational safety is poorly understood. This special issue contains six articles that examine the relationship between trust and safety behavior in a range of high-risk work contexts. The issue begins with two articles that introduce the complex nature of trust and the positive and negative roles that trust can play in shaping an organization's safety culture. This background is then developed by two articles that explore the role of trust and distrust in safety performance, and uncover a range of significant but often counterintuitive relationships between forms of trust and safe behavior. Finally, the issue concludes with two articles that examine the role that leadership may play in developing trust. These articles examine the conditions important for the development of trust in leaders, and the trust-promoting actions that leaders can employ to influence employees' engagement in safety participation.     

Authorizing processes changing team autonomy during new product development

One basic feature of recent collaborative team arrangements for organizing new product development is a high degree of autonomy for cross-functional teams. The literature, however, has not provided a very precise analysis of team autonomy in the context of new product development. The theoretical framework advanced here, based on the literature and the authors' case studies, assumes that developing a large and technologically sophisticated new product requires a hierarchy of collaborating teams. In this complex organizational context, managers do not completely predetermine any one team's autonomy. During the course of a new product development program, certain authorizing (deauthorizing) processes produce ad hoc changes in autonomy. This paper identifies specific authorizing processes and hypothesizes about variables that should affect them. The propositions also lead to some managerial implications for preserving team autonomy.     

THE IMPACT OF R&D INVESTMENT ON PRODUCTIVITY–NEW EVIDENCE USING LINKED R&D–LRD DATA

This paper uses confidential Census longitudinal microdata to examine the association between R&D and productivity for the period 1972–1985. These data allow for significant improvements in measurement and model specification, yielding more precise estimates of the returns to R&D. Our results confirm the findings of existing studies: 1) positive returns to R&D investment 2) higher returns to company-financed research 3) a productivity "premium" on basic research These results are robust to adjustments for "influential outliers." Also, our evidence suggests that the return to company-financed R&D is an increasing function of firm size.