The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution. / Lo scopo di questa tesi è quello di applicare il modello di regressione multilivello nel contesto di indagini sulle famiglie. La struttura gerarchica in questo tipo di dati è caratterizzato da numerosi piccoli gruppi. Negli ultimi anni analisi comparative e multilivello sullo stato di salute percepito sono aumentate molto. L’obiettivo di questa tesi è di applicare un'analisi multilivello a tre livelli per la variabile risposta Physical Component Summary allo scopo di: valutare entità all'interno e tra varianza ad ogni livello (individuale, familiare e comune); indagare quali covariate influiscono sulla percezione dello stato di salute fisica ogni livello; confrontare le analisi model-based e di design-based al fine di stabilire se i pesi campionari siano informativiti per il modello di interesse; stimare una regressione quantile per i dati gerarchici. La popolazione target sono i residenti italiani di età compresa tra 18 anni. Il nostro studio rileva un’elevata omogeneità tra le unità di livello 1 e una correlazione intraclasse del 27% nel modello nullo a 2livelli. Quasi tutta la varianza è spiegata dalle covariate di livello. Nel nostro modello le variabili esplicative hanno un impatto maggiore sulla variabile risposta sono la disabilità, inabilità al lavoro, l’età e le malattie croniche (18 patologie). Un'ulteriore analisi viene eseguita utilizzando una nuova procedura di analisi: "Regressione lineare quantile multilivello”. Questa analisi ci dà la possibilità di descrivere più in generale la distribuzione condizionata della variabile risposta attraverso la stima dei suoi quantili. Questo ha portato un grande vantaggio nei nostri modelli rispetto al classico modello di regressione multilivello. La regressione mediana con effetti casuali si rivela più efficiente del regressione media nella rappresentazione della tendenza centrale. Un'analisi più dettagliata della distribuzione condizionata della variabile risposta in corrispondenza di altri quantili ha evidenziato che certe covariate hanno un effetto diverso lungo la distribuzione.

Dealing with latent constructs (loaded by reflective and congeneric measures) cross-culturally compared means studying how these unobserved variables vary, and/or covary each other, after controlling for possibly disturbing cultural forces. This yields to the so-called ‘measurement invariance’ matter that refers to the extent to which data collected by the same multi-item measurement instrument (i.e., self-reported questionnaire of items underlying common latent constructs) are comparable across different cultural environments. As a matter of fact, it would be unthinkable exploring latent variables heterogeneity (e.g., latent means; latent levels of deviations from the means (i.e., latent variances), latent levels of shared variation from the respective means (i.e., latent covariances), levels of magnitude of structural path coefficients with regard to causal relations among latent variables) across different populations without controlling for cultural bias in the underlying measures. Furthermore, it would be unrealistic to assess this latter correction without using a framework that is able to take into account all these potential cultural biases across populations simultaneously. Since the real world ‘acts’ in a simultaneous way as well. As a consequence, I, as researcher, may want to control for cultural forces hypothesizing they are all acting at the same time throughout groups of comparison and therefore examining if they are inflating or suppressing my new estimations with hierarchical nested constraints on the original estimated parameters. Multi Sample Structural Equation Modeling-based Confirmatory Factor Analysis (MS-SEM-based CFA) still represents a dominant and flexible statistical framework to work out this potential cultural bias in a simultaneous way. With this dissertation I wanted to make an attempt to introduce new viewpoints on measurement invariance handled under covariance-based SEM framework by means of a consumer behavior modeling application on functional food choices.

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Eight methods were evaluated to assess potential soil S-supply to crops, and particularly to identify deficiencies in S-supply. Of these methods, three novel bioassays (sulphate production from incubation of amino acid-amended and elemental S-amended soil, and tissue S-concentrations of plants) proved better indicators (based on correlation with field crop response to S-fertilization) of S-supply than data from traditional chemical extractions. The above experiment was limited by the few soils (10) for which field S-response data was available. A second experiment was conducted with 54 soils using 6 of the 8 methods tested initially. Although no field data was available, a vast array of statistical procedures were performed which demonstrated that bioassays of soil S-supply produced related data sets but with no relation to data sets from chemical extractions. Consistent outlying of data for 2 Bangladesh soils in this experiment suggested an interesting apparent difference in the S-supply characteristics of temperate and tropical soils. The next phase of research aimed to investigate fertilizer S-supply to crops in soil. Firstly, the performance of gypsum and elemental-S were compared. Increased grain yield of barley was only achieved by gypsum application, although enhanced trace element nutrition from elemental S suggested that S-fertilization of crops influences the quality as well as the quantity of crop product. In a further pot experiment, enhancement of barley grain yield due to fertilizer S application was found only for crops grown on S-deficient soil. By labelling gypsum with ³⁵S, the fate of fertilizer in a soil/grass system was assessed. Over 4 cuts in a 12 week period, grass removed about half of applied ³⁵S with a further quarter left in the soil. The remainder was both in the roots and lost from the system. Less than 1 per cent of applied ³⁵S was recovered from microbial biomass. The final experiment investigatead the method for determining S-content of the soil microbial biomass, highlighting the need for effective chloroform removal from soil and the importance of a suitable control (a non-fumigated but evacuated soil was suggested).

This doctoral thesis is devoted to the study of the causal effects of the maternal smoking on the delivery cost. The interest of economic consequences of smoking in pregnancy have been studied fairly extensively in the USA, and very little is known in European context. To identify the causal relation between different maternal smoking status and the delivery cost in the Emilia-Romagna region two distinct methods were used. The first - geometric multidimensional - is mainly based on the multivariate approach and involves computing and testing the global imbalance, classifying cases in order to generate well-matched comparison groups, and then computing treatment effects. The second - structural modelling - refers to a general methodological account of model-building and model-testing. The main idea of this approach is to decompose the global mechanism into sub-mechanisms though a recursive decomposition of a multivariate distribution.

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The person of the counsellor, or what is sometimes referred to as the counsellor�s self, is the focus of this thesis. How the counsellor�s self is described and manifested during therapy constitute the two main research questions. Various perspectives are presented from psychoanalysis, behaviour therapy, cognitive behaviour therapy, person centered therapy and systems therapy. While issues pertaining to the counsellor�s self have been explored predominately by systems therapists, this study extends previous research by involving interviews with counsellors from a range of orientations. The study is conducted within an interpretative research paradigm, and data are collected and interpreted according to a qualitative approach. Semi-structured interviews with 16 counsellors, from a range of theoretical orientations, constitute the primary method of data collection. Other data sources include a short questionnaire sent to the same counsellors, the researcher�s reflective journal as well as recorded meetings between a peer debriefer and the researcher. Study participants describe the counsellor�s self as a multifaceted, positive and integrated entity. The counsellor�s self includes participant�s professional knowledge and skills as well as their beliefs, values, thoughts, feelings, personal style and an unknown aspect of self that some participants referred to as their unconscious. While somewhat influenced by past relationships and the client, the counsellor�s self is primarily autonomous and defined by the individual counsellor. Although the counsellor�s self has the capacity to change over time, in different environments and with different clients, the self also includes notions of stability and consistency. The counsellor�s self is involved in therapy as an inevitable presence, a deliberate tool and a stance. Participants highlighted the importance of self-awareness and various professional and personal constraints on the involvement of self. A central function of the self in therapy is in the therapeutic alliance. The study has implications for the training and supervision of counsellors and future psychotherapeutic research.

Thesis (B.A. (Hons.))--University of Adelaide, (1988?). / Includes bibliographical references (leaves 92-95).