Multidimensional item response theory models with general and specific latent traits for ordinal data

The aim of the thesis is to propose a Bayesian estimation through Markov chain Monte Carlo of multidimensional item response theory models for graded responses with complex structures and correlated traits. In particular, this work focuses on the multiunidimensional and the additive underlying latent structures, considering that the first one is widely used and represents a classical approach in multidimensional item response analysis, while the second one is able to reflect the complexity of real interactions between items and respondents. A simulation study is conducted to evaluate the parameter recovery for the proposed models under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameter recovery is particularly sensitive to the sample size, due to the model complexity and the high number of parameters to be estimated. For a sufficiently large sample size the parameters of the multiunidimensional and additive graded response models are well reproduced. The results are also affected by the trade-off between the number of items constituting the test and the number of item categories. An application of the proposed models on response data collected to investigate Romagna and San Marino residents' perceptions and attitudes towards the tourism industry is also presented.

Response times in computerized adaptive testing: a method for cheating detection

In the field of educational and psychological measurement, the shift from paper-based to computerized tests has become a prominent trend in recent years. Computerized tests allow for more complex and personalized test administration procedures, like Computerized Adaptive Testing (CAT). CAT, following the Item Response Theory (IRT) models, dynamically generates tests based on test-taker responses, driven by complex statistical algorithms. Even if CAT structures are complex, they are flexible and convenient, but concerns about test security should be addressed. Frequent item administration can lead to item exposure and cheating, necessitating preventive and diagnostic measures. In this thesis a method called "CHeater identification using Interim Person fit Statistic" (CHIPS) is developed, designed to identify and limit cheaters in real-time during test administration. CHIPS utilizes response times (RTs) to calculate an Interim Person fit Statistic (IPS), allowing for on-the-fly intervention using a more secret item bank. Also, a slight modification is proposed to overcome situations with constant speed, called Modified-CHIPS (M-CHIPS). A simulation study assesses CHIPS, highlighting its effectiveness in identifying and controlling cheaters. However, it reveals limitations when cheaters possess all correct answers. The M-CHIPS overcame this limitation. Furthermore, the method has shown not to be influenced by the cheaters’ ability distribution or the level of correlation between ability and speed of test-takers. Finally, the method has demonstrated flexibility for the choice of significance level and the transition from fixed-length tests to variable-length ones. The thesis discusses potential applications, including the suitability of the method for multiple-choice tests, assumptions about RT distribution and level of item pre-knowledge. Also limitations are discussed to explore future developments such as different RT distributions, unusual honest respondent behaviors, and field testing in real-world scenarios. In summary, CHIPS and M-CHIPS offer real-time cheating detection in CAT, enhancing test security and ability estimation while not penalizing test respondents.

L'impiego del modello di Rash per la valutazione della soddisfazione del paziente nell'ambito delle strutture sanitarie di ricovero

Hospitals and health service providers are use to collect data about patient’s opinion to improve patient health status and communication with them and to upgrade the management and the organization of the health service provided. A lot of survey are carry out for this purpose and several questionnaire are built to measure patient satisfaction. In particular patient satisfaction is a way to describe and assess the level of hospital service from the patient’s point of view. It is a cognitive and an emotional response to the hospital experience. Methodologically patient satisfaction is defined as a multidimensional latent variable. To assess patient satisfaction Item Response Theory has greater advantages compared to Classical Test Theory. Rasch model is a one-parameter model which belongs to Item Response Theory. Rasch model yield objective measure of the construct that are independent of the set of people interviewed and of set of items used. Rasch estimates are continuous and can be useful to “calibrate” the scale of the latent trait. This research attempt to investigate the questionnaire currently adopted to measure patient satisfaction in an Italian hospital, completed by a large sample of 3390 patients. We verify the multidimensional nature of the variable, the properties of the instrument and the level of satisfaction in the hospital. Successively we used Rasch estimates to describe the most satisfied and the less satisfied patients.

A bayesian model for mixed responses and skew laten variable to measure HRQoL in children

The aim of the thesi is to formulate a suitable Item Response Theory (IRT) based model to measure HRQoL (as latent variable) using a mixed responses questionnaire and relaxing the hypothesis of normal distributed latent variable. The new model is a combination of two models already presented in literature, that is, a latent trait model for mixed responses and an IRT model for Skew Normal latent variable. It is developed in a Bayesian framework, a Markov chain Monte Carlo procedure is used to generate samples of the posterior distribution of the parameters of interest. The proposed model is test on a questionnaire composed by 5 discrete items and one continuous to measure HRQoL in children, the EQ-5D-Y questionnaire. A large sample of children collected in the schools was used. In comparison with a model for only discrete responses and a model for mixed responses and normal latent variable, the new model has better performances, in term of deviance information criterion (DIC), chain convergences times and precision of the estimates.

Assessing the fit of unidimensional IRT models for binary data under model misspecification

Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

Ricezione e Finzione. Una teoria della lettura tra struttura e risposta estetica

Attraverso l’analisi di teorie della lettura “centripete” e “centrifughe”, tra fenomenologia, semiotica e teoria della risposta estetica, questa ricerca punta a definire la lettura come un’esperienza estetica di una variabile e plurale letterarietà, o per essere più precisi, come una relazione estetica ad una funzione nel linguaggio, che di volta in volta diviene immanente e trascendente rispetto al linguaggio, immanente nella percepibilità espressiva del segno e trascendente nella sua ristretta finzionalità o fittività, aperta alla dimensione del senso. Così, la letterarietà è vista, dal punto di vista di una teoria della lettura, come una funzione che nega o sovverte il linguaggio ordinario, inteso come contesto normale, ma anche una funzione che permette il supplemento di senso del linguaggio. Ciò rende la definizione di cosa sia letteratura e di quali testi siano considerabili come letterari come una definizione dipendente dalla lettura, ed anche mette in questione la classica dicotomia tra linguaggio standard e linguaggio deviante, di secondo grado e figurativo, comportamento che distinguerebbe la letteratura. Questi quattro saggi vorrebbero dimostrare che la lettura, come una pratica estetica, è l’espressione di una oscillazione tra una Finzione variabile nei suoi effetti ed una Ricezione, la quale è una risposta estetica controllata dal testo, ma anche una relazione estetica all’artefatto a natura verbale. Solo in questo modo può essere compresa la caratteristica paradossale della lettura, il suo stare tra una percezione passiva ed un’attiva esecuzione, tra un’attenzione aspettuale ed una comprensione intenzionale. Queste modalità si riflettono anche sulla natura dialettica della lettura, come una dialettica di apertura e chiusura, ma anche di libertà e fedeltà, risposta ad uno stimolo che può essere interpretato come una domanda, e che presenta la lettura stessa come una premessa dell’interpretazione, come momento estetico. Così una teoria della lettura dipende necessariamente da una teoria dell’arte che si presenta come funzionale, relativa più al Quando vi è arte?/Come funziona? piuttosto che al Che cosa è Arte?, che rende questo secondo problema legato al primo. Inoltre, questo Quando dell’Arte, che definisce l’opera d’arte come un’arte- all’-opera, dipende a sua volta, in un campo letterario, dalla domanda Quando vi è esperienza estetica letteraria? e dalla sue condizioni, quelle di finzione e ricezione.

Mechanisms of cell senescence: p21 and DNA damage response in aging and longevity

Theory of aging postulates that aging is a remodeling process where the body of survivors progressively adapts to internal and external damaging agents they are exposed to during several decades. Thus , stress response and adaptation mechanisms play a fundamental role in the aging process where the capability of adaptating effects, certainly, also is related the lifespan of each individual. A key gene linking aging to stress response is indeed p21, an induction of cyclin-dependent kinase inhibitor which triggers cell growth arrest associated with senescence and damage response and notably is involved in the up-regulation of multiple genes that have been associated with senescence or implicated in age-related . This PhD thesis project that has been performed in collaboration with the Roninson Lab at Ordway Research Institute in Albany, NY had two main aims: -the testing the hypothesis that p21 polymorphisms are involved in longevity -Evaluating age-associated differences in gene expression and transcriptional response to p21 and DNA damage In the first project, trough PCR-sequencing and Sequenom strategies, we we found out that there are about 30 polymorphic variants in the p21 gene. In addition, we found an haplotpype located in -5kb region of the p21 promoter whose frequency is ~ 2 fold higher in centenarians than in the general population (Large-scale analysis of haplotype frequencies is currently in progress). Functional studies I carried out on the promoter highilighted that the ―centenarian‖ haplotype doesn’t affect the basal p21 promoter activity or its response to p53. However, there are many other possible physiological conditions in which the centenarian allele of the p21 promoter may potentially show a different response (IL6, IFN,progesterone, vitamin E, Vitamin D etc). In the second part, project #2, trough Microarrays we seeked to evaluate the differences in gene expression between centenarians, elderly, young in dermal fibroblast cultures and their response to p21 and DNA damage. Microarray analysis of gene expression in dermal fibroblast cultures of individuals of different ages yielded a tentative "centenarian signature". A subset of genes that were up- or downregulated in centenarians showed the same response to ectopic expression of p21, yielding a putative "p21-centenarian" signature. Trough RQ-PCR (as well Microarrays studies whose analysis is in progress) we tested the DNA damage response of the p21-centenarian signature genes showing a correlation stress/aging in additional sets of young and old samples treated with p21-inducing drug doxorubicin thus finding for a subset of of them , a response to stress age-related.

The role of the Rocky Mountains in shaping the atmospheric mean state and the response to tropical forcing in idealised simulations.

Understanding the natural and forced variability of the atmospheric general circulation and its drivers is one of the grand challenges in climate science. It is of paramount importance to understand to what extent the systematic error of climate models affects the processes driving such variability. This is done by performing a set of simulations (ROCK experiments) with an intermediate complexity atmospheric model (SPEEDY), in which the Rocky Mountains orography is increased or decreased to influence the structure of the North Pacific jet stream. For each of these modified-orography experiments, the climatic response to idealized sea surface temperature anomalies of varying intensity in the El Niño Southern Oscillation (ENSO) region is studied. ROCK experiments are characterized by variations in the Pacific jet stream intensity whose extension encompasses the spread of the systematic error found in Coupled Model Intercomparison Project (CMIP6) models. When forced with ENSO-like idealised anomalies, they exhibit a non-negligible sensitivity in the response pattern over the Pacific North American region, indicating that the model mean state can affect the model response to ENSO. It is found that the classical Rossby wave train response to ENSO is more meridionally oriented when the Pacific jet stream is weaker and more zonally oriented with a stronger jet. Rossby wave linear theory suggests that a stronger jet implies a stronger waveguide, which traps Rossby waves at a lower latitude, favouring a zonal propagation of Rossby waves. The shape of the dynamical response to ENSO affects the ENSO impacts on surface temperature and precipitation over Central and North America. A comparison of the SPEEDY results with CMIP6 models suggests a wider applicability of the results to more resources-demanding climate general circulation models (GCMs), opening up to future works focusing on the relationship between Pacific jet misrepresentation and response to external forcing in fully-fledged GCMs.

On the effect of confounding in linear regression models: an approach based on the theory of quadratic forms

The main topic of this thesis is confounding in linear regression models. It arises when a relationship between an observed process, the covariate, and an outcome process, the response, is influenced by an unmeasured process, the confounder, associated with both. Consequently, the estimators for the regression coefficients of the measured covariates might be severely biased, less efficient and characterized by misleading interpretations. Confounding is an issue when the primary target of the work is the estimation of the regression parameters. The central point of the dissertation is the evaluation of the sampling properties of parameter estimators. This work aims to extend the spatial confounding framework to general structured settings and to understand the behaviour of confounding as a function of the data generating process structure parameters in several scenarios focusing on the joint covariate-confounder structure. In line with the spatial statistics literature, our purpose is to quantify the sampling properties of the regression coefficient estimators and, in turn, to identify the most prominent quantities depending on the generative mechanism impacting confounding. Once the sampling properties of the estimator conditionally on the covariate process are derived as ratios of dependent quadratic forms in Gaussian random variables, we provide an analytic expression of the marginal sampling properties of the estimator using Carlson’s R function. Additionally, we propose a representative quantity for the magnitude of confounding as a proxy of the bias, its first-order Laplace approximation. To conclude, we work under several frameworks considering spatial and temporal data with specific assumptions regarding the covariance and cross-covariance functions used to generate the processes involved. This study allows us to claim that the variability of the confounder-covariate interaction and of the covariate plays the most relevant role in determining the principal marker of the magnitude of confounding.