Regression calibration for logistic regression with multiple surrogates for one exposure

Methods have been developed by several authors to address the problem of bias in regression coefficients due to errors in exposure measurement. These approaches typically assume that there is one surrogate for each exposure. Occupational exposures are quite complex and are often described by characteristics of the workplace and the amount of time that one has worked in a particular area. In this setting, there are several surrogates which are used to define an individual's exposure. To analyze this type of data, regression calibration methodology is extended to adjust the estimates of exposure-response associations for the bias and additional uncertainty due to exposure measurement error from multiple surrogates. The health outcome is assumed to be binary and related to the quantitative measure of exposure by a logistic link function. The model for the conditional mean of the quantitative exposure measurement in relation to job characteristics is assumed to be linear. This approach is applied to a cross-sectional epidemiologic study of lung function in relation to metal working fluid exposure and the corresponding exposure assessment study with quantitative measurements from personal monitors. A simulation study investigates the performance of the proposed estimator for various values of the baseline prevalence of disease, exposure effect and measurement error variance. The efficiency of the proposed estimator relative to the one proposed by Carroll et al. [1995. Measurement Error in Nonlinear Models. Chapman & Hall, New York] is evaluated numerically for the motivating example. User-friendly and fully documented Splus and SAS routines implementing these methods are available (http://www.hsph.harvard.edu/faculty/spiegelman/multsurr.html).     

SWAPCO Nuclear Corporation (SWAPCO)

SWAPCO is a nuclear fuel brokerage company which has managed to survive in a highly competitive niche market for fourteen years. The market is currently declining and the company must develop a strategy for survival and future growth. The case is designed to enable students to think about the effects of a rapidly changing market on a company's business and the effect of changes in the external environment on the company. It leads to discussion of market strategies, the role of government in business, the effects of competition and other external factors in the survival and growth of a business. This revised version was published online in July 2006 with corrections to the Cover Date.     

High Production Volume Chemical Amine Oxides [C8–C20] Category Environmental Risk Assessment

An environmental assessment of amine oxides has been conducted under the OECD SIDS High Production Volume (HPV) Program via the Global International Council of Chemical Associations (ICCA) Amine Oxides Consortium. Amine oxides are primarily used in conjunction with surfactants in cleaning and personal care products. Given the lack of persistence or bioaccumulation, and the low likelihood of these chemicals partitioning to soil, the focus of the environmental assessment is on the aquatic environment. In the United States, the E-FAST model is used to estimate effluent concentrations in the United States from manufacturing facilities and from municipal facilities resulting from consumer product uses. Reasonable worst-case ratios of predicted environmental concentration (PEC) to predicted no effect concentration (PNEC) range from 0.04 to 0.003, demonstrating that these chemicals are a low risk to the environment.     

Joe's First Bank

Joe Spoke has had a highly successful career in banking. Joe will leave his present job as CEO of a county region of a bank chain within 60 days because of disagreements with his new boss. The case explores several career options for Joe. One option is to take a job as one of three executive vice presidents of a local bank. A second option is to take a job that will involve relocation. A third option is to start a new bank in his county. The case explores the option of starting a new bank in detail. Projected financial statements are included for analysis by the students. This revised version was published online in July 2006 with corrections to the Cover Date.     

Resignation or Dismissal?: When a CEO and a President Clash

In the executive director's opinion, Bluehills Family Services' board of directors had serious problems with their organizational governance. These difficulties came to a head in an apparently unresolvable clash between the executive director and the board president. Given the preexisting board and organization perceptions, could an emergency board meeting produce a positive outcome, and would the executive director's participation be counterproductive?     

Use of an ISO 14000 Option in Implementing EPA's Rule on Risk Management Programs for Chemical Accidental Release Prevention

EPA's rule of Risk Management Programs for Chemical Accidental Release Prevention applies to facilities that manufacture, process, use, store, or otherwise handle regulated substances at or above specified threshold quantities. EPA estimates that approximately 66,000 facilities nationwide will be regulated under the rule. This paper examines the use of a structured ISO 14000 mechanism as option-regulated facilities could elect for implementation of the rule. Under the ISO 14000 option, facilities would commit to additional obligations regarding information disclosure, discussions with potentially affected publics, and timely correction of deficiencies noted in annual ISO 14000 audits of their compliance with the Risk Management Program they submit to the EPA under the rule. In return, facilities would be granted significant relief in regard to both EPA audit frequency and the penalties that might be applied for any items of noncompliance with the rule noted during the course of implementing agency reviews of the facility. The paper concludes with a discussion of the advantages and disadvantages of this option to potentially affected stakeholders.     

The Ties that Bind: Social Networks, Person-Organization Value Fit, and Turnover Intention

This article examines the influence of social networks and valuecongruence on turnover intention among public and nonprofitemployees. We argue that employees exist in social networksinside and outside their organization, and these networks shapeemployee attitudes and behavior. To illustrate this theory,we use turnover intention. A strong and positive intraorganizationalsocial network characterized by good relations with and a senseof obligation toward other staff is hypothesized to make itmore likely that employees will stay. A strong social networkexternal to the organization is hypothesized to increase theopportunities that employees have to leave. Our findings offerstrong support for the role of intraorganizational networks,but relatively weak support for the effect of external networks.We also propose that person-organization (P-O) fit shape turnoverintention. Our results suggest that employees who experiencea strong P-O fit in terms of value congruence are more likelyto offer a long-term commitment.     

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.     

Tree-structured analysis of treatment effects with large observational data

Treatment effect in an observational study of relatively large scale can be described as a mixture of effects among subgroups. In particular, analysis for estimating the treatment effect at the level of an entire sample potentially involves not only differential effects across subgroups of the entire study cohort, but also differential propensities – probabilities of receiving treatment given study subjects’ pretreatment history. Such complex heterogeneity is of great research interest because the analysis of treatment effects can substantially depend on the hidden data structure for effect sizes and propensities. To uncover the unseen data structure, we propose a likelihood-based regression tree method which we call marginal tree (MT). The MT method is aimed at a simultaneous assessment of differential effects and propensity scores so that both become homogeneous within each terminal node of the resultant tree structure. We assess simulation performances of the MT method by comparing it with other existing tree methods and illustrate its use with a simulated data set, where the objective is to assess the effects of dieting behavior on its subsequent emotional distress among adolescent girls.