Multiple imputation and selection of ordinal level 2 predictors in multilevel models. An analysis of the relationship between student ratings and teacher beliefs and practices

The paper is motivated by the analysis of the relationship between ratings and teacher practices and beliefs, which are measured via a set of binary and ordinal items collected by a specific survey with nearly half missing respondents. The analysis, which is based on a two-level random effect model, must face two about the items measuring teacher practices and beliefs: (i) these items level 2 predictors severely affected by missingness; (ii) there is redundancy in the number of items and the number of categories of their measurement scale. tackle the first issue by considering a multiple imputation strategy based on information at both level 1 and level 2. For the second issue, we consider regularization techniques for ordinal predictors, also accounting for the multilevel data structure. The proposed solution combines existing methods in an original way to solve specific problem at hand, but it is generally applicable to settings requiring to select predictors affected by missing values. The results obtained with the final model out that some teacher practices and beliefs are significantly related to ratings about teacher ability to motivate students.Comment: Presented at the 12th International Multilevel Conference is held April 9-10, 2019 , Utrech

Online Banking Satisfaction in Italy - OBS project

The datasets provide information from a questionnaire that investigated customer satisfaction of some online banking services in Italy in May and September 2015

Job-major match and job satisfaction in Italy.

Purpose: This paper aims at studying how graduates\u2019 jobs may be determined by their educational performances and social background. In particular, we investigate job-education mismatch and job satisfaction to evaluate whether time spent and effort exerted during university studies were compensated with a good job. Approach: Data on the occupational status of the graduates 36 months after graduation, collected by the Padua University on its graduates, are analysed by means of univariate and multivariate methodologies. In particular, the pathways from graduates\u2019 social capital to job satisfaction are investigated through a Structural Equation Modelling approach. Findings: We find that a minority of graduates can be considered as overeducated when considering the requirements of the labour market, but many graduates state that any degree would suffice for their job. Multivariate analyses show that graduates\u2019 job quality is related to their university choice and outcome, high school choice and performance, social capital. Destiny is written from the beginning of the educational pathway, but students can affect their labour market future with an appropriate choice of university programme. Originality: The qualified point of this paper lies on the complexity of the model adopted for the analysis and its ability to highlight direct and indirect effects: two job outcomes (job-major match and job satisfaction) are the variables of interest, analysed within a structural model covering all educational stages of the Italian educational pathway, from parental social background to University degree

Cross-Country Differentials in Work Disability Reporting Among Older Europeans

Descriptive evidence shows that there is large cross-country variation in self-reported work disability rates of the elderly in Europe. In this paper we analyse whether these differences are genuine or they just reflect heterogeneity in reporting styles. To shed light on the determinants of work-disability differentials across countries, we combine a wide set of individuals’ socioeconomic and health status characteristics with macro-economic indicators describing the institutional background of the country of residence

A model-driven approach to better identify older people at risk of depression

Depression in later life is one of the most common mental disorders. Several instruments have been developed to detect the presence or the absence of certain symptoms or emotional disorders, based on cut-off points. However, the use of a cut-off does not allow identification of depression sub-types or distinguish between mild and severe depression. As a result, depression may be under- or over-diagnosed in older people. This paper aims to apply a model-driven approach to classify individuals into distinct sub-groups, based on different combinations of depressive and emotional conditions. This approach is based on two distinct statistical solutions: first, a latent class analysis is applied to the items collected by the depression scale and, according to the final model, the probability of belonging to each class is calculated for every individual. Second, a factor analysis of these classes is performed to obtain a reduced number of clusters for easy interpretation. We use data collected through the EURO-D scale in a large sample of older individuals, participants of the sixth wave of the Survey of Health, Ageing and Retirement in Europe. We show that by using such a model-based approach it is possible to classify individuals in a more accurate way than the simple dichotomisation ‘depressed’ versus ‘non-depressed’

Supportive care for older people with dementia: socio-organisational implications

For many years, dementia care has been dominated by the standard medical approach, in which dementia is treated mainly with drugs, such as anti-anxiety, antidepressant and anti-psychotic medications. With the aim of seeking effective treatments for patients with dementia, over the last years, several contributions have criticised the pervasive use of drugs for the management of behavioural and physiological symptoms related to dementia, proposing personalised interventions aimed at supporting patients and their relatives from diagnosis until death. With particular reference to long-term settings, in this work, we aim at understanding the organisational implications of three types of interventions (labelled supportive care interventions – SCIs) that have characterised this shift in dementia care: person-centred, palliative and multi-disciplinary care. Conducted by following the integrative review method, our review underlines how SCIs have controversial consequences on the quality of care, the care-givers’ quality of life and cultural backgrounds. After an in-depth analysis of selected papers, we offer some considerations about the implications of SCIs for long-term care organisations and future research directions

Early-life circumstances and late-life income

This paper aims at evaluating and comparing across European countries the influence of early-life circumstances, like childhood disparities and educational attainments, on incomes in later life. Using life-history data from SHARELIFE, country-specific structural relationships among childhood socio-economic status, education and incomes at the first and the last job are investigated by means of recursive models, controlling for individual covariates. Poorer childhood socio-economic conditions are associated with higher differentials in years of full-time education and higher income inequalities. The extent of these results varies across countries

Early-life circumstances and late-life income

This paper aims at evaluating and comparing across European countries the influence of early-life circumstances, like childhood disparities and educational attainments, on incomes in later life. Using life-history data from SHARELIFE, country-specific structural relationships among childhood socio-economic status, education and incomes at the first and the last job are investigated by means of recursive models, controlling for individual covariates. Poorer childhood socio-economic conditions are associated with higher differentials in years of full-time education and higher income inequalities. The extent of these results varies across countries