SR visits: bringing electronic access to the census bureau library

The United States Census Bureau Library, acting on a study commissioned in 2002, has undertaken to improve electronic access for their patrons. The library provides e-journal and database access. The staff relies on usage statistics from these resources to sharpen the focus of the collection. Through an aggressive outreach program Census Bureau employees learn about these new products and services. Future plans include adding more e-journals, an open OPAC, and a new library building.     

Assessing efficacy in important subgroups in confirmatory trials: An example using Bayesian dynamic borrowing

Assessment of efficacy in important subgroups – such as those defined by sex, age, race and region – in confirmatory trials is typically performed using separate analysis of the specific subgroup. This ignores relevant information from the complementary subgroup. Bayesian dynamic borrowing uses an informative prior based on analysis of the complementary subgroup and a weak prior distribution centred on a mean of zero to construct a robust mixture prior. This combination of priors allows for dynamic borrowing of prior information; the analysis learns how much of the complementary subgroup prior information to borrow based on the consistency between the subgroup of interest and the complementary subgroup. A tipping point analysis can be carried out to identify how much prior weight needs to be placed on the complementary subgroup component of the robust mixture prior to establish efficacy in the subgroup of interest. An attractive feature of the tipping point analysis is that it enables the evidence from the source subgroup, the evidence from the target subgroup, and the combined evidence to be displayed alongside each other. This method is illustrated with an example trial in severe asthma where efficacy in the adolescent subgroup was assessed using a mixture prior combining an informative prior from the adult data in the same trial with a non-informative prior.     

What matters most? Different stakeholder perspectives on estimands for an invented case study in COPD

In drug development, we ask ourselves which population, endpoint and treatment comparison should be investigated. In this context, we also debate what matters most to the different stakeholders that are involved in clinical drug development, for example, patients, physicians, regulators and payers. With the publication of draft ICH E9 addendum on estimands in 2017, we now have a common framework and language to discuss such questions in an informed and transparent way. This has led to the estimand discussion being a key element in study development, including design, analysis and interpretation of a treatment effect. At an invited session at the 2018 PSI annual conference, PSI hosted a role‐play debate where the aim of the session was to mimic a regulatory and payer scientific advice discussion for a COPD drug. Including role‐play views from an industry sponsor, a patient, a regulator and a payer. This paper presents the invented COPD case‐study design and considerations relating to appropriate estimands are discussed by each of the stakeholders from their differing viewpoints with the additional inclusion of a technical (academic) perspective. The rationale for each perspective on approaches for handling intercurrent events is presented, with a key emphasis on the application of while‐on‐treatment and treatment policy estimands in this context. It is increasingly recognised that the treatment effect estimated by the treatment policy approach may not always be of primary clinical interest and may not appropriately communicate to patients the efficacy they can expect if they take the treatment as directed.     

Missing data sensitivity analysis for recurrent event data using controlled imputation

Statistical analyses of recurrent event data have typically been based on the missing at random assumption. One implication of this is that, if data are collected only when patients are on their randomized treatment, the resulting de jure estimator of treatment effect corresponds to the situation in which the patients adhere to this regime throughout the study. For confirmatory analysis of clinical trials, sensitivity analyses are required to investigate alternative de facto estimands that depart from this assumption. Recent publications have described the use of multiple imputation methods based on pattern mixture models for continuous outcomes, where imputation for the missing data for one treatment arm (e.g. the active arm) is based on the statistical behaviour of outcomes in another arm (e.g. the placebo arm). This has been referred to as controlled imputation or reference‐based imputation. In this paper, we use the negative multinomial distribution to apply this approach to analyses of recurrent events and other similar outcomes. The methods are illustrated by a trial in severe asthma where the primary endpoint was rate of exacerbations and the primary analysis was based on the negative binomial model. Copyright © 2014 John Wiley & Sons, Ltd.     

Use of generalized estimating equations in a trial in influenza to explore treatment effects over time

For trials with repeated measurements of outcome, analyses often focus on univariate outcomes, such as analysis of summary measures or of the last on‐treatment observation. Methods which model the whole data set provide a rich source of approaches to analysis. For continuous data, mixed‐effect modelling is increasingly used. For binary and categorical data, models based on use of generalized estimating equations account for intra‐subject correlation and allow exploration of the time course of response, as well as providing a useful way to account for missing data, when such data can be maintained as missing in the analysis. The utility of this approach is illustrated by an example from a trial in influenza. Copyright © 2004 John Wiley & Sons Ltd.     

Motivations for Involvement in Nonmetropolitan LGBTQ Organizations: A Multimethod Qualitative Exploration

Organizations serving lesbian, gay, bisexual, transgender, and queer (LGBTQ) communities provide services aimed at improving the health and well-being of LGBTQ people, yet may face limited resources and community support in nonmetropolitan communities. This study seeks to understand LGBTQ individuals’ motivations for becoming and staying involved in nonmetropolitan LGBTQ organizations. Data collection methods included interviews, participant observation, and focus groups. Six categories of motivations emerged: (1) to access support and resources; (2) to establish an LGBTQ community; (3) to be generative; (4) to affirm identity; (5) to support an LGBTQ organization; and (6) to combine one’s personal and professional lives.     

INSTITUTIONAL QUALITY AND TRADE: WHICH INSTITUTIONS? WHICH TRADE?

Using a panel of countries over 1990–2000, this paper examines the extent to which different dimensions of the institutional framework affect total exports, exports of manufactured goods, and exports of nonmanufactured goods. It is observed that exports of manufactured goods are positively affected by the quality of institutions but neither total exports nor nonmanufactured exports. The latter may even correlate negatively with the quality of institutions. The results are robust to estimation methods. ( JEL F14, F15, O17)     

Comparing Offers and Take‐ups of Employee Health Insurance across Race,Gender, and Decade*

How often do U.S. employees receive health insurance offers from employers? When offered, how often do they take up their employer‐based health insurance? This article uses the 1992 and 2002 waves of the National Study of the Changing Workforce (NSCW) to investigate changes in access to (offers) and employees electing to accept, take, or purchase their employers’ health insurance plans (take‐ups) among wage and salaried workers. Although much research has studied employee health benefits, little has examined the intersection of gender and race regarding both offers and take‐ups of such benefits. Logistic regression results indicate that offers and take‐ups of personal health benefits declined from 1992 to 2002, net of salient controls. Further analyses demonstrate that these declines did not affect all workers identically. Offers declined somewhat for both women and men among whites and African Americans, but declined more among Hispanic women and men. Among other ethnoracial groups, offers declined the most among men, but increased among comparable women. Take‐ups declined among white men and Hispanic workers. However, white and African American women's take‐ups did not change and among African American men take‐ups increased. We discuss the need to examine gender and race simultaneously and urge researchers to more closely examine changes in health benefit offers and take‐ups.     

Barriers to involvement in nonmetropolitan LGBTQ organizations

Lesbian, gay, bisexual, transgender, and queer (LGBTQ) organizations are spaces in which LGBTQ individuals can access support and community, yet they have received little empirical attention, particularly outside urban areas. Given the benefits of LGBTQ community involvement, this study examined the barriers to involvement in nonmetropolitan LGBTQ organizations. Three qualitative methods were employed: interviews, focus groups, and participant observation sessions. Thematic analyses identified eight barriers originating within the individual (managing one's LGBTQ identity, individual characteristics), organization (lack of diversity, group dynamics, lack of awareness of programs, workplace/school climate), and community (size, hostility). Implications for reducing barriers in nonmetropolitan LGBTQ organizations are discussed.     

Intent‐to‐treat analysis in the presence of off‐treatment or missing data

Intent‐to‐treat (ITT) analysis is viewed as the analysis of a clinical trial that provides the least bias, but difficult issues can arise. Common analysis methods such as mixed‐effects and proportional hazards models are usually labeled as ITT analysis, but in practice they can often be inconsistent with a strict interpretation of the ITT principle. In trials where effective medications are available to patients withdrawing from treatment, ITT analysis can mask important therapeutic effects of the intervention studied in the trial. Analysis of on‐treatment data may be subject to bias, but can address efficacy objectives when combined with careful review of the pattern of withdrawals across treatments particularly for those patients withdrawing due to lack of efficacy and adverse events. Copyright © 2010 John Wiley & Sons, Ltd.