Limited Dependent Variable Model Research Articles

Mapping from SIBDQ to EQ-5D-5L for patients with inflammatory bowel disease

ObjectiveClinical studies commonly use disease-specific measures to assess patients’ health-related quality of life. However, economic evaluation often requires preference-based utility index scores to calculate cost per quality-adjusted life-year (QALY). When utility index scores are not directly available, mappings are useful. To our knowledge, no mapping exists for the Short Inflammatory Bowel Disease Questionnaire (SIBDQ). Our aim was to develop a mapping from SIBDQ to the EQ-5D-5L index score with German weights for inflammatory bowel disease (IBD) patients.MethodsWe used 3856 observations of 1055 IBD patients who participated in a randomised controlled trial in Germany on the effect of introducing regular appointments with an IBD nurse specialist in addition to standard care with biologics. We considered five data availability scenarios. For each scenario, we estimated different regression and machine learning models: linear mixed-effects regression, mixed-effects Tobit regression, an adjusted limited dependent variable mixture model and a mixed-effects regression forest. We selected the final models with tenfold cross-validation based on a model subset and validated these with observations in a validation subset.ResultsFor the first four data availability scenarios, we selected mixed-effects Tobit regressions as final models. For the fifth scenario, mixed-effects regression forest performed best. Our findings suggest that the demographic variables age and gender do not improve the mapping, while including SIBDQ subscales, IBD disease type, BMI and smoking status leads to better predictions.ConclusionWe developed an algorithm mapping SIBDQ values to EQ-5D-5L index scores for different sets of covariates in IBD patients. It is implemented in the following web application: https://www.bwl.uni-hamburg.de/hcm/forschung/mapping.html.

Facing the storm: Lessons from corporate social responsibility during the covid pandemic

AbstractThis study analyzes the impact on the sustainability performance of firms during the outbreak of the COVID‐19 pandemic, based on microdata made available by the World Bank through the Enterprise Surveys platform. By employing econometric estimation techniques like multinomial limited dependent variable model alongside data visualization tools, this analysis provides insights into the effects of the pandemic outbreak, as well as the moderating influence of enterprise innovation levels and CSR. The findings highlight that the duration of firm operations and company size play significant roles in mitigating turnover during the initial response to the pandemic. The analysis evaluates the actions taken by companies and governments to navigate the crisis, one and a half years after its appearance: containing the impact has a strong social impact, related to corporate social responsibility. The companies that successfully contained the shock and recovered more quickly are those that relied on innovation through their private investments or government measures. The analysis reveals how evenly distributed government subsidies have failed to produce significant effects.

Mapping health assessment questionnaire disability index onto EQ-5D-5L in China.

This research aimed to develop the more accurate mapping algorithms from health assessment questionnaire disability index (HAQ-DI) onto EQ-5D-5L based on Chinese Rheumatoid Arthritis patients. The cross-sectional data of Chinese RA patients from 8 tertiary hospitals across four provincial capitals was used for constructing the mapping algorithms. Direct mapping using Ordinary least squares regression (OLS), the general linear regression model (GLM), MM-estimator model (MM), Tobit regression model (Tobit), Beta regression model (Beta) and the adjusted limited dependent variable mixture model (ALDVMM) and response mapping using Multivariate Ordered Probit regression model (MV-Probit) were carried out. HAQ-DI score, age, gender, BMI, DAS28-ESR and PtAAP were included as the explanatory variables. The bootstrap was used for validation of mapping algorithms. The average ranking of mean absolute error (MAE), root mean square error (RMSE), adjusted R 2 (adjR 2) and concordance correlation coefficient (CCC) were used to assess the predictive ability of the mapping algorithms. According to the average ranking of MAE, RMSE, adjR 2, and CCC, the mapping algorithm based on Beta performed the best. The mapping algorithm would perform better as the number of variables increasing. The mapping algorithms provided in this research can help researchers to obtain the health utility values more accurately. Researchers can choose the mapping algorithms under different combinations of variables based on the actual data.

Analysis of spatial and temporal characteristics of carbon emission efficiency of pig farming and the influencing factors in China.

Pig farming has been a crucial contribution to China's food security although intestinal fermentation and its excrement during pig breeding are major sources of greenhouse gas emissions. In this paper, we measured the carbon emission efficiency of pig farming in 30 provinces (autonomous regions and municipalities) from 2010 to 2020 by using the non-expected output Slack-Based Measure (SBM) model and analyzed the spatial characteristics of the carbon emission efficiency of pig farming in China. We also examined and analyzed the factors influencing the carbon emission efficiency of pig farming by using the limited dependent variable model (Tobit). The results show that: the carbon emission efficiency of pig farming in China shows an M-shaped upward trend over time by comparing the carbon emission efficiency longitudinally during the study period and the carbon emission efficiency of pig farming shows a decreasing trend in the east, central and west regions of China by comparing the carbon emission efficiency of different regions horizontally. It's also shown that regions with low- and extremely-low-efficiency transfer from the east to the central and west regions and the central and regions with high-efficiency transfer to the east. The regression analysis of the factors influencing the carbon emission efficiency of pig breeding shows that the comparative advantage of the pig industry and transportation accessibility is positively correlated with the carbon emission efficiency of pig breeding, whereas the proportion of food resources and market scale is negatively correlated with the carbon emission efficiency of pig breeding. At the same time, the production layout index has no significant influence on the carbon emission efficiency of pig breeding. The research results provide a theoretical basis for regional differentiation of carbon emission management from pig farming, optimizing the layout of the pig industry and reducing environmental pollution.

Mapping the Insomnia Severity Index Instrument to EQ-5D Health State Utilities: A United Kingdom Perspective.

This study aimed to map the Insomnia Severity Index (ISI) to the EQ-5D-3L utility values from a UK perspective. Source data were derived from the 2020 National Health and Wellness Survey (NHWS) for France, Germany, Italy, Spain, the UK and the US. Ordinary least squares regression, generalised linear model (GLM), censored least absolute deviation, and adjusted limited dependent variable mixture model (ALDVMM) were employed to explore the relationship between ISI total summary score and EQ-5D utility while accounting for adjustment covariates derived from the NHWS. Fitting performance was assessed using standard metrics, including mean-squared error (MSE) and coefficient of determination (R2). A total of 17,955 respondent observations were included, with a mean ISI score of 12.12±5.32 and a mean EQ-5D-3L utility (UK tariff) of 0.71±0.23. GLM gamma-log and ALDVMM were the two best performing models. The ALDVMM had better fitting performance (R2=0.320, MSE 0.0347) than the GLM gamma-log (R2=0.303, MSE 0.0353); in train-test split-sample validation, ALDVMM also slightly outperformed the GLM gamma-log model, with an MSE of 0.0351 versus 0.0355. Based on fitting performance, ALDVMM and GLM gamma-log were the preferred models. In the absence of preference-based measures, this study provides an updated mapping algorithm for estimating EQ-5D-3L utilities from the ISI summary total score. This new mapping not only draws its strengths from the use of a large international dataset but also the incorporation of adjustment variables (including sociodemographic and general health characteristics) to reduce the effects of confounders.

Mapping the Patient-Reported Outcomes Measurement Information System (PROMIS-29) to EQ-5D-5L.

The Patient-Reported Outcomes Measurement Information System (PROMIS-29) is gaining popularity as healthcare system funders increasingly seek value-based care. However, it is limited in its ability to estimate utilities and thus inform economic evaluations. This study develops the first mapping algorithm for estimating EuroQol 5-Dimension 5-Level (EQ-5D-5L) utilities from PROMIS-29 responses using a large dataset and through extensive comparisons between econometric models. An online survey was conducted to collect responses to PROMIS-29 and EQ-5D-5L from the general Australian population (N = 3013). Direct and indirect mapping methods were explored, including linear regression, Tobit, generalised linear model, censored regression model, beta regression (Betamix), the adjusted limited dependent variable mixture model (ALDVMM) and generalised ordered logit. The most robust model was selected by assessing the performance based on average ten-fold cross-validation geometric mean absolute error and geometric mean squared error, the predicted mean, maximum and minimum utilities, as well as the fitting across the entire distribution. The direct approach using ALDVMM was considered the preferred model based on lowest geometric mean absolute error and geometric mean squared error in cross-validation (0.0882, 0.0299) and its superiority in predicting the actual observed mean, full health states and lower utility extremes. The robustness and precision in prediction across the entire distribution of utilities with ALDVMM suggest it is an accurate and valid mapping algorithm. Moreover, the suggested mapping algorithm outperformed previously published algorithms using Australian data, indicating the validity of this model for economic evaluations. This study developed a robust algorithm to estimate EQ-5D-5L utilities from PROMIS-29. Consistent with the recent literature, the ALDVMM outperformed all other econometric models considered in this study, suggesting that the mixture models have relatively better performance and are an ideal candidate model for mapping.

An examination of machine learning to map non-preference based patient reported outcome measures to health state utility values.

Non‐preference‐based patient‐reported outcome measures (PROMs) are popular in health outcomes research. These measures, however, cannot be used to estimate health state utilities, limiting their usefulness for economic evaluations. Mapping PROMs to a multi‐attribute utility instrument is one solution. While mapping is commonly conducted using econometric techniques, failing to specify the complex interactions between variables may lead to inaccurate prediction of utilities, resulting in inaccurate estimates of cost‐effectiveness and suboptimal funding decisions. These issues can be addressed using machine learning. This paper evaluates the use of machine learning as a mapping tool. We adopt a comprehensive approach to compare six machine learning techniques with eight econometric techniques to map the Patient‐Reported Outcomes Measurement Information System Global Health 10 (PROMIS‐GH10) to the EuroQol five dimensions (EQ‐5D‐5L). Using data collected from 2015 Australians, we find the least absolute shrinkage and selection operator (LASSO) model out‐performed all machine learning techniques and the adjusted limited dependent variable mixture model (ALDVMM) out‐performed all econometric techniques, with the LASSO performing better than ALDVMM. The variable selection feature of LASSO was then used to enhance the performance of the ALDVMM in a hybrid model. Our analysis identifies the potential benefits and challenges of using machine learning techniques for mapping and offers important insights for future research.

Health-related quality of life among adult patients with visual impairments in Yazd, Iran.

BACKGROUND:Visual impairment (VI) is one of the major public health problems that cause suffering, disability, loss of productivity, and reduced quality of life (QoL). This study aimed to evaluate the health-related QoL (HRQoL) among adults with visual problems in 2021.MATERIALS AND METHODS:This analytical cross-sectional study was conducted on 300 patients with VIs referring to ophthalmology centers in Yazd, Iran. Data were collected through face-to-face interviews using EQ-5D, visual analog scale (VAS), and demographic information questionnaires. The results were analyzed using independent sample t-test, one-way analysis of variance, Pearson correlation coefficient, and adjusted limited dependent variable mixture model (ALDVMM) model by STATA, and SPSS.RESULTS:The mean and standard deviation of EQ-5D-5 L index and EQ-VAS score in the studied patients were 0.68 ± 0.25 and 72.46 ± 19.36, respectively. Most problems at unable/extreme level were related to the mobility dimension (12%) and the usual activities dimension (9%). Factors related to HRQoL scores using ALDVMM model showed that divorced or widow marital status, age over 50, having strabismus, and acuter visual problems had significant negative effects on EQ-5D-5 L index values (P < 0.05).CONCLUSIONS:The results showed that HRQoL was moderate in patients with VIs and reduced in patients with high disease severity, old age, lack of a spouse, retirement, and nonuniversity education. As a result, socioeconomic and demographic characteristics were required to be considered in visual health policies.

Mapping the Haem-A-QoL to the EQ-5D-5L in patients with hemophilia.

This study's objective was to develop an algorithm that mapping the Haem-A-QoL scores to EQ-5D-5L utility scores in patients with hemophilia in China. A national sample of 862 patients with hemophilia completed both the EQ-5D-5L and Haem-A-QoL instruments. Eight regression models were selected to develop the mapping algorithm, they were: the ordinary least squares, general linear regression, Tobit regression, censored least absolute deviation, mixture beta regression, adjusted limited dependent variable mixture, the two-part, and robust MM-estimator model. Root mean squared error (RMSE), mean absolute error (MAE), and R-square (R2) calculated using the tenfold cross-validation and random sample validation methods were used to assess the predictive ability of the models. Based on RMSE, MAE, and R2, the mixture beta regression model with selected Haem-A-QoL subscale scores as the predicted variables showed the best performance. Our mapping algorithm bolsters the calculation of QALYs while conducting an economic evaluation of hemophilia-related interventions when only Haem-A-QoL data are available. The external validity of the algorithm should be further assessed in the other populations.

Movimentos de Emigração de Mulheres Rurais em Itapejara d’Oeste/PR: enfrentando relações de poder patriarcais

Este artigo analisa as relações de poder, saber e ser que, desde o colonialismo, constituíram hierarquias em torno das classificações de gênero. Nossa cultura rotula como não civilizada e não humana aquelas(es) que não se enquadram no modelo hegemônico, esse rótulo é usado para entender o papel da mulher no meio rural. Nas áreas rurais, as mulheres modernas buscam romper com as relações de poder estabelecidas, procuram maior independência e acesso à liderança pública. Diante dessas questões, vale a pena perguntar: quais são os fatores que empoderam as mulheres rurais? Observa-se que a escolaridade e as alternativas de renda não agrícola possibilitam quebrar sua invisibilidade nos estabelecimentos rurais. Para a construção da análise, são apresentados os dados estatísticos de uma amostra de 95 casos da população rural de Itapejara d'Oeste/PR, cujo levantamento inicial foi realizado em 2005 e posteriormente atualizado em 2010 e 2015, nesta análise, utilizou-se de ferramentas econométricas, com base no modelo de variável limitada dependente (MVLD). Os resultados indicaram a ocorrência de uma maior emigração de mulheres relacionadas à maior escolaridade, bem como uma redução dessa emigração quando as mulheres passaram a ter maior acesso a rendimentos não agrícolas no meio rural. Ambas as formas de acesso ao espaço público deram às mulheres rurais maior independência e provavelmente ajudaram a sair de sua invisibilidade.

Health-related quality of life and its associated factors in patients with type 2 diabetes mellitus.

Background:Assessing the health-related quality of life in patients with type 2 diabetes mellitus is important for evaluation of treatment outcome. The purpose of this study was to evaluate the health-related quality of life in type 2 diabetes mellitus patients and its related factors in Yazd.Methods:Data were gathered by using the EuroQoL-five-dimension-5 level instrument as well as using medical records of 734 outpatients with type 2 diabetes mellitus who were referred to the largest governmental diabetes center in South of Iran, Yazd province. When appropriate, the Kruskal–Wallis test or the Wilcoxon test was used to test the difference in the health-related quality-of-life scores in each factor. Finally, the adjusted limited dependent variable mixture model was developed to investigate factors associated with health-related quality-of-life scores.Results:The mean and median of the EuroQoL-five-dimension-5 level index values of 717 patients who completed the questionnaires were 0.75 ± 0.006 and 0.72 ± 0.20, respectively, and those of the Visual Analogue Scale scores were 69.25 ± 0.63 and 75 ± 30, respectively. The mean scores for health-related quality of life were significantly higher for employed, educated, single, and male patients, as well as patients without comorbidities, diabetes-related complications, and hemoglobin A1c level >7%. Adjusted limited dependent variable mixture model showed that gender, age, marital status, and diabetes-related complications are significant independent predictors of EuroQoL-five-dimension-5 level index value.Conclusion:The mean scores for health-related quality of life in patients with type 2 diabetes mellitus were moderate in this study, and this finding is consistent with health-related quality-of-life scores reported in other studies conducted in the Middle East region. Therefore, health-related quality of life should be the most important consideration in the management of patients. In parallel, some factors, especially gender, should be considered to improve health-related quality of life.

Distribution Approximation of Shrinkage Estimate in Censored Regression Model via Randomly Weighting Method

Censored regression (“Tobit”) model is a special case of limited dependent variable regression model, and plays an important role in econometrics. Based on this model, all kinds of methods for variable or group variable selection have been developed and the corresponding shrinkage parameter estimates are widely studied. However, asymptotic distributions of the shrinkage estimates involve unknown nuisance parameters, such as density function of error term. To avoid estimating nuisance parameters, this paper presents a randomly weighting method to approximate to the asymptotic distribution of the shrinkage estimate. A computation procedure of random approximation is provided and asymptotic properties of the randomly weighting estimates are also obtained. The proposed methods are evaluated with extensively numerical studies and a women labor supply example.

Health State Preference Weights for the Glasgow Outcome Scale Following Traumatic Brain Injury: A Systematic Review and Mapping Study.

BackgroundValid and relevant estimates of health state preference weights (HSPWs) for Glasgow Outcome Scale (GOS) categories are a key input of economic models evaluating treatments for traumatic brain injury (TBI).ObjectivesTo characterize existing HSPW estimates, and model the EuroQol five-dimensional questionnaire (EQ-5D) from the GOS, to inform parameterization of future economic models.MethodsA systematic review of HSPWs for GOS categories following TBI was conducted using a highly sensitive search strategy implemented in an extensive range of information sources between 1975 and 2016. A cross-sectional mapping study of GOS health states onto the three-level EQ-5D UK tariff index values was also performed in patients with significant TBI (head region Abbreviated Injury Scale score ≥3) from the Victoria State Trauma Registry. A limited dependent variable mixture model was used to estimate the 12-month EQ-5D UK value set as a function of GOS category, age, and other explanatory variables.ResultsSix unique HSPWs from five eligible studies were identified. All studies were at high risk of bias with limited applicability. The magnitude of HSPWs differed significantly between studies. Three class mixture models demonstrated excellent goodness of fit to the observed Victoria State Trauma Registry data. GOS category, age at injury, sex, comorbidity, and major extracranial injury all had significant independent effects on mean EQ-5D utility values.ConclusionsThe few available HSPWs for GOS categories are challenged by potential biases and restricted generalizability. Mixture models are presented to provide HSPWs for GOS categories consistent with the National Institute for Health and Care Excellence reference case.

Towards a liberalised European rail transport: Analysing and modelling the impact of competition on productive efficiency

This paper contributes to the railway benchmarking literature in three ways. Firstly, we used the stochastic distance function to measure productive efficiency and productivity change while considering multiple outputs in the railway sector. This method is less used among the studies that compare the performance of railway. Secondly, we calculate the evolution and decomposition of the total factor productivity for European railway. The average rate of productivity showed a slight annual improvement of 27% and the core engine of this was a 25% increase in technical progress. Results by country identify those needing improvement, to be more attractive. Finally, we use a limited dependent variable model to test the impact of rail liberalization process on productive efficiency. Results show that competition tendering improves productive efficiency, whereas free entry delivers the opposite result. Our results also show that competition and the overall liberalization have no impact on productive efficiency. It seems that liberalization process in not the key success factor for the railway industry. Our suggestion is that, in Europe, instead of focusing on rail liberalization process, policy maker should give priority to productivity gains.

Risk factors for domestic violence – an empirical analysis for Indian states

In December 2012, a young student was gang-raped on a bus in Delhi. Since then media attention has been directed toward raising awareness about crimes against women in India. But data shows that domestic violence and not rape is India’s number one reported crime over the last decade. An incidence of domestic violence, legally defined as “cruelty by husband or his relatives,” is reported once every five minutes. This paper attempts to prospectively examine the association between several risk factors and domestic violence in India. We utilize a comprehensive, national database, viz. the National Family Health Survey (NFHS-3) and focus on a sample of 69704 ever-married women between the ages of 15-49. A limited dependent variable model was used to estimate the effects. The dependent variable is a dichotomous variable indicating whether a respondent has faced any form of violence (both physical and emotional). Benchmark results and robustness checks indicate that several socio-economic and demographic factors are significantly associated with the likelihood of facing domestic violence. Factors that matter are educational attainment by the female as well as the husband, her employment status, the employment status of the husband, and demographic factors like caste and religion. A broad investigation indicates that among a comprehensive set of socio-economic and demographic variables that affect the susceptibility of ever-married women to domestic violence, women’s exposure to intergenerational violence, and alcohol consumption by the partner emerge as significant risk factors. The results remain robust even with choice of sub-samples based on educational differences between the partners. There is ample anecdotal evidence to suggest that excessive alcohol consumption is a national problem. Policy options have varied between outright prohibition and the use of tax instruments to curb excessive alcohol consumption. Apart from these, other positive interventions could emphasize on adverse health impacts and children’s well-being to bring about a sustainable behavioral change in partners. In addition to empowering women to break the cycle of domestic violence, one possible policy solution calls for the use of medical settings as an intervention point for children exposed to such violence. In order to support practitioners, NGOs and governmental agencies could identify best practices and disseminate such information to communities.

Bioeconomic factors of beef heifer maturity to consider when establishing criteria to optimally select and/or retain herd replacements.

Understanding the biology of heifer maturity and its relationship to calving difficulty and subsequent breeding success is a vital step in building a bioeconomic model to identify optimal production and profitability. A limited dependent variable probit model is used to quantify the responses among heifer maturities, measured by a maturity index (MI), on dystocia and second pregnancy. The MI account for heifer age, birth BW, prebreeding BW, nutrition level, and dam size and age and is found to be inversely related to dystocia occurrence. On average there is a 2.2% increase in the probability of dystocia with every 1 point drop in the MI between the MI scores of 50 and 70. Statistically, MI does not directly alter second pregnancy rate; however, dystocia does. The presence of dystocia reduced second pregnancy rates by 10.67%. Using the probability of dystocia predicted from the MI in the sample, it is found that on average, every 1 point increase in MI added 0.62% to the probability of the occurrence of second pregnancy over the range represented by the data. Relationships among MI, dystocia, and second pregnancy are nonlinear and exhibit diminishing marginal effects. These relationships indicate optimal production and profitability occur at varying maturities, which are altered by animal type, economic environment, production system, and management regime. With these captured relationships, any single group of heifers may be ranked by profitability given their physical characteristics and the applicable production, management, and economic conditions.

Use of generic and condition-specific measures of health-related quality of life in NICE decision-making: a systematic review, statistical modelling and survey

The National Institute for Health and Care Excellence recommends the use of generic preference-based measures (GPBMs) of health for its Health Technology Assessments (HTAs). However, these data may not be available or appropriate for all health conditions. To determine whether GPBMs are appropriate for some key conditions and to explore alternative methods of utility estimation when data from GPBMs are unavailable or inappropriate. The project was conducted in three stages: (1) A systematic review of the psychometric properties of three commonly used GPBMs [EQ-5D, SF-6D and Health Utilities Index Mark 3 (HUI3)] in four broadly defined conditions: visual impairment, hearing impairment, cancer and skin conditions. (2) Potential modelling approaches to 'map' EQ-5D values from condition-specific and clinical measures of health [European Organisation for Research and Treatment of Cancer Quality-of-life Questionnaire Core 30 (EORTC QLQ-C30) and Functional Assessment of Cancer Therapy - General Scale (FACT-G)] are compared for predictive ability and goodness of fit using two separate data sets. (3) Three potential extensions to the EQ-5D are developed as 'bolt-on' items relating to hearing, tiredness and vision. They are valued using the time trade-off method. A second valuation study is conducted to fully value the EQ-5D with and without the vision bolt-on item in an additional sample of 300 people. The valuation surveys were conducted using face-to-face interviews in the respondents' homes. Two representative samples of the UK general population from Yorkshire (n=600). None. Comparisons of EQ-5D, SF-6D and HUI3 in four conditions with various generic and condition-specific measures. Mapping functions were estimated between EORTC QLQ-C30 and FACT-G with EQ-5D. Three bolt-ons to the EQ-5D were developed: EQ + hearing/vision/tiredness. A full valuation study was conducted for the EQ + vision. (1) EQ-5D was valid and responsive for skin conditions and most cancers; in vision, its performance varied according to aetiology; and performance was poor for hearing impairments. The HUI3 performed well for hearing and vision disorders. It also performed well in cancers although evidence was limited and there was no evidence in skin conditions. There were limited data for SF-6D in all four conditions and limited evidence on reliability of all instruments. (2) Mapping algorithms were estimated to predict EQ-5D values from alternative cancer-specific measures of health. Response mapping using all the domain scores was the best performing model for the EORTC QLQ-C30. In an exploratory analysis, a limited dependent variable mixture model performed better than an equivalent linear model. In the full analysis for the FACT-G, linear regression using ordinary least squares gave the best predictions followed by the tobit model. (3) The exploratory valuation study found that bolt-on items for vision, hearing and tiredness had a significant impact on values of the health states, but the direction and magnitude of differences depended on the severity of the health state. The vision bolt-on item had a statistically significant impact on EQ-5D health state values and a full valuation model was estimated. EQ-5D performs well in studies of cancer and skin conditions. Mapping techniques provide a solution to predict EQ-5D values where EQ-5D has not been administered. For conditions where EQ-5D was found to be inappropriate, including some vision disorders and for hearing, bolt-ons provide a promising solution. More primary research into the psychometric properties of the generic preference-based measures is required, particularly in cancer and for the assessment of reliability. Further research is needed for the development and valuation of bolt-ons to EQ-5D. This project was funded by the UK Medical Research Council (MRC) as part of the MRC-NIHR methodology research programme (reference G0901486) and will be published in full in Health Technology Assessment; Vol. 18, No. 9. See the NIHR Journals Library website for further project information.

A Comparison of Direct and Indirect Methods for the Estimation of Health Utilities from Clinical Outcomes

Analysts frequently estimate health state utility values from other outcomes. Utility values like EQ-5D have characteristics that make standard statistical methods inappropriate. We have developed a bespoke, mixture model approach to directly estimate EQ-5D. An indirect method, "response mapping," first estimates the level on each of the 5 dimensions of the EQ-5D and then calculates the expected tariff score. These methods have never previously been compared. We use a large observational database from patients with rheumatoid arthritis (N = 100,398). Direct estimation of UK EQ-5D scores as a function of the Health Assessment Questionnaire (HAQ), pain, and age was performed with a limited dependent variable mixture model. Indirect modeling was undertaken with a set of generalized ordered probit models with expected tariff scores calculated mathematically. Linear regression was reported for comparison purposes. Impact on cost-effectiveness was demonstrated with an existing model. The linear model fits poorly, particularly at the extremes of the distribution. The bespoke mixture model and the indirect approaches improve fit over the entire range of EQ-5D. Mean average error is 10% and 5% lower compared with the linear model, respectively. Root mean squared error is 3% and 2% lower. The mixture model demonstrates superior performance to the indirect method across almost the entire range of pain and HAQ. These lead to differences in cost-effectiveness of up to 20%. There are limited data from patients in the most severe HAQ health states. Modeling of EQ-5D from clinical measures is best performed directly using the bespoke mixture model. This substantially outperforms the indirect method in this example. Linear models are inappropriate, suffer from systematic bias, and generate values outside the feasible range.

Household Saving Behavior and the Influence of Family-Owned Business

This study focused on the lifecycle income objective of business-owning (farm and nonfarm) households. We hypothesized that the complex relationship between household and business management decisions had the potential to challenge predictions from standard household savings theory. Specifically, we tested for differences in saving behavior of these entrepreneurial households relative to the average US household. A limited dependent variable model was performed, keying in on the saving behavior and ability of household respondents in the Survey of Consumer Finances for 2007. The estimation results indicated that, along with standard demographic influences of savings models, households owning a farm or nonfarm business had a significantly higher likelihood of maintaining private saving in a given year. Our results highlight the necessity for future research on household saving behavior to account for the differing objectives and choice sets faced by households that own businesses when conducting analyses of household saving.

Determinantes dos Custos de Transação no Mercado de Ações no Brasil

Este artigo aplica a estimativa de custos de transação de Lesmond (20055) no mercado brasileiro de ações, apoiada num modelo de variável dependente limitada. O objetivo é testar hipóteses sobre fatores determinantes dos custos de transação no mercado secundário (liquidez, volatilidade, tamanho, governança corporativa diferenciada, participação em programa de ADRs), bem como o impacto da crise de 2008. Utilizam-se dados diários do período de 1999 a 2009, em média com mais de 250 ações por ano. É observado que o custo total médio de transação sofreu redução substancial e continuada em cada ano do período, indo de 2,95% em 1999 a 1,22% em 2009. É verificado que a volatilidade da ação e a participação em níveis de governança corporativa diferenciada são as variáveis explicativas mais importantes.