Luis Nobre Pereira

How consistent are health utility values

The use of preference-based generic instruments to measure the health-related quality of life of a general population or of individuals suffering from a specific disease has been increasing. However, there are several discrepancies between instruments in terms of utility results. This study compares SF-6D and EQ-5D when administered to patients with cataracts and aims at explaining the differences. Agreement between EQ-5D and SF-6D health state classifications was assessed by correlation coefficients. Simple correspondence analysis was used to assess the agreement among the instrument’s descriptive systems and to investigate similarities between dimensions’ levels. Cluster analysis was used to classify SF-6D and EQ-5D levels into homogeneous groups. There was evidence of floor effects in SF-6D and ceiling effects in EQ-5D. Comparisons of means showed that SF-6D values exceeded EQ-5D values. Agreement between both instruments was high, especially between similar dimensions. However, different valuation methods and scoring algorithms contributed to the main differences found. We suggest that one or both instruments should be revised, in terms of their descriptive systems or their scoring algorithms, in order to overcome the weakness found.

A portuguese value set for the SF-6D

OBJECTIVES The SF-6D is a preference-based measure of health derived from the SF-36 that can be used for cost-effectiveness analysis using cost-per-quality adjusted life-year analysis. This study seeks to estimate a system weight for the SF-6D for Portugal and to compare the results with the UK system weights. METHODS A sample of 55 health states defined by the SF-6D has been valued by a representative random sample of the Portuguese population, stratified by sex and age (n = 140), using the Standard Gamble (SG). Several models are estimated at both the individual and aggregate levels for predicting health-state valuations. Models with main effects, with interaction effects and with the constant forced to unity are presented. Random effects (RE) models are estimated using generalized least squares (GLS) regressions. Generalized estimation equations (GEE) are used to estimate RE models with the constant forced to unity. Estimations at the individual level were performed using 630 health-state valuations. Alternative functional forms are considered to account for the skewed distribution of health-state valuations. RESULTS The models are analyzed in terms of their coefficients, overall fit, and the ability for predicting the SG-values. The RE models estimated using GLS and through GEE produce significant coefficients, which are robust across model specification. However, there are concerns regarding some inconsistent estimates, and so parsimonious consistent models were estimated. There is evidence of under prediction in some states assigned to poor health. The results are consistent with the UK results. CONCLUSION The models estimated provide preference-based quality of life weights for the Portuguese population when health status data have been collected using the SF-36. Although the sample was randomly drowned findings should be treated with caution, given the small sample size, even knowing that they have been estimated at the individual level.

An application of the SF-6D to create heath values in Portuguese working age adults

Objectives: This study describes the health-related quality of life (HRQOL) of the Portuguese working age population and investigates sociodemographic differences. Methods: Subjects randomly selected from the working age population (n=2,459) were assessed using the SF-36v2 and converted into the preference-based SF-6D. Results: The mean SF-6D utility value was 0.70 (range 0.63–0.73). The mean utility value was lower for the lower educational level than for the highest. Women, people living in rural areas and older adults reported lower levels of utility values. Non-parametric tests showed that health utility values were significantly related to employment; unskilled manual workers reported utility values lower than non-manual workers. For different diseases, mean utility values ranged from 0.58 (sexual diseases) to 0.66 (hepatic conditions). Cluster analysis was adopted to classify individuals into three groups according to their answers to the SF-6D dimensions. Multinomial logit regression was used to detect sociodemographic characteristics affecting the probability of following each cluster pattern. This study yielded normative data by age and gender for the SF-6D. Conclusions: The authors conclude that SF-6D is an effective tool for measuring HRQOL in the community so that different population groups can be compared. The preference-based measure used seems to discriminate adequately across sociodemographic differences. These results allow a better understanding of the impact of sociodemographic variables on the burden of illness perception. A previous version of this paper was presented at the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 8th Annual European Congress held at Florence, Italy in November 2005.

Photogrowth: non-photorealistic renderings through ant paintings

We introduce photogrowth, an evolutionary approach to the production of non-photorealistic renderings of images. The painting algorithm - inspired by ant colony approaches - is described and explained, giving emphasis to its novel aspects: the evolution of the sensory parameters of the ants; the production of resolution independent images; the rendering lines of variable width. The experimental results highlight the range of imagery that can be evolved by the system and show the potential of the approach for the production of large-format artworks.

Assessing different uncertainty measures of EBLUP: a resampling-based approach

The empirical best linear unbiased prediction approach is a popular method for the estimation of small area parameters. However, the estimation of reliable mean squared prediction error (MSPE) of the estimated best linear unbiased predictors (EBLUP) is a complicated process. In this paper we study the use of resampling methods for MSPE estimation of the EBLUP. A cross-sectional and time-series stationary small area model is used to provide estimates in small areas. Under this model, a parametric bootstrap procedure and a weighted jackknife method are introduced. A Monte Carlo simulation study is conducted in order to compare the performance of different resampling-based measures of uncertainty of the EBLUP with the analytical approximation. Our empirical results show that the proposed resampling-based approaches performed better than the analytical approximation in several situations, although in some cases they tend to underestimate the true MSPE of the EBLUP in a higher number of small areas.

A Small Area Predictor under Area-Level Linear Mixed Models with Restrictions

A calibrated small area predictor based on an area-level linear mixed model with restrictions is proposed. It is showed that such restricted predictor, which guarantees the concordance between the small area estimates and a known estimate at the aggregate level, is the best linear unbiased predictor. The mean squared prediction error of the calibrated predictor is discussed. Further, a restricted predictor under a particular time-series and cross-sectional model is presented. Within a simulation study based on real data collected from a longitudinal survey conducted by a national statistical office, the proposed estimator is compared with other competitive restricted and non-restricted predictors.

Small area estimation of mean price of habitation transaction using time-series and cross-sectional area-level models

In this paper, a new small domain estimator for area-level data is proposed. The proposed estimator is driven by a real problem of estimating the mean price of habitation transaction at a regional level in a European country, using data collected from a longitudinal survey conducted by a national statistical office. At the desired level of inference, it is not possible to provide accurate direct estimates because the sample sizes in these domains are very small. An area-level model with a heterogeneous covariance structure of random effects assists the proposed combined estimator. This model is an extension of a model due to Fay and Herriot [5], but it integrates information across domains and over several periods of time. In addition, a modified method of estimation of variance components for time-series and cross-sectional area-level models is proposed by including the design weights. A Monte Carlo simulation, based on real data, is conducted to investigate the performance of the proposed estimators in comparison with other estimators frequently used in small area estimation problems. In particular, we compare the performance of these estimators with the estimator based on the Rao–Yu model [23]. The simulation study also accesses the performance of the modified variance component estimators in comparison with the traditional ANOVA method. Simulation results show that the estimators proposed perform better than the other estimators in terms of both precision and bias.

Determinants for the commitment relationship maintenance between the alumni and the alma mater

ABSTRACT This study aims to find determinants for the commitment relationship between alumni and alma mater. Based on the literature, satisfaction and image are proposed as drivers of commitment. A survey applied to 2544 alumni in a Portuguese university provides data analyzed through a structural equation modeling technique. The results present ‘image of education’, ‘image of communication’ and ‘satisfaction with social and academic environment’ as determinants of the commitment relationship, which provide important clues for the marketers’ decision-making process when developing activities geared towards alumni. This process should emphasize aspects relating to their willingness to give back, academic and relationship quality, and institutional values. Within the Higher Education market, this study underscores the need to maintain and reinforce the relationship with alumni, and contributes to the scarce Portuguese literature on alumni matters.

Perdas por imparidade: fatores explicativos e impactos

Purpose – To analyze recognition of impairment losses in tangible and intangible assets, and their relevance to investors in companies listed in the Lisbon and Madrid Stock Exchange (2007-2011). Methodology – Quantitative analysis of a panel data sample of 80 companies listed in the Lisbon and Madrid Stock Exchange (20072011) was carried out. Panel data linear and non-linear regression models were estimated. Findings – We found that the amount of impairment losses showed an upward trend, and that these losses are most significant among intangibles, especially goodwill (GW). We also found that the probability of recognition of impairment losses is positively influenced by the dimension of entities and negatively by market value (p < 0.10). Portuguese export-oriented companies have a higher probability of not recognizing impairments. However, Portuguese companies with higher market values have greater probability of recognizing impairment losses, contrary to the sample as a whole, in which the relationship is negative (p < 0.10). The results also suggest that there is a smoothing effect on results because of impairments, especially in IBEX35 companies. As to the relevance of impairment losses to market value, we confirm a significant negative relationship, in line with conclusions from previous studies. Originality/value – This study contributes to the introduction of the cultural factor in this analysis, highlighting the differentiated behaviors between Portuguese and Spanish companies.

The Attractiveness of Portugal as a Tourist Destination: The Perspective of Czech Tour Operators

ABSTRACT In this study we investigate the attractiveness of Portugal as a tourist destination from the perspective of Czech tour operators. Tour operators were selected as the target population because they represent an important source of information about a destination and can significantly influence the decision of potential tourists about a holiday destination. One of the important findings of this research is that weak promotion and financial demands are perceived as the main reasons why many Czech tourists do not choose Portugal as their vacation destination. An obvious obstacle in the development of Portugal as a Czech tourism destination is the lack of information about its advantages as a tourist destination. The results also show that Portugal is not considered a key destination for Czech tourists. However, in terms of its attractiveness as a tourist destination Portugal has much potential, which should be utilized in the future.