The effect of omitted covariates in marginal and partially conditional recurrent event analyses

There have been many advances in statistical methodology for the analysis of recurrent event data in recent years. Multiplicative semiparametric rate-based models are widely used in clinical trials, as are more general partially conditional rate-based models involving event-based stratification. The partially conditional model provides protection against extra-Poisson variation as well as event-dependent censoring, but conditioning on outcomes post-randomization can induce confounding and compromise causal inference. The purpose of this article is to examine the consequences of model misspecification in semiparametric marginal and partially conditional rate-based analysis through omission of prognostic variables. We do so using estimating function theory and empirical studies.

     

Rural Appalachian High School Students’ College‐Going and STEMM Perceptions

The authors examined perceptions of key social cognitive career theory (Lent, Brown, & Hackett, 1994) variables related to college‐going and science, technology, engineering, math, and medical (STEMM) careers in 10th and 11th graders (N = 892) attending 3 rural Appalachian high schools. The authors examined differences in perceptions related to gender, prospective 1st‐generation college student status, and the presence or absence of aspirations to pursue a STEMM career. Young women and young men scored similarly on all but 1 dependent variable, college‐going self‐efficacy (young women scored higher). Students who had STEMM career aspirations had higher scores on every measure than those who did not. Results suggest examining a 3rd prospective 1st‐generation college student status group—students who are unsure of their parents’ education level—as a distinct group in future research. By examining the college‐going and STEMM attitudes of rural Appalachian high school students, this study advances the literature and informs practitioners on reducing educational and vocational inequalities in this region.     

What shapes plant and animal diversity on urban golf courses?

Recent concern over increasing loss of biodiversity has prompted considerable interest in the role of urban green spaces as reservoirs of local biodiversity. This study assessed the diversity of three indicator taxa - plants, ants and birds - on golf courses spanning a wide range of environmental variation in terms of climate, elevation, course age, size and connectivity to native woodland. Species richness and community composition was further compared between contrasting on-course habitat types that reflect different management intensities. We identified a set of taxon-specific environmental correlates indicating an intricate interplay of landscape- and local-scale variables that affect local species diversity. Our results show that floristic diversity is positively associated with the amount of rainfall, whereas ant and bird diversity are related to local-scale factors, particularly the number of trees and the size of water features on a site. The amount of on-course native habitat was a strong predictor of plant and ant diversity and was also associated with the number of unique species at the site level; this reinforces the value of remnant habitat patches as local biodiversity reservoirs that represent mini hot-spots in an otherwise species-poor urban landscape. Community composition for all three taxa differed markedly between non-playing and playing areas, with boundary and remnant habitats generally having more diverse, species-rich communities. Our results suggest that local floral and faunal biodiversity on urban golf courses can be enhanced by creating woody non-playing areas and, especially, by preserving, restoring or expanding remnant habitats.     

A Content Analysis of Intake Paperwork: An Exploration of How Clinicians Ask About Gender,Sex, and Sexual/Affectual Orientation

In the United States, the transgender and gender nonconforming (TGNC) population has increased twofold since 2011. Although counseling professionals are called to provide competent services to TGNC clients, no empirical studies exist that examine one of the first points of contact: Intake paperwork. The authors conducted a content analysis (N = 128) of intake paperwork and assessed how and if clinicians asked for gender, sex, and sexual/affectual orientation, and whether they conflated these constructs. Findings indicate adjustments need to be made for intakes to be more inclusive of these constructs. The authors offer clinical implications and avenues for future research.     

Using relative utility curves to evaluate risk prediction

Summary.  Because many medical decisions are based on risk prediction models that are constructed from medical history and results of tests, the evaluation of these prediction models is important. This paper makes five contributions to this evaluation: the relative utility curve which gauges the potential for better prediction in terms of utilities, without the need for a reference level for one utility, while providing a sensitivity analysis for misspecification of utilities, the relevant region, which is the set of values of prediction performance that are consistent with the recommended treatment status in the absence of prediction, the test threshold, which is the minimum number of tests that would be traded for a true positive prediction in order for the expected utility to be non-negative, the evaluation of two-stage predictions that reduce test costs and connections between various measures of performance of prediction. An application involving the risk of cardiovascular disease is discussed.     

Bayesian autoregressive spectral analysis

The article describes an operational Bayesian approach to making inferences for the spectral density function for univariate autoregressive processes and for the AR operator of multivariate autoregressive processes. The derivation of the approach is described. Numerical examples, including the Wolfer Sunspot numbers, are used to demonstrate the practical usefulness of the approach.     

Urban forest cover of the Chicago region and its relation to household density and income

Urban forests and herbaceous open space play a vital role in the environmental and aesthetic health of cities, yet they are rarely identified in land-use inventories of urban areas. To provide information on urban forests and other vegetative land cover in Illinois cities, Landsat Thematic Mapper (TM) data from June 27, 1988, were classified for the Chicago metropolitan region (9,717 km²). Ten land-cover classes were identified, including two types of forestland (occupying 5.8% of the total area), residential land with trees (14.6%) or without trees (7.8%), cropland (37.5%), two types of grassland (7.7%), urban with impervious surfaces (23.1%), water (1.6%), and miscellaneous vegetation (2.1%). Correlation analyses indicated that household income and household density are strongly related to land covers in the region, particularly those with tree cover and urbanized land. Population changes for 1980–1985 and 1985–2010 (projected) show a pattern of increasing density in the urbanized zone concurrent with continued urban sprawl, primarily into current cropland.     

Quality circle failures in UK manufacturing companies—A study. Part II

This paper presents five case studies of quality circle failures which provide a detailed picture of some of the reasons behind quality circle failures as identified in Part 1 of this study. The results also indicate that it will be easier to implement quality circles if a business is in a stable phase and the probability of success and survival will be higher. However, there is no absolutely right time to introduce quality circles and a company facing severe economic difficulties may be able to achieve a successful programme, but in such cases survival will ultimately depend on maintaining trade union support. It is pointed out that quality circle programmes are able to withstand a high failure rate of individual circles yet still be very successful.     

Evaluating the administrative efficiency of courts

In addition to being held accountable for judicial decision, courts, like other public agencies, can and should be evaluated in terms of their administrative efficiency. This paper illustrates how courts can be evaluated in terms of their relative administrative efficiency, using a new approach—data envelopment analysis (DEA)—first proposed by Charnes et al. [1]. The DEA is based upon the economic notion of Pareto optimality which states that a given decision making unit (DMU) is inefficient if some other DMU, or some combination of other DMUs, can produce at least the same amounts of all outputs with less of some resource input and not more of any other resource. Conversely a DMU is said to be efficient if the above is not possible. Charnes et al. [1] generalized the usual input/output ratio measure of efficiency for a given unit in terms of a fractional linear program with fractional constraints. In the case of courts, the efficiency of any particular court is calculated by forming the ratio of a weighted sum of outputs to a weighted sum of inputs, where the weights for both outputs and inputs are to be selected in a manner that calculates the Pareto-Koopmans efficiency of the court. This paper reviews the DEA method and illustrates its application to a data base for 100 criminal superior courts in North Carolina.