A statistician's perspective on biomarkers in drug development

Biomarkers play an increasingly important role in many aspects of pharmaceutical discovery and development, including personalized medicine and the assessment of safety data, with heavy reliance being placed on their delivery. Statisticians have a fundamental role to play in ensuring that biomarkers and the data they generate are used appropriately and to address relevant objectives such as the estimation of biological effects or the forecast of outcomes so that claims of predictivity or surrogacy are only made based upon sound scientific arguments. This includes ensuring that studies are designed to answer specific and pertinent questions, that the analyses performed account for all levels and sources of variability and that the conclusions drawn are robust in the presence of multiplicity and confounding factors, especially as many biomarkers are multidimensional or may be an indirect measure of the clinical outcome. In all of these areas, as in any area of drug development, statistical best practice incorporating both scientific rigor and a practical understanding of the situation should be followed. This article is intended as an introduction for statisticians embarking upon biomarker-based work and discusses these issues from a practising statistician's perspective with reference to examples.     

The social dimensions of happiness and life satisfaction of Australians: Evidence from the World Values Survey

Relatively short‐term verbal therapies and other forms of intervention may help people to overcome difficult passages in life, but studies in recent decades have pointed to the salience of social and economic conditions in shaping life satisfaction and happiness. The present study contributes to our knowledge of this field by extending the range of social factors considered, but also, crucially, by the employment of statistical analyses that serve to disentangle the often overlapping variables associated with life satisfaction and happiness. Our results support previous ‘demographic’ findings as well as new results including education, marriage, children, human rights and, particularly in the context of Australian society, perceived choice in life. Establishing what the major contributing factors are can assist the formulation of social policy. Moreover, it can alert practitioners to the value of consolidating their work by encouraging service users to utilise community sources that enhance life satisfaction and/or happiness. Key Practitioner Message: ● The informed linking of service users to sources of life satisfaction and happiness can ‘value add’ direct service interventions; ● The salience of exercising individual choice to achieving life satisfaction reinforces the importance of the practice principle of self‐determination; ● A person's sense of physical wellbeing is a relevant part of social assessment and subsequent planned actions.     

Marginal Correlation from Logit- and Probit-Beta-Normal Models for Hierarchical Binary Data

In hierarchical data settings, be it of a longitudinal, spatial, multi-level, clustered, or otherwise repeated nature, often the association between repeated measurements attracts at least part of the scientific interest. Quantifying the association frequently takes the form of a correlation function, including but not limited to intraclass correlation. Vangeneugden et al. (2010 Vangeneugden, T., Molenberghs, G., Laenen, A., Geys, H., Beunckens, C., Sotto, C. (2010). Marginal correlation in longitudinal binary data based on generalized linear mixed models. Communi. Stati. Theory &; Methods. 39:3542–3557. [Google Scholar]) derived approximate correlation functions for longitudinal sequences of general data type, Gaussian and non-Gaussian, based on generalized linear mixed-effects models. Here, we consider the extended model family proposed by Molenberghs et al. (2010 Molenberghs, G., Verbeke, G., Demétrio, C., Vieira, A. (2010). A family of generalized linear models for repeated measures with normal and conjugate random effects. Stat. Sci. 25:325–347.[Crossref], [Web of Science ®] , [Google Scholar]). This family flexibly accommodates data hierarchies, intra-sequence correlation, and overdispersion. The family allows for closed-form means, variance functions, and correlation function, for a variety of outcome types and link functions. Unfortunately, for binary data with logit link, closed forms cannot be obtained. This is in contrast with the probit link, for which such closed forms can be derived. It is therefore that we concentrate on the probit case. It is of interest, not only in its own right, but also as an instrument to approximate the logit case, thanks to the well-known probit-logit ‘conversion.’ Next to the general situation, some important special cases such as exchangeable clustered outcomes receive attention because they produce insightful expressions. The closed-form expressions are contrasted with the generic approximate expressions of Vangeneugden et al. (2010 Vangeneugden, T., Molenberghs, G., Laenen, A., Geys, H., Beunckens, C., Sotto, C. (2010). Marginal correlation in longitudinal binary data based on generalized linear mixed models. Communi. Stati. Theory &; Methods. 39:3542–3557. [Google Scholar]) and with approximations derived for the so-called logistic-beta-normal combined model. A simulation study explores performance of the method proposed. Data from a schizophrenia trial are analyzed and correlation functions derived.     

Forming Effective Employee Information and Consultation: A Five‐Stage Trust and Justice Process

In this paper we show how trust and justice influence the efficacy of employee information and consultation (I&C) bodies. Evidence is drawn from a 2‐year qualitative study of I&C participants in two organizations in the UK. The research builds on Dietz and Fortin's conceptual five‐stage model of the I&C process to provide a more nuanced understanding of I&C trust and justice outcomes. In particular, we point to crucial stages in the process, and how these influence the effectiveness of I&C mechanisms. Implications for theory and practice are discussed.