BUSCADOR RECOLECTA

We propose two draw systems for the group round of sport tournaments where there are some geographical and/or seeding restrictions. One of the systems, related to the equal-sum partition problem, is "perfect, " since it yields perfectly balanced groups. The other system, which uses the classical scheme of extracting teams from pots, is heuristic and gives results where the groups have very similar scores. We apply our results to Federation Internationale de Football Association (FIFA) Soccer World Cups and show that our proposals are much better than the FIFA system and also outperform other recently developed systems.

In this paper, we propose an algorithmic approach based on resampling and bootstrap techniques to measure the importance of a variable, or a set of variables, in econometric models. This algorithmic approach allows us to check the real weight of a variable in a model, avoiding the biases of classical tests, and to select the more relevant variables, or models, in terms of predictability, by reducing dimensions. We apply this methodology to the Global Entrepreneurship Monitor data for the year 2014, to analyze the individual- and national-level determinants of entrepreneurial activity, and compare the results with a forward selection approach, also based on resampling
predictability, and a standard forward stepwise selection process. We find that our proposed techniques offer more accurate results, which show that innovation and new technologies, peer effects, the sociocultural environment, entrepreneurial education at University, R&D transfers, and the availability of government subsidies are among the most important predictors of entrepreneurial behavior.

In the first phase of pharmaceutical development, and assuming that the probability of positive response increases with dose, the main statistical goal is to estimate a percentile of the dose–response function for a given target ¿. We compare the Maximum Likelihood and centred isotonic regression estimators of the target dose and we discuss several performance criteria to assess inferential precision, the amount of toxicity exposure and the trade-off between them for a set of some exemplary adaptive designs. We compare these designs using graphical tools. Several scenarios are considered using simulation, including the use of several start-up rules, the change of slope of the dose-toxicity function at the target dose and also different theoretical models, as logistic, normal or skew-normal distribution functions.

STUDY DESIGN: Multicenter, parallel randomized clinical trial. BACKGROUND: Myofascial trigger points (MTrPs) are implicated in shoulder pain and functional limitations. An intervention intended to treat MTrPs is dry needling. OBJECTIVES: To investigate the effectiveness of dry needling in addition to evidence-based personalized physical therapy treatment in the treatment of shoulder pain. METHODS: One hundred twenty patients with nonspecific shoulder pain were randomly allocated into 2 parallel groups: (1) personalized, evidencebased physical therapy treatment; and (2) trigger point dry needling in addition to personalized, evidence-based physical therapy treatment. Patients were assessed at baseline, posttreatment, and 3-month follow-up. The primary outcome measure was pain assessed by a visual analog scale at 3 months, and secondary variables were joint range-of-motion limitations, Constant-Murley score for pain and function, and number of active MTrPs. Clinical efficacy was assessed using intention-to-treat analysis. RESULTS: Of the 120 enrolled patients, 63 were randomly assigned to the control group and 57 to the intervention group. There were no significant differences in outcome between the 2 treatment groups. Both groups showed improvement over time. CONCLUSION: Dry needling did not offer benefits in addition to personalized, evidencebased physical therapy treatment for patients with nonspecific shoulder pain. Copyright

In the first phase of pharmaceutical development, and assuming that the probability of positive response increases with dose, the main statistical goal is to estimate a percentile of the dose–response function for a given target Г. We compare the Maximum Likelihood and centred isotonic regression estimators of the target dose and we discuss several performance criteria to assess inferential precision, the amount of toxicity exposure and the trade-off between them for a set of some exemplary adaptive designs. We compare these designs using graphical tools. Several scenarios are considered using simulation, including the use of several start-up rules, the change of slope of the dose-toxicity function at the target dose and also different theoretical models, as logistic, normal or skew-normal distribution functions., Fernando Plo and Jose Moler acknowledge the financial support received from the projects Ministerio de Economía y Competitividad (MTM2014‐53340‐P) and Secretaría de Estado de Investigación, Desarrollo e Innovación (MTM2016‐77015‐R).