1,354,152 research outputs found
III. Rivista filologico-letteraria, publicata da F. Corazzini, A. Gemma, B. Zandonella
No full textP. G. III. Rivista filologico-letteraria, publicata da F. Corazzini, A. Gemma, B. Zandonella. In: Romania, tome 2 n°6, 1873. pp. 270-271
Formalizzazione delle Ipotesi di Ricerca in Psicologia: Design Analysis e Model Comparison
No full textLa valutazione di ipotesi definite in accordo con le aspettative dei ricercatori o di prospettive teoriche è uno degli obiettivi principali della ricerca empirica. Quando viene condotto uno studio, infatti, i ricercatori di solito vogliono valutare la plausibilità delle loro ipotesi sulla base dei dati osservati. Per fare ciò, sono stati sviluppati diversi approcci statistici come, ad esempio, il Null Hypothesis Significance Testing (NHST).
In psicologia, il NHST è l'approccio statistico dominante per valutare le ipotesi di ricerca. In realtà, tuttavia, l'approccio NHST non consente ai ricercatori di rispondere alla domanda a cui di solito sono interessati. Infatti, l'approccio NHST non quantifica l'evidenza a favore di un'ipotesi, ma quantifica solo l'evidenza contro l'ipotesi nulla. Ciò può facilmente portare a un'errata interpretazione dei risultati che, insieme all'applicazione meccanica ad insensata dell'approccio NHST, è considerata una delle cause dell'attuale crisi di replicabilità.
Nella prima parte della tesi, introduciamo il framework della Design Analysis che ci permette di valutare i rischi inferenziali legati alla stima della dimensione dell'effetto quando si seleziona per la significatività. Nel caso di studi con campioni ridotti che valutano fenomeni complessi e con grande variabilità nei dati (tutte condizioni molto comuni in psicologia), la selezione per significatività può facilmente portare a risultati fuorvianti ed inaffidabili. Questo aspetto è spesso trascurato nella Power Analysis tradizionale. La Design Analysis, invece, mette in evidenza questo importante problema.
Nella seconda parte della tesi, ci spostiamo dal NHST verso l'approccio del Model Comparison. Il Model Comparison ci consente di valutare correttamente l'evidenza relativa a favore di un'ipotesi in base ai dati. In primo luogo, le ipotesi di ricerca vengono formalizzate sotto forma di diversi modelli statistici. Successivamente, queste vengono valutate secondo diversi possibili criteri come, ad esempio, gli Information Criteria e il Bayes Factor con encompassing prior. Gli Information Criteria valutano la capacità predittiva dei modelli penalizzando per la complessità del modello. Il Bayes Factor con encompassing prior, invece, consente ai ricercatori di valutare facilmente ipotesi informative con vincoli di uguaglianza e disuguaglianza sui parametri del modello.The evaluation of research and theoretical hypotheses is one of the principal goals of empirical research. In fact, when conducting a study, researchers usually have expectations based on hypotheses or theoretical perspectives they want to evaluate according to the observed data. To do that, different statistical approaches have been developed, for example, the Null Hypothesis Significance Testing (NHST).
In psychology, the NHST is the dominant statistical approach to evaluate research hypotheses. In reality, however, the NHST approach does not allow researchers to answer the question they usually are interested in. In fact, the NHST approach does not quantify the evidence in favour of a hypothesis, but it only quantifies the evidence against the null hypothesis. This can easily lead to the misinterpretation of the results that, together with a mindless and mechanical application of the NHST approach, is considered as one of the causes of the ongoing replicability crisis.
In the first part of the thesis, we introduce the Design Analysis framework that allows us to evaluate the inferential risks related to effect size estimation when selecting for significance. In the case of underpowered studies evaluating complex multivariate phenomena with noisy data (all very common conditions in psychology), selecting for significance can easily lead to misleading and unreliable results. This aspect is often neglected in traditional power Analysis. Design analysis, instead, highlights this relevant issue.
In the second part of the thesis, we move away from the NHST towards the model comparison approach. Model comparison allows us to properly evaluate the relative evidence in favour of one hypothesis according to the data. First, research hypotheses are formalized into different statistical models, subsequently, these are evaluated according to different possible criteria. We consider the information criteria and the Bayes Factor with encompassing prior. Information criteria assess models predictive ability penalizing for model complexity. Bayes Factor with encompassing prior, instead, allows researchers to easily evaluate informative hypotheses with equality and inequality constraints on the model parameters
Berger, Dolezal, Zandonella, Wood, Staudegger
No full textNeurotechnologien sind als wirkmächtige Technologien einem rasant wachsenden Wirtschaftssektor zuzurechnen. Die Nutzung im medizinischen Bereich ist bereits etabliert, daneben drängen Unternehmen vor allem in den sog „Enhancement“- Sektor. „Neuroenhancement“ soll hier grundsätzlich als Einsatz der Neurotechnologie am gesunden Menschen zur bloßen Selbstverbesserung verstanden werden. Dabei sind die Grenzen zwischen medizinisch-therapeutischen Zwecken und Enhancement fließend, weil sich Neurotechnologien als besonders transgressive Technologien erweisen, mit transformativen gesellschaftlichen Konsequenzen. Da sich beim Grenzübergang vom medizinisch-therapeutischen in den Enhancement-Bereich die moralischen, ethischen und gesetzlichen Grundlagen ändern, ist die plausible kategoriale Abgrenzung der beiden Bereiche von besonderer Bedeutung. Der Beitrag stellt den in interdisziplinärer Zusammenarbeit gewonnenen Vorschlag einer praktikablen Unterscheidung zur Diskussion.
Schlagworte: Neurotechnologien, Enhancement, Gesundheit, Therapie, Selbstverbesserung, TranshumanismusNeurotechnologies are powerful technologies that are part of a rapidly growing industry. Their use in the medical field is already well-established, but the market is also pushing into the so-called ‘enhancement’ sector. The term ‘neuroenhancement’ is used here to refer to the use of neurotechnology on healthy people for the sole purpose of self- improvement. The boundaries between medical-therapeutic purposes and enhancement are blurred, as neurotechnologies are proving to be particularly transgressive technologies with transformative social consequences. As the moral, ethical and legal foundations change in the transition from the medical-therapeutic to the enhancement area, the plausible categorical demarcation of the two areas is of particular importance. In this article, the proposal for a practicable distinction developed in interdisciplinary co-operation is presented for further discussion.
Keywords: Neurotechnologies, recovery, discovery, enhancement, enchantment, health, therapy, self-improvement, transhumanis
Data and supplemental material of the paper “Effectiveness of digital-based interventions for children with mathematical learning difficulties: A meta-analysis”
No full textData and supplement material of the article “Effectiveness of digital-based interventions for children with mathematical learning difficulties: A meta-analysis” (Benavides-Varela et al.) [1] are presented. Data were collected from studies included in the meta-analysis to evaluate the effects of digital-based interventions for children with mathematical learning difficulties compared to control conditions in group-designed randomized controlled trials. Literature search, inclusion criteria and coding procedure are described. PRISMA flow-chart is reported to summarize the literature search and coding of all the relevant characteristics of the primary studies is made available. This allows other researchers to easily access to the information needed to evaluate the studies and to use these data in future meta-analyses. However, researchers are highly recommended to refer to the original papers in order to check studies suitability to their own criteria. Moreover, in the supplemental material all the information needed to reproduce the meta-analysis results is reported together with the R code syntax. Data and supplemental material are available online (https://osf.io/ajdnv/)
Designing Studies and Evaluating Research Results: Type M and Type S Errors for Pearson Correlation Coefficient
No full textIt is widely appreciated that many studies in psychological science suffer from low statistical power. One of the consequences of analyzing underpowered studies with thresholds of statistical significance is a high risk of finding exaggerated effect size estimates, in the right or the wrong direction. These inferential risks can be directly quantified in terms of Type M (magnitude) error and Type S (sign) error, which directly communicate the consequences of design choices on effect size estimation. Given a study design, Type M error is the factor by which a statistically significant effect is on average exaggerated. Type S error is the probability to find a statistically significant result in the opposite direction to the plausible one. Ideally, these errors should be considered during a prospective design analysis in the design phase of a study to determine the appropriate sample size. However, they can also be considered when evaluating studies’ results in a retrospective design analysis. In the present contribution, we aim to facilitate the considerations of these errors in the research practice in psychology. For this reason, we illustrate how to consider Type M and Type S errors in a design analysis using one of the most common effect size measures in psychology: Pearson correlation coefficient. We provide various examples and make the R functions freely available to enable researchers to perform design analysis for their research projects
Hyperspectral aerial images. A valuable tool for submerged vegetation recognition in the Orbetello lagoons, Italy
No full textPublisher: Taylor & Franci
Sustainable food: an educational proposal, for key stage 3 in secondary schools, based on the assessment for learning method.
No full textArcheologia e restauro di un castello medievale: Castrum de Monte Zambano
No full textIl castello di Monzambano fu edificato nel sec. XII, sulla sommità della collina su cui sorge il borgo abitato. In questo studio, redatto a più mani, l'analisi stratigrafica e storica si accompagna alle vicende del restauro e degli scavi archeologici. Il volume è composto inoltre da un ricco apparato iconografico: una dettagliata campagna fotografica e la riproduzione di mappe medievali e rinascimentali, ad attestare l'importanza che questo castello ha rivestito nei secoli
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