We propose a new method for selecting a common subset of explanatory variables where the aim is to model several response variables. The idea is a natural extension of the LASSO technique proposed ...

There are a wide array of smoothing methods available for finding structure in data. A general framework is developed which shows that many of these can be viewed as a projection of the data, with respect to appropriate norms. The underlying vector space is an unusually large product space, which allows inclusion of a wide range of smoothers in our setup (including many methods not typically considered to be projections). We give several applications of this simple geometric interpretation of smoothing. A major payoff is the natural and computationally frugal incorporation of constraints. Our point of view also motivates new estimates and helps understand the finite sample and asymptotic behavior of these estimates.

Data from murine models suggest that CD40 activation may synergize with cytotoxic chemotherapy. We aimed to determine the maximum tolerated dose (MTD) and toxicity profile and to explore immunological biomarkers of the CD40-activating antibody CP-870,893 with cisplatin and pemetrexed in patients with malignant pleural mesothelioma (MPM). Eligible patients had confirmed MPM, ECOG performance status 0–1, and measurable disease. Patients received cisplatin 75 mg/m² and pemetrexed 500 mg/m² on day 1 and CP-870,893 on day 8 of a 21-day cycle for maximum 6 cycles with up to 6 subsequent cycles single-agent CP-870,893. Immune cell subset changes were examined weekly by flow cytometry. Fifteen patients were treated at three dose levels. The MTD of CP-870,893 was 0.15 mg/kg, and was exceeded at 0.2 mg/kg with one grade 4 splenic infarction and one grade 3 confusion and hyponatraemia. Cytokine release syndrome (CRS) occurred in most patients (80%) following CP-870,893. Haematological toxicities were consistent with cisplatin and pemetrexed chemotherapy. Six partial responses (40%) and 9 stable disease (53%) as best response were observed. The median overall survival was 16.5 months; the median progression-free survival was 6.3 months. Three patients survived beyond 30 months. CD19+ B cells decreased over 6 cycles of chemoimmunotherapy (P < 0.001) with a concomitant increase in the proportion of CD27+ memory B cells (P < 0.001) and activated CD86+CD27+ memory B cells (P < 0.001), as an immunopharmacodynamic marker of CD40 activation. CP-870,893 with cisplatin and pemetrexed is safe and tolerable at 0.15 mg/kg, although most patients experience CRS. While objective response rates are similar to chemotherapy alone, three patients achieved long-term survival. ACTRN12609000294257.

Genetic algorithms have been extensively used and studied in computer science, yet there is no generally accepted methodology for exploring which parameters significantly affect performance, whether there is any interaction between parameters, and how performance varies with respect to changes in parameters. This paper presents a rigorous yet practical statistical methodology for the exploratory study of genetic and other adaptive algorithms. This methodology addresses the issues of experimental design, blocking, power calculations, and response curve analysis. It details how statistical analysis may assist the investigator along the exploratory pathway. As a demonstration of our methodology, we describe case studies using four well-known test functions. We find that the effect upon performance of crossover is pre-dominantly linear, while the effect of mutation is predominantly quadratic. Higher order effects are noted but contribute less to overall behavior. In the case of crossover, both positive and negative gradients are found suggesting the use of a maximum crossover rate for some problems and its exclusion for others. For mutation, optimal rates appear higher compared with earlier recommendations in the literature, while supporting more recent work. The significance of interaction and the best values for crossover and mutation are problem specific.

All analyses of spatially aggregated data are vulnerable to the modifiable areal unit problem (MAUP), which describes the sensitivity of analytical results to the arbitrary choice of spatial aggregation unit at which data are measured. The MAUP is a serious problem endemic to analyses of spatially aggregated data in all scientific disciplines. However, the impact of the MAUP is rarely considered, perhaps partly because it is still widely considered to be unsolvable. It was originally understood that a solution to the MAUP should constitute a comprehensive statistical framework describing the regularities in estimates of association observed at different combinations of spatial scale and zonation. Additionally, it has been debated how such a solution should incorporate the geographical characteristics of areal units (e.g. shape, size, and configuration), and in particular whether this can be achieved in a purely mathematical framework (i.e. independent of areal units). We argue that the consideration of areal units must form part of a solution to the MAUP, since the MAUP only manifests in their presence. Thus, we present a theoretical and statistical framework that incorporates the characteristics of areal units by combining estimates obtained from different scales and zonations. We show that associations estimated at scales larger than a minimal geographical unit of analysis are systematically biased from a true minimal-level effect, with different zonations generating uniquely biased estimates. Therefore, it is fundamentally erroneous to infer conclusions based on data that are spatially aggregated beyond the minimal level. Instead, researchers should measure and display information, estimate effects, and infer conclusions at the smallest possible meaningful geographical scale. The framework we develop facilitates this. The proposed framework represents a new minimum standard in the estimation of associations using spatially aggregated data, and a reference point against which previous findings and misconceptions related to the MAUP can be understood.