1,721,035 research outputs found
New permutation methodologies to deal with the multiplicity issue: multiple comparisons and multiple tests with applications to single-case experiments and to regression analysis
Full text linkThe thesis presents new results within the permutation testing approach in order to deal with real complex problems. Very often real datasets are the result of complicated planning phases of the study or they are complex by themselves. Multiple outcomes are often of interest and, a fact which increases further on their complexity, complicated and unknown dependence structures can underlie such multivariate responses (i.e. the multiplicity issue). Two particular applied problems are faced: single-case experiments and regression analysis of ordinal data.
Both univariate and multivariate solutions to such issues are proposed in this thesis, which show to successfully handle the data complexity by means of permutation tests and their nonparametric combination. Regarding the single-case experiments problem a complex solution is developed which exploits the joint use of smoothing techniques and permutation theory. For ordinal data analysis instead, we propose some permutation solutions that use parametric estimates as test statistics, creating a link between parametric and nonparametric problem solving.
Several simulation studies and real case applications show the good behavior and the usefulness of the presented procedures.Questa tesi presenta nuove metodologie di permutazione per risolvere problemi reali di natura complessa. Spesso i dati reali sono risultati di complesse fasi di pianificazione dell'esperimento, o sono di loro natura complessi. Risposte multiple sono spesso di interesse e, fatto che aumenta ulteriormente la complessità, le strutture di dipendenza presenti all'interno dei dati sono, oltre che complicate, sconosciute (problema della molteplicità). Sono qui stati affrontati due problemi reali: i così detti single-case experiments e l'analisi di dati ordinali.
Nella tesi vengono proposte soluzioni sia univariate che multivariate, che mostrano di risolvere il problema in modo soddisfacente tramite l'utilizzo di test di permutazione e della loro combinazione non parametrica. Riguardo i single-case experiments viene presentata una soluzione complessa basata sulla combinazione di tecniche di lisciamento e della teoria di permutazione. Per l'analisi di dati ordinali, invece, si propongono alcuni test di permutazione che utilizzano stime non parametriche come statistiche test, creando in questo modo un collegamento tra soluzione del problema via parametrica e non parametrica.
Diversi studi di simulazione e applicazioni a dati reali mostrano il buon comportamento e l'utilità dei metodi proposti
EXTENSIONS OF PERMUTATION SOLUTIONS TO TEST FOR TREATMENT EFFECTS IN REPLICATED SINGLE-CASE ALTERNATION EXPERIMENTS WITH MULTIVARIATE RESPONSE
No full textSingle-case experiments are frequently used to do research involving a clinical intervention, since large-n trials are often impractical in clinical research. In order to investigate a possible difference in the effect of the treatments considered in the study, nonparametric instruments are valid tools; in particular permutation solutions work well when we wish to assess differences in treatment effects. We present an extension of a permutation solution to the multivariate response case and to the case of replicated single-case experiments. A simulation study shows that the approach is both reliable under the null hypothesis and powerful under the alternative. At the end we present the results of an application to two real experiments
Advances in Permutation Tests for Covariates in a Mixture Model for Preference Data Analysis
No full textThe rating problem arises very often in statistical surveys and a new approach for this problem is represented by the combination of uniform and binomial models. In the present work a simulation study is presented to prove the good power behavior of a permutation test on the covariates of a complex model, with more than one covariate. Moreover a discussion on the minimum sample size needed to perform such permutation test is also given
A Permutation Solution to Test for Treatment Effects in Alternation Design Single-Case Experiments
No full textResearch involving a clinical intervention is normally aimed at testing the treatment effects on a dependent variable, which is assumed to be a relevant indicator of health or quality-of-life status. In much clinical research large-n trials are in fact impractical because the availability of individuals within well-defined categories is limited in this application field. This makes it more and more important to concentrate on single-case experiments. The goal with these is to investigate the presence of a difference in the effect of the treatments considered in the study. In this setting, valid inference generally cannot be made using the parametric statistical procedures that are typically used for the analysis of clinical trials and other large-n designs. Hence, nonparametric tools can be a valid alternative to analyze this kind of data. We propose a permutation solution to assess treatment effects in single-case experiments within alternation designs. An extension to the case of more than two treatments is also presented. A simulation study shows that the approach is both reliable under the null hypothesis and powerful under the alternative, and that it improves the performance of a considered competitor. In the end, we present the results of a real case application
Cardiac telerehabilitation : a novel cost-efficient care delivery strategy that can induce long-term health benefits
No full textAbstract: Background: Finding innovative and cost-efficient care strategies that induce long-term health benefits in cardiac patients constitutes a big challenge today. The aim of this Telerehab III follow-up study was to assess whether a 6-month additional cardiac telerehabilitation programme could induce long-term health benefits and remain cost-efficient after the tele-intervention ended. Methods and results: A total of 126 cardiac patients first completed the multicentre, randomised controlled telerehabilitation trial (Telerehab III, time points t(0) to t(1)). They consequently entered the follow-up study (t(1)) with evaluations 2 years later (t(2)). A quantitative analysis of peak aerobic capacity (VO2 peak, primary endpoint), international physical activity questionnaire self-reported physical activity and HeartQoL quality of life (secondary endpoints) was performed. The incremental cost-effectiveness ratio was calculated. Even though a decline in VO2 peak (248ml/[min*kg] at t(1) and 226ml/[min*kg] at t(2); P <= 0.001) was observed within the tele-intervention group patients; overall they did better than the no tele-intervention group (P=0.032). Dividing the incremental cost (-(sic)878/patient) by the differential incremental quality-adjusted life years (QALYs) (0.22 QALYs) yielded an incremental cost-effectiveness ratio of -(sic)3993/QALY. Conclusions: A combined telerehabilitation and centre-based programme, followed by transitional telerehabilitation induced persistent health benefits and remained cost-efficient up to 2 years after the end of the intervention. A partial decline of the benefits originally achieved did occur once the tele-intervention ended. Healthcare professionals should reflect on how innovative cost-efficient care models could be implemented in standard care. Future research should focus on key behaviour change techniques in technology-based interventions that enable full persistence of long-term behaviour change and health benefits
Nonparametric Multivariate Inference Via Permutation Tests for CUB Models
No full textA new approach for modelling discrete choices in rating or ranking problems is represented by a class of mixture models with covariates (Combination of Uniform and shifted Binomial distributions, CUB models), proposed by Piccolo (2003, Quaderni di Statistica, 5, 85-104), D'Elia & Piccolo (2005, Computational Statistics & Data Analysis, 49, 917-934), Piccolo (2006, Quaderni di Statistica, 8, 33-78) and Iannario (2010, Metron, LXVIII, 87-94). In case of a univariate response, a permutation solution to test for covariates effects has been discussed in Bonnini et al. (2012, Communication in Statistics: Theory and Methods), together with parametric inference. We propose an extension of this nonparametric test to deal with the multivariate case. The good performances of the method are showed trough a simulation study and the procedure is applied to real data regarding the evaluation of the Ski School of Sesto Pusteria (Italy)
Customer satisfaction survey on Passito wine with theapplication of a new approach to modelling discrete choices
No full textThe aim of this work is to study the demand for Passito wine in the Veneto region (northeast Italy) identifying homogeneous segments of consumers based on preferences and consumption habits. In 2009 market research telephone interviews were conducted. Data and processing reported in this article refer to that survey. Applying the CUB model (Iannario and Piccolo, 2007) it is possible to describe a subject's preferences through a class of mixture models with two parameters representing the feeling toward the Passito and the uncertainty of the evaluators. Estimations and tests of hypotheses on the model's parameters allow us to study if and how some individual customer characteristics affect feeling and uncertainty
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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