Estimation and Inference in Two-Step Econometric Models

A commonly used procedure in a wide class of empirical applications is to impute unobserved regressors, such as expectations, from an auxiliary econometric model. This two-step (T-S) procedure fails to account for the fact that imputed regressors are measured with sampling error, so hypothesis tests based on the estimated covariance matrix of the second-step estimator are biased, even in large samples. We present a simple yet general method of calculating asymptotically correct standard errors in T-S models. The procedure may be applied even when joint estimation methods, such as full information maximum likelihood, are inappropriate or computationally infeasible. We present two examples from recent empirical literature in which these corrections have a major impact on hypothesis testing.     

Random vs. systematic non-response in group-level research

This study investigates whether, in the context of group-level research, the effect of random non-response pattern, in biasing group-level scores, would be more salient than the effect of systematic non-response pattern with all other factors (i.e. group size, within-group variability, between-group variability and response rate) held constant. The findings of the Monte Carlo simulation study are counter-intuitive and reveal that the amount of error in the group-level variable is indeed the largest under the conditions of random non-response pattern.     

Viewpoint: observations on scaled average bioequivalence

The two one-sided test procedure (TOST) has been used for average bioequivalence testing since 1992 and is required when marketing new formulations of an approved drug. TOST is known to require comparatively large numbers of subjects to demonstrate bioequivalence for highly variable drugs, defined as those drugs having intra-subject coefficients of variation greater than 30%. However, TOST has been shown to protect public health when multiple generic formulations enter the marketplace following patent expiration. Recently, scaled average bioequivalence (SABE) has been proposed as an alternative statistical analysis procedure for such products by multiple regulatory agencies. SABE testing requires that a three-period partial replicate cross-over or full replicate cross-over design be used. Following a brief summary of SABE analysis methods applied to existing data, we will consider three statistical ramifications of the proposed additional decision rules and the potential impact of implementation of scaled average bioequivalence in the marketplace using simulation. It is found that a constraint being applied is biased, that bias may also result from the common problem of missing data and that the SABE methods allow for much greater changes in exposure when generic-generic switching occurs in the marketplace.     

Planning for an adaptive design: a case study in COPD

We discuss the practical and clinical considerations encountered when planning a Phase IIa trial in chronic obstructive pulmonary disease (COPD). Various adaptive strategies for reducing the cost of the trial and the statistical implications of these are explored. Use of the EAST software to evaluate the properties of the study designs with one or more interim analyses for futility, efficacy or either is described. We emphasize the rationale for choosing between alternative designs and the relationship between the clinical and statistical considerations.     

A Decade of Microaggression Research and LGBTQ Communities: An Introduction to the Special Issue

ABSTRACT

Though the Supreme Court of the U.S. legalized same-sex marriage in 2015, heterosexism and transphobia has continued to manifest through many systems in the US — from lack of federal protection in employment non-discrimination laws to polices that prohibit transgender people from using bathroom and public facilities that match their gender identities. Heterosexist and transphobic discrimination have also persisted through interpersonal interactions — ranging from more overt forms (e.g., hate crimes, bullying) to more subtle forms of discrimination, otherwise known as microaggressions. Since 2008, there have been hundreds of articles written on microaggressions, with dozens focusing specifically on experiences of lesbian, gay, bisexual, transgender, and queer (LGBTQ) people. Qualitative and quantitative studies have revealed that LGBTQ people who experience microaggressions have reported negative outcomes like depression, low self-esteem, and trauma. This special issue aims to further Microaggression Theory by providing theoretical and empirical papers that focus on the manifestation and impact of microaggressions on LGBTQ people. Using an interdisciplinary approach, articles range in topic from intersectional identities, to health and psychological outcomes, to advancing research methods. Future studies regarding microaggressions and LGBTQ people are discussed- highlighting the influence of the changing landscape of heterosexism and transphobia within general society, as well as new dynamics that have formed and developed within LGBTQ communities.     

Implementing Consumer Choice in Long‐term Care: The Impact of Individual Budgets on Social Care Providers in England

In common with many advanced welfare states, England has increasingly relied on consumerist principles to deliver both greater quality and improved efficiency in the long‐term care system. The Individual Budget (IB) pilots marked the next step in this process, through a new system of funding whereby greater control of resources is given to service users, in lieu of direct in‐kind care provision. IBs have the potential to transform the market for care services as well as the relationships between key stakeholders within it. Purchasing will increasingly be shaped by the demands of IB holders, with providers expected to deliver a wider range of personalized services. What will this mean for providers, and what can they do to prepare for these changes? These questions are relevant not just in England but in many other countries adopting similar mechanisms for devolving control over the design, delivery and funding of care to the end‐user. The article explores the early impact of IBs on providers' services, on their workforces, and on the administrative implications for providers of managing IBs. The study finds that providers were positive about the opportunities for better‐quality services that IBs can bring about. However, participants highlighted a number of obstacles to their effectiveness, and reported a range of potentially adverse administrative and workforce consequences which have the potential to jeopardize the consumerist policy objectives of increased choice and efficiency.