Bootstrap: fundamentos e introducción a sus aplicaciones

La técnica bootstrap proporciona estimaciones del error estadistico, imponiendo escasas restricciones sobre las variables aleatorias analizadas y estableciéndose como un procedimiento de caracter general, independien- temente del estadístico considerado. En este trabajo se realiza una presen- tacion de los fundamentos teóricos de la técnica bootstrap, mas desde una perspectiva divulgadora que estrictamente tedrica, ademas de realizarse un breve estudio donde se podra comparar la eficacia de la técnica frente a otras mas establecidas. Palabras clave: Bootstrap, error estadistico, remuestreo Monte Car- 10, tasa de error tip0 I, técnica percentil

Weighting strategies in the meta-analysis of single-case studies

Establishing the evidence base of interventions taking place in areas such as psychology and special education is one of the research aims of single-case designs in conjunction with the aim of improving the well-being of participants in the studies. The scientific criteria for solid evidence focus on the internal and external validity of the studies, and for both types of validity, replicating studies and integrating the results of these replications (i.e., meta-analyzing) is crucial. In the present study we deal with one of the aspects of meta-analysis, namely the weighting strategy used when computing an average effect size across studies. Several weighting strategies suggested for single-case designs are discussed and compared in the context of both simulated and real-life data. The results indicated that there are no major differences between the strategies and, thus we consider that it is important to choose weights with a sound statistical and methodological basis, while scientific parsimony is another relevant criterion. More empirical research and conceptual discussion are warranted regarding the optimal weighting strategy in single-case designs, alongside investigation of the optimal effect size measure in these types of design

Probability and visual aids for assessing intervention effectiveness in single-case designs: A field test

Single-case data analysis still relies heavily on visual inspection and, at the same time, it is not clear to what extent the results of different quantitative procedures converge in identifying an intervention effect and its magnitude when applied to the same data; this is the type of evidence provided here for two procedures. One of the procedures, included due to the importance of providing objective criteria to visual analysts, is a visual aid fitting and projecting split-middle trend while taking into account data variability. The other procedure converts several different metrics into probabilities making their results comparable. In the present study we study to what extend these two procedures coincide in the magnitude of intervention effect taking place in a set of studies stemming from a recent meta-analysis. The procedures concur to a greater extent with the values of the indices computed and with each other and, to a lesser extent, with our own visual analysis. For the distinctions smaller and larger effects the probability-based approach seems somewhat better suited. Moreover, the results of the field test suggest that the latter is a reasonably good mechanism for translating different metrics into similar labels. User friendly R code is provided for promoting the use of the visual aid, together with a quantification based on nonoverlap and the label provided by the probability approach

A discussion of alternatives for establishing empirical benchmarks for interpreting single-case effect sizes

In this paper we reflect on the numerous calls for the development of benchmarks for interpreting effect size indices, reviewing several possibilities. Such benchmarks are aimed to provide criteria so that analysts can judge whether the size of the effect observed is rather 'small', 'medium' or 'large'. The context of this discussion is single-case experimental designs, for which a great variety of procedures have been proposed, with their different nature (e.g., being based on amount of overlap vs. a standardized mean difference) posing challenges to interpretation. For each of the alternatives discussed we point at their strengths and limitations. We also comment how such empirical benchmarks can be obtained, usually b methodologists, and illustrate how these benchmarks can be used by applied researchers willing to have more evidence on the magnitude of effect observed and not only whether an effect is present or not. One of the alternatives discussed is a proposal we make in the current paper. Although it has certain limitations, as all alternatives do, we consider that it is worth discussing it and the whole set of alternatives in order to advance in interpreting effect sizes, now that computing and reporting their numerical values is (or is expected to be) common practice

Assessing functional relations in single-case designs: Quantitative proposals in the context of the evidence-based movement

In the context of the evidence-based practices movement, the emphasis on computing effect sizes and combining them via meta-analysis does not preclude the demonstration of functional relations. For the latter aim, we propose to augment the visual analysis to add consistency to the decisions made on the existence of a functional relation without losing sight of the need for a methodological evaluation of what stimuli and reinforcement or punishment are used to control the behavior. Four options for quantification are reviewed, illustrated, and tested with simulated data. These quantifications include comparing the projected baseline with the actual treatment measurements, on the basis of either parametric or nonparametric statistics. The simulated data used to test the quantifications include nine data patterns in terms of the presence and type of effect and comprising ABAB and multiple baseline designs. Although none of the techniques is completely flawless in terms of detecting a functional relation only when it is present but not when it is absent, an option based on projecting split-middle trend and considering data variability as in exploratory data analysis proves to be the best performer for most data patterns. We suggest that the information on whether a functional relation has been demonstrated should be included in meta-analyses. It is also possible to use as a weight the inverse of the data variability measure used in the quantification for assessing the functional relation. We offer an easy to use code for open-source software for implementing some of the quantifications

Random assignment of intervention points in two phase single-case designs: data-division-specific distributions

The present study explores the statistical properties of a randomization test based on the random assignment of the intervention point in a two-phase (AB) single-case design. The focus is on randomization distributions constructed with the values of the test statistic for all possible random assignments and used to obtain p-values. The shape of those distributions is investigated for each specific data division defined by the moment in which the intervention is introduced. Another aim of the study consisted in testing the detection of inexistent effects (i.e., production of false alarms) in autocorrelated data series, in which the assumption of exchangeability between observations may be untenable. In this way, it was possible to compare nominal and empirical Type I error rates in order to obtain evidence on the statistical validity of the randomization test for each individual data division. The results suggest that when either of the two phases has considerably less measurement times, Type I errors may be too probable and, hence, the decision making process to be carried out by applied researchers may be jeopardized

THE SAME ASSETS, BUT NEW IMPACTS: IT-ENABLED COORDINATION AND ENVIRONMENTAL PERFORMANCE

In this paper we analyze the effect of information technologies (IT) on the environmental performance of firms. In particular, we study the moderating effect of IT on the relationship between a firm\u27s environmental practices and its environmental performance. The paper considers two moderating effects namely, IT-enabled coordination and IT-enabled control. IT-enabled coordination refers to the integration of processes and the sharing of information between a firm and its suppliers in design and manufacturing. IT-enabled control refers to the use of IT to monitor the environmental practices that a firm implements in production and logistics. The data used were obtained from the fifth (2009) round of the International Manufacturing Strategy Survey (IMSS) which includes responses from manufacturing plants within the assembly industry. Our findings suggest that IT-enabled coordination strengthens the impact of the implementation of environmental practices on the environmental performance of firms. A relevant contribution for practice is derived from this study: firms can use the same technologies (ERP, shared databases) that they once implemented to improve their operational performance to improve the environmental performance

Quantifying Social Asymmetric Structures

Many social phenomena involve a set of dyadic relations among agents whose actions may be dependent. Although individualistic approaches have frequently been applied to analyze social processes, these are not generally concerned with dyadic relations nor do they deal with dependency. This paper describes a mathematical procedure for analyzing dyadic interactions in a social system. The proposed method mainly consists of decomposing asymmetric data into their symmetrical and skew-symmetrical parts. A quantification of skew-symmetry for a social system can be obtained by dividing the norm of the skew-symmetrical matrix by the norm of the asymmetric matrix. This calculation makes available to researchers a quantity related to the amount of dyadic reciprocity. Regarding agents, the procedure enables researchers to identify those whose behavior is asymmetric with respect to all agents. It is also possible to derive symmetric measurements among agents and to use multivariate statistical techniques

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London