A. John Bailer

Testing for the equality of area under the curves when using destructive measurement techniques

The area under a curve (AUC) of metabolite concentration or drug concentration over time has biological meaning in many situations, and the test of AUC equality among a set of different dosing regimens is often of interest. For the situation where the experimental unit must be sacrificed in order to obtain an estimate of the metabolite or drug concentration, it is noted that linear combinations of mean concentrations at time points for a particular dosing regimen can be used to estimate the AUC for that regimen. Contrasts among AUC estimates are readily constructed and tested within this derivation.

Comparing median lethal concentration values using confidence interval overlap or ratio tests

Experimenters in toxicology often compare the concentration-response relationship between two distinct populations using the median lethal concentration (LC50). This comparison is sometimes done by calculating the 95% confidence interval for the LC50 for each population, concluding that no significant difference exists if the two confidence intervals overlap. A more appropriate test compares the ratio of the LC50s to 1 or the log(LC50 ratio) to 0. In this ratio test, we conclude that no difference exists in LC50s if the confidence interval for the ratio of the LC50s contains 1 or the confidence interval for the log(LC50 ratio) contains 0. A Monte Carlo simulation study was conducted to compare the confidence interval overlap test to the ratio test. The confidence interval overlap test performs substantially below the nominal alpha = 0.05 level, closer to p = 0.005; therefore, it has considerably less power for detecting true differences compared to the ratio test. The ratio-based method exhibited better type I error rates and superior power properties in comparison to the confidence interval overlap test. Thus, a ratio-based statistical procedure is preferred to using simple overlap of two independently derived confidence intervals.

A Weight-of-Evidence Framework for Assessing Sediment (Or Other) Contamination: Improving Certainty in the Decision-Making Process

A basic framework is presented for the ecological weight-of-evidence (WOE) process for sediment assessment that clearly defines its essential elements and will improve the certainty of conclusions about whether or not impairment exists due to sediment contamination, and, if so, which stressors and biological species (or ecological responses) are of greatest concern. The essential “Certainty Elements” are addressed in a transparent best professional judgment (BPJ) process with multiple lines-of-evidence (LOE) ultimately quantitatively integrated (but not necessarily combined into a single value). The WOE Certainty Elements include: (1) Development of a conceptual model (showing linkages of critical receptors and ecosystem quality characteristics); (2) Explanation of linkages between measurement endpoint responses (direct and indirect with associated spatial/temporal dynamics) and conceptual model components; (3) Identification of possible natural and anthropogenic stressors with associated exposure dynamics; (4) Evaluation of appropriate and quantitatively based reference (background) comparison methods; (5) Consideration of advantages and limitations of quantification methods used to integrate LOE; (6) Consideration of advantages and limitations of each LOE used; (7) Evaluation of causality criteria used for each LOE during output verification and how they were implemented; and (8) Combining the LOE into a WOE matrix for interpretation, showing causality linkages in the conceptual model. The framework identifies several statistical approaches for integrating within LOE, the suitability of which depends on physical characteristics of the system and the scale/nature of impairment. The quantification approaches include: (1) Gradient (regression methods); (2) Paired reference/test (before/after control impact and ANOVA methods); (3) Multiple reference (ANOVA and multivariate methods); and 4) Gradient with reference (regression, ANOVA and multivariate methods). This WOE framework can be used for any environmental assessment and is most effective when incorporated into the initial and final study design stages (e.g., the Problem Formulation and Risk Characterization stages of a risk assessment) with reassessment throughout the project and decision-making process, rather than in a retrospective data analysis approach where key certainty elements cannot be adequately addressed.

Fatal occupational injury rates in southern and non-southern states, by race and Hispanic ethnicity

OBJECTIVES We investigated fatal occupational injury rates in the United States by race and Hispanic ethnicity during the period 1990-1996. METHODS Fatalities were identified by means of the national traumatic occupational fatalities surveillance system. Fatal occupational injury rates were calculated by race/ethnicity and region using US-census-based workforce estimates. RESULTS Non-Hispanic Black men in the South had the highest fatal occupational injury rate (8.5 per 100000 worker-years), followed by Hispanic men in the South (7.9 per 100000 worker-years). Fatal injury rates for Hispanic men increased over the study period, exceeding rates for non-Hispanic Black men in the latter years of observation. CONCLUSIONS These data suggest a change in the demographics of fatal occupational injuries in the United States. Hispanic men in the South appear to be emerging as the group with the nations highest unintentional fatal occupational injury rate.

Comparing model averaging with other model selection strategies for benchmark dose estimation

Model averaging (MA) has been proposed as a method of accommodating model uncertainty when estimating risk. Although the use of MA is inherently appealing, little is known about its performance using general modeling conditions. We investigate the use of MA for estimating excess risk using a Monte Carlo simulation. Dichotomous response data are simulated under various assumed underlying dose–response curves, and nine dose–response models (from the USEPA Benchmark dose model suite) are fit to obtain both model specific and MA risk estimates. The benchmark dose estimates (BMDs) from the MA method, as well as estimates from other commonly selected models, e.g., best fitting model or the model resulting in the smallest BMD, are compared to the true benchmark dose value to better understand both bias and coverage behavior in the estimation procedure. The MA method has a small bias when estimating the BMD that is similar to the bias of BMD estimates derived from the assumed model. Further, when a broader range of models are included in the family of models considered in the MA process, the lower bound estimate provided coverage close to the nominal level, which is superior to the other strategies considered. This approach provides an alternative method for risk managers to estimate risk while incorporating model uncertainty.

Risk Factors of Falls in Community-Dwelling Older Adults: Logistic Regression Tree Analysis

PURPOSE OF THE STUDY A novel logistic regression tree-based method was applied to identify fall risk factors and possible interaction effects of those risk factors. DESIGN AND METHODS A nationally representative sample of American older adults aged 65 years and older (N = 9,592) in the Health and Retirement Study 2004 and 2006 modules was used. Logistic Tree with Unbiased Selection, a computer algorithm for tree-based modeling, recursively split the entire group in the data set into mutually exclusive subgroups and fit a logistic regression model in each subgroup to generate an easily interpreted tree diagram. RESULTS A subgroup of older adults with a fall history and either no activities of daily living (ADL) limitation and at least one instrumental activity of daily living or at least one ADL limitation was classified as at high risk of falling. Additionally, within each identified subgroup, the best predictor of falls varied over subgroups and was also evaluated. IMPLICATIONS Application of tree-based methods may provide useful information for intervention program design and resource allocation planning targeting subpopulations of older adults at risk of falls.

Differential survivorship among allozyme genotypes of Hyalella azteca exposed to cadmium, zinc or low pH.

The survival functions (SF) during acute exposures to cadmium, zinc or low pH were examined for amphipods exhibiting variation at three loci. Significant differences were observed in eight of nine locus/toxicant combinations. Two general types of survival curve patterns were identified when genotype-related SF differences were observed. In the first pattern, the survival differences between genotypes were immediately apparent with two SF curves separated at the beginning of exposure with little or no overlap. For the second pattern, both genotypes had similar SF for a period of time, during which the two survival curves crossed or overlapped. After this period, the survival probability of one genotype dropped sharply relative to the other. While SF was related to genotype, it was not related to heterozygosity. Genetic distance analysis showed that exposure to cadmium, zinc or low pH each resulted in directional selection, suggesting the potential use of genetic distance as a bioindicator.

Baseline characteristics and statistical implications for the OECD 210 fish early‐life stage chronic toxicity test

The fish toxicity assay most commonly used to establish chronic effects is the Organisation for Economic Co-operation and Development (OECD) 210, fish early-life stage test. However, the authors are not aware of any systematic analysis of the experimental design or statistical characteristics of the test since the test guideline was adopted nearly 20 years ago. Here, the authors report the results of an analysis of data compiled from OECD 210 tests conducted by industry labs. The distribution of responses observed in control treatments was analyzed, with the goal of understanding the implication of this variability on the sensitivity of the OECD 210 test guideline and providing recommendations on revised experimental design requirements of the test. Studies were confined to fathead minnows, rainbow trout, and zebrafish. Dichotomous endpoints (hatching success and posthatch survival) were examined for indications of overdispersion to evaluate whether significant chamber-to-chamber variability was present. Dichotomous and continuous (length, wet wt, dry wt) measurement endpoints were analyzed to determine minimum sample size requirements to detect differences from control responses with specified power. Results of the analysis indicated that sensitivity of the test could be improved by maximizing the number of replicate chambers per treatment concentration, increasing the acceptable level of control hatching success and larval survival compared to current levels, using wet weight measurements rather than dry weight, and focusing test efforts on species that demonstrate less variability in outcome measures. From these analyses, the authors provide evidence of the impact of expected levels of variability on the sensitivity of traditional OECD 210 studies and the implications for defining a target for future animal alternative methods for chronic toxicity testing in fish.

Impact of Exchanges and Client–Therapist Alliance in Online-Text Psychotherapy

The impact of exchanges and client-therapist alliance of online therapy text exchanges were compared to previously published results in face-to-face therapy, and the moderating effects of four participant factors found significant in previously published face-to-face studies were investigated using statistical mixed-effect modeling analytic techniques. Therapists (N=30) and clients (N=30) engaged in online therapy were recruited from private practitioner sites, e-clinics, online counseling centers, and mental-health-related discussion boards. In a naturalistic design, they each visited an online site weekly and completed the standard impact and alliance questionnaires for at least 6 weeks. Results indicated that the impact of exchanges and client-therapist alliance in text therapy was similar to, but in some respects more positive than, previous evaluations of face-to-face therapy. The significance of participant factors previously found to influence impact and alliance in face-to-face therapy (client symptom severity, social support, therapist theoretical orientation, and therapist experience) was not replicated, except that therapists with the more symptomatic clients rated their text exchanges as less smooth and comfortable. Although its small size and naturalistic design impose limitations on sensitivity and generalizability, this study provides some insights into treatment impact and the alliance in online therapy.

Risk assessment--the mother of all uncertainties. Disciplinary perspectives on uncertainty in risk assessment.

Abstract: Uncertainty in the detection and evaluation of chemical hazards to health leads to challenges when conducting risk assessments. Some of the uncertainty has to do with data, some with incomplete understanding of processes, and some with the most fundamental ways of viewing the questions. True variability‐across space, in time, or among individuals‐complicates the search for understanding many important aspects of risk. A few statistical and toxicologic tools are available to assess uncertainty. Three methods of classifying uncertainty are briefly discussed. In addition, our disciplinary background may influence how we view and discuss variability and uncertainty. We rarely know as much as we think we do (and not just in risk assessment). Great uncertainty is likely to remain an important part of risk assessment for some decades to come.