Nonparametric specification tests for conditional duration models

This paper deals with the testing of autoregressive conditional duration (ACD) models by gauging the distance between the parametric density and hazard rate functions implied by the duration process and their non-parametric estimates. We derive the asymptotic justification using the functional delta method for fixed and gamma kernels, and then investigate the finite-sample properties through Monte Carlo simulations. Although our tests display some size distortion, bootstrapping suffices to correct the size without compromising their excellent power. We show the practical usefulness of such testing procedures for the estimation of intraday volatility patterns.

Ecological carrying capacity for intensive tilapia (Oreochromis niloticus) cage aquaculture in a large hydroelectrical reservoir in Southeastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Small study effects in meta-analyses of osteoarthritis trials: meta-epidemiological study

Objective To examine the presence and extent of small study effects in clinical osteoarthritis research. Design Meta-epidemiological study. Data sources 13 meta-analyses including 153 randomised trials (41 605 patients) that compared therapeutic interventions with placebo or non-intervention control in patients with osteoarthritis of the hip or knee and used patients’ reported pain as an outcome. Methods We compared estimated benefits of treatment between large trials (at least 100 patients per arm) and small trials, explored funnel plots supplemented with lines of predicted effects and contours of significance, and used three approaches to estimate treatment effects: meta-analyses including all trials irrespective of sample size, meta-analyses restricted to large trials, and treatment effects predicted for large trials. Results On average, treatment effects were more beneficial in small than in large trials (difference in effect sizes −0.21, 95% confidence interval −0.34 to −0.08, P=0.001). Depending on criteria used, six to eight funnel plots indicated small study effects. In six of 13 meta-analyses, the overall pooled estimate suggested a clinically relevant, significant benefit of treatment, whereas analyses restricted to large trials and predicted effects in large trials yielded smaller non-significant estimates. Conclusions Small study effects can often distort results of meta-analyses. The influence of small trials on estimated treatment effects should be routinely assessed.

Mental Health Services for Nursing Home Residents: What Will It Cost?

The Nursing Home Reform Act of 1987 requires nursing homes to provide basic mental health services for all residents and to give active mental health treatment, a set of specialized mental health services, to those residents who are admitted with a serious mental illness. This article examines the potential size of the nursing home population who will require mental health services, its demographic composition, and the facilities in which these individuals reside using the Institutional Population Component of the National Medical Expenditure Survey. Estimates of the potential costs of providing monthly psychotherapy and pharmacological management to this population in nursing homes indicate that the mandate will have significant financial effects on nursing facilities. Conclusions about how the requirements for maintaining the mental and psychosocial well-being of nursing home residents may affect the future of nursing home care and mental health care are considered.

Benford's Law and Fraud Detection. Facts and Legends

Is Benford's law a good instrument to detect fraud in reports of statistical and scientific data? For a valid test the probability of "false positives" and "false negatives" has to be low. However, it is very doubtful whether the Benford distribution is an appropriate tool to discriminate between manipulated and non-manipulated estimates. Further research should focus more on the validity of the test and test results should be interpreted more carefully.

Continuation of Benchmark Project - Phase IV, 1999 Calendar Year, 2000

This is the final Report to the Iowa DOT Offices of Construction and the Highway Division for the calendar year 1999 research project entitled - Continuation of Benchmarking Project: Phase IV. This project continues efforts started in 1995 with the development of a performance measurement system. The performance measurements were used to identify areas that required improvement and process improvement teams (PITs) were launched to make recommendations for improvement. This report provides a brief historical background, documents Benchmark Steering Team Activities, describes measurement activities including the employee survey and collection of non-survey data. Then a retrospective of past PIT activities is given, which sets the stage for the substantial increase in PIT activity that occurred during the winter of 1998/9. Finally, the report closes with suggestions for future directions in Benchmarking Activity.

L'échantillonnage équilibré par la méthode du cube et la méthode rejective

Au cours de ces dernières années, les techniques d’échantillonnage équilibré ont connu un regain d’intérêt. En effet, ces techniques permettent de reproduire la structure de la population dans des échantillons afin d’améliorer l’efficacité des estimations. La reproduction de cette structure est effectuée par l’introduction des contraintes aux plans de sondage. Encore récemment, des nouvelles procédures d’échantillonnage équilibré ont été proposées. Il s’agit notamment de la méthode du cube présentée par Deville et Tillé (2004) et de l’algorithme réjectif de Fuller (2009). Alors que la première est une méthode exacte de sélection, la seconde est une approche approximative qui admet une certaine tolérance dans la sélection. Alors, après une brève présentation de ces deux méthodes dans le cadre d’un inventaire de pêcheurs, nous comparons à l’aide de simulations Monte Carlo, les plans de sondage produits par ces deux méthodes. Aussi, cela a été l’occasion pour nous de vérifier si ces méthodes modifient les probabilités de sélection des unités.

Effect on trend estimates of the difference between survey respondents and non-respondents: Results from 27 populations in the WHO MONIICA Project

Introduction: In the World Health Organization (WHO) MONICA (multinational MONItoring of trends and determinants in CArdiovascular disease) Project considerable effort was made to obtain basic data on non-respondents to community based surveys of cardiovascular risk factors. The first purpose of this paper is to examine differences in socio-economic and health profiles among respondents and non-respondents. The second purpose is to investigate the effect of non-response on estimates of trends. Methods:Socio-economic and health profile between respondents and non-respondents in the WHO MONICA Project final survey were compared. The potential effect of non-response on the trend estimates between the initial survey and final survey approximately ten years later was investigated using both MONICA data and hypothetical data. Results: In most of the populations, non-respondents were more likely to be single, less well educated, and had poorer lifestyles and health profiles than respondents. As an example of the consequences, temporal trends in prevalence of daily smokers are shown to be overestimated in most populations if they were based only on data from respondents. Conclusions: The socio-economic and health profiles of respondents and non-respondents differed fairly consistently across 27 populations. Hence, the estimators of population trends based on respondent data are likely to be biased. Declining response rates therefore pose a threat to the accuracy of estimates of risk factor trends in many countries.

Adjusting HIV Prevalence Estimates for Non-participation: an Application to Demographic Surveillance

Introduction: HIV testing is a cornerstone of efforts to combat the HIV epidemic, and testing conducted as part of surveillance provides invaluable data on the spread of infection and the effectiveness of campaigns to reduce the transmission of HIV. However, participation in HIV testing can be low, and if respondents systematically select not to be tested because they know or suspect they are HIV positive (and fear disclosure), standard approaches to deal with missing data will fail to remove selection bias. We implemented Heckman-type selection models, which can be used to adjust for missing data that are not missing at random, and established the extent of selection bias in a population-based HIV survey in an HIV hyperendemic community in rural South Africa.

Methods: We used data from a population-based HIV survey carried out in 2009 in rural KwaZulu-Natal, South Africa. In this survey, 5565 women (35%) and 2567 men (27%) provided blood for an HIV test. We accounted for missing data using interviewer identity as a selection variable which predicted consent to HIV testing but was unlikely to be independently associated with HIV status. Our approach involved using this selection variable to examine the HIV status of residents who would ordinarily refuse to test, except that they were allocated a persuasive interviewer. Our copula model allows for flexibility when modelling the dependence structure between HIV survey participation and HIV status.

Results: For women, our selection model generated an HIV prevalence estimate of 33% (95% CI 27–40) for all people eligible to consent to HIV testing in the survey. This estimate is higher than the estimate of 24% generated when only information from respondents who participated in testing is used in the analysis, and the estimate of 27% when imputation analysis is used to predict missing data on HIV status. For men, we found an HIV prevalence of 25% (95% CI 15–35) using the selection model, compared to 16% among those who participated in testing, and 18% estimated with imputation. We provide new confidence intervals that correct for the fact that the relationship between testing and HIV status is unknown and requires estimation.

Conclusions: We confirm the feasibility and value of adopting selection models to account for missing data in population-based HIV surveys and surveillance systems. Elements of survey design, such as interviewer identity, present the opportunity to adopt this approach in routine applications. Where non-participation is high, true confidence intervals are much wider than those generated by standard approaches to dealing with missing data suggest.

Non-ignorable loss to follow-up: correcting mortality estimates based on additional outcome ascertainment

Loss to follow-up (LTFU) is a common problem in many epidemiological studies. In antiretroviral treatment (ART) programs for patients with human immunodeficiency virus (HIV), mortality estimates can be biased if the LTFU mechanism is non-ignorable, that is, mortality differs between lost and retained patients. In this setting, routine procedures for handling missing data may lead to biased estimates. To appropriately deal with non-ignorable LTFU, explicit modeling of the missing data mechanism is needed. This can be based on additional outcome ascertainment for a sample of patients LTFU, for example, through linkage to national registries or through survey-based methods. In this paper, we demonstrate how this additional information can be used to construct estimators based on inverse probability weights (IPW) or multiple imputation. We use simulations to contrast the performance of the proposed estimators with methods widely used in HIV cohort research for dealing with missing data. The practical implications of our approach are illustrated using South African ART data, which are partially linkable to South African national vital registration data. Our results demonstrate that while IPWs and proper imputation procedures can be easily constructed from additional outcome ascertainment to obtain valid overall estimates, neglecting non-ignorable LTFU can result in substantial bias. We believe the proposed estimators are readily applicable to a growing number of studies where LTFU is appreciable, but additional outcome data are available through linkage or surveys of patients LTFU. Copyright © 2013 John Wiley & Sons, Ltd.

Communications materials on methods of development of revenue and cost estimates to non-technical audiences

This CDROM includes PDFs of presentations on the following topics: "TXDOT Revenue and Expenditure Trends;" "Examine Highway Fund Diversions, & Benchmark Texas Vehicle Registration Fees;" "Evaluation of the JACK Model;" "Future highway construction cost trends;" "Fuel Efficiency Trends and Revenue Impact"

Keeping our nursing and midwifery workforce : factors that support non-practising clinicians to return to practice

BACKGROUND: Within Australia and internationally (Health Workforce Australia, 2012) an increasing and on-going nursing workforce shortage is documented. Recent international estimates indicate that there will be ongoing and significant gaps in the supply of a nursing workforce; the United Kingdom is predicted to have a reduction of 12.12% nurses over the coming eight years if a current 'steady state' is maintained (Buchan and Seacombe, 2011); Canada is predicted to have a shortage of 60,000 nurses by 2022 (Tomblin et al., 2012) with Australia's anticipated nursing shortage reported as over 90,000 by the year 2025 (Health Workforce Australia, 2012). Queensland Health in response to their tracked emerging nursing and midwifery workforce shortages developed a nursing and midwifery refresher programme to return registered staff back to the workforce. A study was undertaken between 2008 and 2010 to provide an understanding of how non-practising nurses and midwives maybe supported back into the workforce. METHODS: Programme applicants (444) were invited to respond to an on-line survey designed to understand what aspects of the programme supported their learning and ability to return to the workforce. This number represents those who applied but not all completed or commenced the programme. Descriptive statistics (Polit and Beck, 2008) were used to collate quantifiable survey responses and free text and unsolicited responses were themed. RESULTS: The survey received a 35.5% response rate (n=158) with a return of 20% of unsolicited comments in the form of e-mail responses which were included in the themed results. Key themes supporting participants' learning and ability to return to the workforce were: Respondents were 94% female and 6% male, with 37.7% >51 years of age. Child rearing was the foremost reason for female staff relinquishing workforce roles (36.6%). The primary reason for returning to the workforce was maintenance of registration (40.5%). Both theory and clinical placement components were seen by participants as contributing to their confidence to return to the health workforce. CONCLUSION: The Queensland Nursing and Midwifery Refresher Programs provided a structured programme for registered, non-practising nurses and midwives to return to the Queensland Health workforce. Responses indicated that clinical supervision and contract learning should be central to a return to workforce induction programme for registered but non-practising nurses and midwives. The majority of nurses and midwives returning to the workforce were approaching retirement age in 10-15 years.

State Estimates of Employment Rates for Persons with Disabilities: Report Summary

Statistics on the states’ employment rates for persons with disabilities relative to their non-disabled peers may be of assistance to providers of employment services for persons with disabilities. Such information can help service providers, policy makers, and disability advocacy leaders to assess whether the employment rate of people with disabilities is improving over time, given policy, regulatory, and service intervention strategies. A recent report from the Cornell University Rehabilitation Research and Training Center (RRTC) for Economic Research on Employment Policy for Persons with Disabilities uses data from the March Current Population Survey to estimate employment rates for persons with and without a disability in the non-institutionalized working-age (aged 25 through 61) civilian population in the United States, and for each state and the District of Columbia for the years 1980 through 1998. The employment rate of persons with a disability relative to that of persons without disabilities are found to vary greatly across states. Over the last 20 years the relative employment rate of those with a disability dramatically declined overall and in most states.