Maximum modulus confidence bands

A family of confidence bands (simultaneous confidence regions) is given for EY = x′β that are piecewise-linear in x. Normality is assumed. These confidence bands are advocated over the usual hyperbolic band when the region of prime interest is distant from ${\overline{\bf x}}$ . In particular, this is the case when x?=?x(t) for time t and future time is of primary interest, that is for the prediction problem. For the case x′?=?(1, t), the family of bands includes that of Graybill and Bowden (J Am Stat Assoc 62:403–408, 1967).     

Beyond Absenteeism: Father Incarceration and Child Development

High rates of incarceration among American men, coupled with high rates of fatherhood among men in prison, have motivated recent research on the effects of parental imprisonment on children’s development. We use data from the Fragile Families and Child Wellbeing Study to examine the relationship between paternal incarceration and developmental outcomes for approximately 3,000 urban children. We estimate cross-sectional and longitudinal regression models that control not only for fathers’ basic demographic characteristics and a rich set of potential confounders, but also for several measures of pre-incarceration child development and family fixed effects. We find significant increases in aggressive behaviors and some evidence of increased attention problems among children whose fathers are incarcerated. The estimated effects of paternal incarceration are stronger than those of other forms of father absence, suggesting that children with incarcerated fathers may require specialized support from caretakers, teachers, and social service providers. The estimated effects are stronger for children who lived with their fathers prior to incarceration but are also significant for children of nonresident fathers, suggesting that incarceration places children at risk through family hardships including and beyond parent-child separation.     

Use of Risk Assessment Methods in the Certification of Decontaminated Buildings

Accidental events such as fires, explosions, and leaks often result in large-scale contaminations of buildings with toxic chemicals. After decontamination, the certification for original use requires testing for residual contamination. The two basic kinds of sampling plans in use up to recently both fall short of the required performance. Their deficiencies are analyzed in terms of the scientific questions implicit in both the sampling plan and the subsequent statistical evaluation. A sampling strategy of a new kind is proposed and discussed in the same context. It is motivated by concern for the long-term safety of the building's occupants and is, therefore, based on factors important in risk assessment. Three different sampling plans are derived in the framework of this methodology, two of which have already been used in actual certification proceedings.     

The accuracy and biases of diary communication data

A study to determine the accuracy and reliability of telephone communications data obtained via self-recording diaries was undertaken. The methodology involved comparing data obtained from the diaries to the more objective data provided by the recording capabilities of a PBX (Private branch Exchange). Two questions formed the basis for the analysis. First, what is the level of accuracy of diary data, and, second what biases are inherent in data obtained from self-recorded diaries. The findings indicate that diary data significantly understate the actual frequency of communications. There were also several biases inherent in the diary data. One involved a significant understatement of very short communications (i.e. those lasting less than 90 seconds). The others showed an under-recording of received calls and a likelihood to record internal rather than external cals. The conclusion drawn is that in the absence of objective data (i.e. data obtained from machine recording) diaries can provide usable data as long as one pays attention to the biases inherent in their use.     

Entrepreneurs in the rural environment

Change in rural activities is frequently seen as: (1) reaction to changes in other areas and sectors, and (2) negative. This downplays the role and importance of entrepreneurs, both farm and non-farm, in sustaining the vitality of rural areas. The notion of entrepreneur can be extended to entrepreneurial activity by other people, e.g. local government activity, which is an integral part of rural community economic development. Both the entrepreneur and the quasi-entrepreneur in local government are critical leaders in urban fringes and other rural areas alike. Their activity in an area is partly dependent upon the broader political, social and economic environment which influences: (1) the need to change and (2) whether any “benefit” can be derived from entrepreneurial activity. A framework is presented in this paper to place entrepreneurs and entrepreneurial activity into the context first, of decision-taking generally in the rural environment, and second, of the broader “enabling” environment. It is argued that constraints originating in this broader environment are often necessary, but they may have unforeseen side-effects in discouraging innovation. Changes in such constraints or in the manner in which they are implemented may be a necessary ingredient to maintain rural vitality through encouraging entrepreneurial activity.     

Measures of centrality for multivariate and directional distributions

Measures of centrality that generalize the univariate median are studied and applied to multivariate and directional distributions. A standard example is developed for general multivariate settings, and the uniqueness of the median proved for distributions satisfying certain regularity conditions. In the presence of weaker regularity, this median is shown to be of codimension 2. Conditions are also provided for these measures of centrality to be equivariant under transformations on the sample space. The equivariance of the usual univariate median under monotone transformations is seen as a special case.     

On functionals of random convex hulls

The completeness of the induced distribution of the convex hull of a random set of points drawn uniformly from a convex region seems not to have been noticed before. The result generalizes a well-known result for dimension one. As a consequence, there exists a theory of best unbiased estimation for certain functionals of the convex region. For example, a best estimator of the centroid of the convex region can be constructed. This estimator is distinct from the centroid of the convex hull. Therefore another generalization of a property holding in dimension one, namely the unbiased-ness of the centroid of the convex hull, is seen to fail.     

Shortest confidence and prediction intervals for the log-normal

We provide the shortest prediction interval for X, and the shortest confidence interval for the median of X, when X has the log-normal distribution for both the case σ², the variance of log X, known and unknown. Tables are given to assist the practitioner in constructing these intervals. A real-life example is provided to illustrate the results.     

Quantification of Variability and Uncertainty for Censored Data Sets and Application to Air Toxic Emission Factors

Many environmental data sets, such as for air toxic emission factors, contain several values reported only as below detection limit. Such data sets are referred to as "censored." Typical approaches to dealing with the censored data sets include replacing censored values with arbitrary values of zero, one-half of the detection limit, or the detection limit. Here, an approach to quantification of the variability and uncertainty of censored data sets is demonstrated. Empirical bootstrap simulation is used to simulate censored bootstrap samples from the original data. Maximum likelihood estimation (MLE) is used to fit parametric probability distributions to each bootstrap sample, thereby specifying alternative estimates of the unknown population distribution of the censored data sets. Sampling distributions for uncertainty in statistics such as the mean, median, and percentile are calculated. The robustness of the method was tested by application to different degrees of censoring, sample sizes, coefficients of variation, and numbers of detection limits. Lognormal, gamma, and Weibull distributions were evaluated. The reliability of using this method to estimate the mean is evaluated by averaging the best estimated means of 20 cases for small sample size of 20. The confidence intervals for distribution percentiles estimated with bootstrap/MLE method compared favorably to results obtained with the nonparametric Kaplan-Meier method. The bootstrap/MLE method is illustrated via an application to an empirical air toxic emission factor data set.     

Perceptions of organization development in South Korea: the use of a sensemaking approach

ABSTRACT

This qualitative study explores how employees engage in sensemaking during Organization Development (OD) initiatives in chaebols, that is, large family-owned firms in South Korea. In adopting a case study approach, semi-structured interviews were conducted with 37 respondents drawn from different levels of a chaebol to address three research questions. First, what key contextual factors are associated with employees’ sensemaking at different levels of an organization? Second, how do individuals at different levels of the organization make sense of an OD initiative through the ‘searching for plausibility’ property of sensemaking? Third, what contextual cues are influential when employees engage in ‘identity construction’ in sensemaking in response to an OD initiative? The findings and implications of the study demonstrate multiple subjective realities, which employees from different levels construct, indicating that the prevailing norms and practice within the existing culture, which have been influential in constructing the identities of employees should be identified when attempting to implement OD to change the organizational culture.