Bayesian networks in survey data: Robustness and sensitivity issues

Bayesian networks (BN) implement a graphical model structure known as a directed acyclic graph (DAG) that is popular in statistics, machine learning, and artificial intelligence. They enable an effective representation and computation of a joint probability distribution (JPD) over a set of random variables. The paper focuses on the selection of a robust network structure according to different learning algorithms and the measure of arc strength using resampling techniques. Moreover, it shows how 'what-if' sensitivity scenarios are generated with BN using hard and soft evidence in the framework of predictive inference. Establishing a robust network structure and using it for decision support are two essential enablers for efficient and effective applications of BN to improvements of products and processes. A customer-satisfaction survey example is presented and R scripts are provided

First evaluation of QuantiFERON-TB Gold Plus performance in contact screening

Identifying latently infected individuals is crucial for the elimination of tuberculosis (TB). We evaluated for the first time the performance of a new type of interferon-γ release assay, QuantiFERON-TB Plus (QFT-Plus), which includes an additional antigen tube (TB2), stimulating both CD4(+) and CD8(+) T-cells in contacts of TB patients.Contacts were screened for latent TB infection by tuberculin skin test, QFT-Plus and QuantiFERON-TB Gold in Tube (QFT-GIT).In 119 TB contacts, the overall agreement between QFT-Plus and QFT-GIT was high, with a Cohen's κ of 0.8. Discordant results were found in 12 subjects with negative QFT-GIT and positive QFT-Plus results. In analyses of markers of TB exposure and test results, the average time spent with the index case was the strongest risk factor for positivity in each of these tests. The difference in interferon-γ production between the two antigen tubes (TB2-TB1) was used as an estimate of CD8(+) stimulation provided by the TB2. TB2-TB1 values >0.6 IU·mL(-1) were significantly associated with proximity to the index case and European origin.QFT-Plus has a stronger association with surrogate measures of TB exposure than QFT-GIT in adults screened for latent TB infection. Interferon-γ response in the new antigen tube used an indirect estimate of specific CD8(+) response correlates with increased Mycobacterium tuberculosis exposure, suggesting a possible role in identifying individuals with recent infection

Comparison for alternative imputation methods for ordinal data : conference proceedings

In this paper, we compare alternative missing imputation methods in the presence of ordinal data, in the framework of CUB (combination of uniform and (shifted) binomial random variable) models. Single and multiple imputation methods are considered, as well as univariate and multivariate approaches. The rst step consists of running a simulation study designed by varying the parameters of the CUB model, in order to consider and compare CUB models as well as other methods of missing imputation. We use real datasets on which to base the comparison between our approach and some general methods of missing imputation for various missing data pattern

Model-based approach for importance–performance analysis

The importance that users or customers attach to various services and products is an essential part of customer satisfaction surveys. Some proposals for linking satisfaction and importance can be found in available literature. The objective is to identify and understand the dimensions with high importance but low perceived quality. These dimensions are primary candidates for focused improvement initiatives. In this study, we propose to apply a class of statistical models, denoted as CUB models, generally used to estimate the feeling and the uncertainty, to measure the importance of items on observed overall satisfaction. A questionnaire with explicit variables of importance for each dimension is considered to compare the obtained ranks with the observed ones. Then the estimated importance and the perceived quality, both obtained with the CUB models, will be jointly analyzed in different datasets coming from various fields. This approach will be compared with some others reported in the literatur

Importance and quality of service quality dimensions : a model based approach

The importance that users or customers attach to various services and products is an essential part of customer satisfaction surveys. Some proposals for linking satisfaction and importance can be found in available literature. The objective is to identify and understand the dimensions with high importance but low perceived quality. These dimensions are primary candidates for focused improvement initiatives. In this study, we propose to apply a class of statistical models, denoted as CUB models, generally used to estimate the feeling and the uncertainty, to measure the importance of items on observed overall satisfaction. A questionnaire with explicit variables of importance for each dimension is considered to compare the obtained ranks with the observed ones. Then the estimated importance and the perceived quality, both obtained with the CUB models, will be jointly analyzed in different datasets coming from various fields. This approach will be compared with some others reported in the literature

A model-based approach to validate a measuring instrument for assessing the quality of care

The Functional Assessment of Chronic Illness Therapy - Treatment Satisfaction - Patient Satisfaction (FACIT-TS-PS) is a measure for assessing the quality of care and satisfaction in chronically ill patients. Validity of the multi-dimensional structure and reliability of the FACIT-TS-PS were investigated in a sample of 431 chronically ill patients, using Confirmative Factor Analysis (CFA) and CUB models. Integrated use of CUB models and CFA resulted in a satisfactory structure, leading to confirmation of the original, reliable, seven-factor structure, even with a reduction in items from 25 to 15. The FACIT-TS-PS appears to be a practical instrument that is reliable and has good construct validity

Bayesian networks and the assessment of universities' value added

A broad literature focused on the effectiveness of tertiary education. In classical models, a performance indicator is regressed on a set of characteristics of the individuals and fixed effects at the institution level. The FE coefficients are interpreted as the pure value added of the universities. The innovative contribution of the present paper resides in the use of Bayesian network (BN) analysis to assess the effectiveness of tertiary education. The results of an empirical study focused on Italian universities are discussed, to present the use of BN as a decision support tool for policy-making purposes

Valutazione degli effetti di un training conversazionale su teoria della mente e solitudine in età scolare.

Introduzione: La letteratura sulle abilità di teoria della mente (ToM) nella media infanzia si è ampliata nel corso degli ultimi anni e alcuni ricercatori hanno attuato interventi di training finalizzati al miglioramento di tali abilità. Studi recenti hanno mostrato che training basati sulle conversazioni circa gli stati mentali migliorano non solo le abilità di ToM (e.g. Bianco, Lecce, & Banerjee, 2016; Lecce, Bianco, Devine, Hughes, & Banerjee, 2014), ma anche altre abilità, come la comprensione di emozioni e l’orientamento prosociale (Ornaghi, Grazzani, Cherubin, Conte, & Piralli, 2015). Nel presente studio abbiamo esaminato un possibile effetto di modulazione indotta da un training conversazionale sulle abilità di ToM (misurate tramite le Strange Stories) e sulla percezione di solitudine e insoddisfazione sociale (misurata tramite il questionario Loneliness and Social Dissatisfaction Questionnaire - LSDQ). Metodo: A tale scopo abbiamo coinvolto 210 bambini di quarta (età media= 9.3 anni, DS = 0.29) e quinta elementare (età media = 10.08 anni, DS = 1.07), casualmente assegnati ad una delle due condizioni (ToM o no-ToM). Entrambi i gruppi hanno partecipato a cinque sessioni di training conversazionale (da 50 minuti ciascuna) nell’arco di un mese: a partire dalla lettura di una storia il gruppo assegnato alla condizione ToM conversava sugli stati mentali dei personaggi mentre il gruppo assegnato alla condizione no-ToM su elementi non mentalistici della narrazione. Tutti i bambini hanno completato una prova di vocabolario, le Strange Stories e il questionario LSDQ prima (T0) e dopo il training (T1), così come due mesi dopo (T2). La performance dei due gruppi nelle prove a T0 era simile. Risultati: Le variazioni dei punteggi nelle Strange Stories e nel questionario LSDQ ottenuti durante il progetto nei due gruppi sono state valutate tramite modelli lineari ad effetti misti. Per quanto riguarda le abilità di ToM, è emerso un aumento significativo dei punteggi nel tempo (p-value T1 < .0001, p-value T2 < .0001); inoltre, la performance dei bambini assegnati alla condizione ToM risulta a T1 significativamente superiore rispetto a quella dei bambini assegnati alla condizione no-ToM (effetto significativo dell’interazione tra tempo e gruppo, p-value =0.0004). Relativamente al questionario LSDQ, si è osservata una riduzione nei punteggi dei bambini assegnati alla condizione ToM al tempo T1 (p-value= 0.0321). Discussione: Le conversazioni mirate alla comprensione e all’utilizzo di diversi stati mentali (condizione ToM) non solo hanno favorito l’aumento di abilità di ToM ma hanno anche ridotto la percezione di solitudine e insoddisfazione sociale. Le conversazioni limitate ad elementi non mentalistici (condizione no-ToM) della narrazione non hanno sortito lo stesso effetto benefico. Conclusioni: I risultati del presente lavoro suggeriscono pertanto l’utilità di interventi conversazionali per la promozione del benessere negli anni della scuola primaria