Distribution Of Individual Characteristics Research Articles

Gender and Advanced Urothelial Cancer: Outcome, Efficacy and Toxicity following Chemotherapy.

Background and Objectives: The incidence of urothelial cancer in males is higher than in females; however, females have a higher risk of recurrence and progression. The aim of our study was to report the effect of gender on the oncological outcome in advanced urothelial cancer. Materials and Methods: In our retrospective study, all patients had undergone primary surgical treatment for urothelial cancer and were affected by stage IV disease at the time of chemotherapy. Response to therapy and toxicity were evaluated. Subgroups were analyzed for tumour presentation, first- and second-line treatment response, progression-free survival (PFS) and overall survival (OS). Results. Seventy-five patients, 18 (24%) females and 57 (76%) males, were considered. Investigation into the distribution of individual characteristics according to gender revealed a significant difference only for smoking, with a prevalence of smokers in women (p = 0.029). At the end of follow-up, OS was higher in females (27.5% vs. 17.4%; p = 0.047). Smoking did not significantly influence OS (p = 0.055), while univariate Cox regression analysis confirmed that males had a higher risk of death (HR = 2.28, 95% CI 0.99–129 5.25), with borderline statistical significance (p = 0.053). Men showed higher PFS than women both after first-line (p = 0.051) and second-line chemotherapy (p = 0.018), with a lower risk of progression (HR = 0.29, 95% CI 0.10–0.86; p = 0.026). No differences were found between genders with regard to toxicity. Conclusions. In our series, PFS rates following first- and second-line therapies for advanced urothelial carcinoma confirmed that females have a greater risk of progression than males.

Determinants of prepaid systems of healthcare financing: a worldwide country-level perspective

In this paper we examine determinants of prepaid modes of health care financing in a worldwide cross-country perspective. We use three different indicators to capture the role of prepaid modes in health care financing: (i) the share of total prepaid financing as percent of total current health expenditures, (ii) the share of voluntary prepaid financing as percent of total prepaid financing, and (iii) the share of compulsory health insurance as percent of total compulsory prepaid financing. In the econometric analysis, we refer to a panel data set comprising 154 countries and covering the time period 2000–2015. We apply a static as well as a dynamic panel data model. We find that the current structure of prepaid financing is significantly determined by its different forms in the past. The significant influence of GDP per capita, governmental revenues, the agricultural value added, development assistance for health, degree of urbanization and regulatory quality varies depending on the financing structure we look at. The share of the elderly and the education level are only of minor importance for explaining the variation in a country’s share of prepaid health care financing. The importance of the mentioned variables as determinants for prepaid health care financing also varies depending on the countries’ socio-economic development. From our analysis we conclude that more detailed information on indicators which reflect the distribution of individual characteristics (such as income, family size and structure and health risks) within a country’s population would be needed to gain deeper insight into the decisive determinants for prepaid health care financing.

Gender-specific human capital: identification and quantifying its wage effects

PurposeThe purpose of this paper is to better understand the possible reasons behind gender pay disparities, focussing on the unique features of male and female human capital and their wage returns. Despite increasing convergence of male and female human capital attainments, substantial differences remain. Extraction of human capital components non-overlapping across genders provides more profound explanation of the unexplained wage gap of men and women.Design/methodology/approachStarting with the non-parametric matching-based decomposition technique, the authors extend the pay gap estimation framework and focus on males and females having no counterpart in a set of characteristics within the opposite gender. The authors identify gender-unique human capital in terms of differences in distribution of individual characteristics across men and women and gender-specific combination of human capital characteristics. Wage returns to gender-specific profiles are evaluated applying wage regression on both full distribution of earnings and wage quantiles. The research relies on the Survey of Adult Skills (PIAAC) database for Estonia, which incorporates both formal education and cognitive skill records.FindingsThe study identifies sets of characteristics and competencies exclusive for both genders, proving that male and female profiles cannot be directly compared. The results suggest that men possess high individual and combined abilities in numeracy and problem solving in technology-rich environment, not always reached by females. This potentiates men’s higher earnings in spite of their generally lower formal educational attainments. Wage gap analysis over the full distribution of earnings shows even larger “glass ceiling” effect for females, possessing woman-specific human capital.Originality/valueThe authors raise a research from a novel perspective towards a role of human capital in gender wage inequality. Instead of usual reference to observable gaps in male and female characteristics, the authors identify the gender-specific human capital profiles, to a large extent non-reached by the opposite gender. Analysed associations between gender-specific characteristics and earnings provide an insight to possible effects of gender-unique human capital on a male-female wage disparity.

OUP accepted manuscript

SummaryCapture-recapture experiments are widely used to collect data needed for estimating the abundance of a closed population. To account for heterogeneity in the capture probabilities, Huggins (1989) and Alho (1990) proposed a semiparametric model in which the capture probabilities are modelled parametrically and the distribution of individual characteristics is left unspecified. A conditional likelihood method was then proposed to obtain point estimates and Wald-type confidence intervals for the abundance. Empirical studies show that the small-sample distribution of the maximum conditional likelihood estimator is strongly skewed to the right, which may produce Wald-type confidence intervals with lower limits that are less than the number of captured individuals or even are negative. In this paper, we propose a full empirical likelihood approach based on Huggins and Alho’s model. We show that the null distribution of the empirical likelihood ratio for the abundance is asymptotically chi-squared with one degree of freedom, and that the maximum empirical likelihood estimator achieves semiparametric efficiency. Simulation studies show that the empirical likelihood-based method is superior to the conditional likelihood-based method: its confidence interval has much better coverage, and the maximum empirical likelihood estimator has a smaller mean square error. We analyse three datasets to illustrate the advantages of our empirical likelihood approach.

Physical Activity Patterns Among U.S. Adults With Disabilities

Purpose: To characterize physical activity patterns among people with disabilities using data from a nationally representative health survey.Method: Individual-level data came from the Behavioral Risk Factor Surveillance System 2011 survey. Pearson’s chi-squared tests were conducted to assess the difference in the proportion distribution of individual characteristics between each of the 4 disability categories and the population without disability. Conditional on their statistical significance, 2 sample proportion tests were performed on individual demographics including gender, age group, and race/ethnicity.Results: Compared to people without disabilities, the prevalence of physical inactivity was substantially higher among people with disabilities. Walking and gardening were the most common physical activities among people with disabilities. Physical activity patterns varied significantly across gender, age, race/ethnicity, and disability categories.Conclusion: Ecological interventions to promote physical activity engagement in people with disabilities should be mindful of the feasibility, acceptability, and accessibility for this specific and particularly vulnerable population.

Identification of a Semiparametric Item Response Model

We consider the identification of a semiparametric multidimensional fixed effects item response model. Item response models are typically estimated under parametric assumptions about the shape of the item characteristic curves (ICCs), and existing results suggest difficulties in recovering the distribution of individual characteristics under nonparametric assumptions. We show that if the shape of the ICCs are unrestricted, but the shape is common across individuals and items, the individual characteristics are identified. If the shape of the ICCs are allowed to differ over items, the individual characteristics are identified in the multidimensional linear compensatory case but only identified up to a monotonic transformation in the unidimensional case. Our results suggest the development of two new semiparametric estimators for the item response model.

Decomposing Gender Differences in Low-Density Lipoprotein Cholesterol among Veterans with or at Risk for Cardiovascular Illness

ObjectivesTo measure the extent to which gender differences in poor lipid control among individuals at risk for cardiovascular diseases could be explained by patient-level characteristics. Study DesignCross-sectional analyses of merged Veteran Health Administration (VHA) and Medicare claims data for the fiscal years (FY) 2002 and 2003 consisting of veterans using VHA facilities and were diagnosed with diabetes or heart disease or hypertension during FY 2002 and had recorded LDL cholesterol values in FY2003 (N = 527,568). There were 10,582 women and 516,986 men veterans. Poor lipid control was defined as LDL cholesterol values ≥130 mg/dL. Multivariate techniques consisted of logistic regressions. Based on the parameter estimates and distribution of individual characteristics, we used a decomposition technique to analyze factors that contributed to the gender difference in poor lipid control. Principal FindingsA significantly higher percent of women (27.4%) than men (17.1%) had LDL cholesterol values ≥130 mg/dL. Of the 10.3 percentage point difference in lipid control, 3.4 percentage points were explained by variables included in the model. The gender difference in poor lipid control was mostly explained by age, physical illnesses, use of lipid lowering medications and depression. ConclusionsOnly one-third of the gender difference in poor lipid control could be explained by differences in individual characteristics, some of which are modifiable or could be used to identify groups at risk with poor lipid control. Our findings suggest that gender differences in lipid control could be partially reduced by increasing the prescription of lipid lowering drugs and treating depression among women. Interventions that improve lipid control in the non-elderly will also benefit women. However the largest part of the difference in lipid control between women and men remains unexplained and further research is needed to identify additional modifiable and unmodifiable factors.

Decomposing Gender Differences in Low Density Lipoprotein Cholesterol Among Veterans with or at Risk for Cardiovascular Illness

To measure the extent to which gender differences in poor lipid control among individuals at risk for cardiovascular diseases could be explained by patient-level characteristics. Cross-sectional analyses of merged Veteran Health Administration (VHA) and Medicare claims data for the fiscal years (FY) 2002 and 2003 consisting of veterans using VHA facilities and were diagnosed with diabetes or heart disease or hypertension during FY 2002 and had recorded LDL cholesterol values in FY2003 (N = 527,568). There were 10,582 women and 516,986 men veterans. Poor lipid control was defined as LDL cholesterol values > 130mg/dL. Multivariate techniques consisted of logistic regressions. Based on the parameter estimates and distribution of individual characteristics, we used a decomposition technique to analyze factors that contributed to the gender difference in poor lipid control. A significantly higher percent of women (27.4%) than men (17.1%) had LDL cholesterol values > 130mg/dL. Of the 10.3 percentage point difference in lipid control, 3.4 percentage points were explained by variables included in the model. The gender difference in poor lipid control was mostly explained by age, physical illnesses, use of lipid lowering medications and depression. Only one-third of the gender difference in poor lipid control could be explained by differences in individual characteristics, some of which are modifiable or could be used to identify groups at risk with poor lipid control. Our findings suggest that gender differences in lipid control could be partially reduced by increasing the prescription of lipid lowering drugs and treating depression among women. Interventions that improve lipid control in the non-elderly will also benefit women. However the largest part of the difference in lipid control between women and men remains unexplained and further research is needed to identify additional modifiable and unmodifiable factors.

Analysis of the lag phase to exponential growth transition by incorporating inoculum characteristics

During the last decade, individual-based modelling (IbM) has proven to be a valuable tool for modelling and studying microbial dynamics. As each individual is considered as an independent entity with its own characteristics, IbM enables the study of microbial dynamics and the inherent variability and heterogeneity. IbM simulations and (single-cell) experimental research form the basis to unravel individual cell characteristics underlying population dynamics. In this study, the IbM framework MICRODIMS, i.e., MICRObial Dynamics Individual-based Model/Simulator, is used to investigate the system dynamics (with respect to the model and the system modelled). First, the impact of the time resolution on the simulation accuracy is discussed. Second, the effect of the inoculum state and size on emerging individual dynamics, such as individual mass, individual age and individual generation time distribution dynamics, is studied. The distributions of individual characteristics are more informative during the lag phase and the transition to the exponential growth phase than during the exponential phase. The first generation time distributions are strongly influenced by the inoculum state. All inocula with a pronounced heterogeneity, except the inocula starting from a uniform distribution, exhibit commonly observed microbial behaviour, like a more spread first generation time distribution compared to following generations and a fast stabilisation of biomass and age distributions.

The Gender Wage Gap in Peru 1986-2000: Evidence from a Matching Comparisons Approach

Applying the methodology developed in Nopo (2004), this paper analyzes the evolution of the gender wage gap in Peru from 1986 to 2000. This methodology has two advantages. First, it recognizes that the supports of observable characteristics distributions differ substantially. Second, it provides deeper insights regarding the distribution of the unexplained gender differences in earnings. For the period under analysis, males earn on average 45 percent more than females. This wage gap is composed of three additive elements: 11 percent differences in supports, 6 percent differences in distributions of individual characteristics and 28 percent unexplainable differences. About half of these unexplainable differences occur in the highest quintile of the wage distribution.

Convergence of strategic behavior to price taking

We address the following issue: what can be said about the degree of competition, in a set of markets with a large number of participants, when no information on the distribution of individual characteristics is available? Our main result is that the proportion of individuals whose strategic behavior differs substantially from price taking, converges to zero as the number of market participants becomes large, regardless of the distribution of characteristics.

Matching as a Tool to Decompose Wage Gaps

In this paper I present a methodology that uses matching comparisons to explain gender differences in wages. The approach emphasizes gender differences in the supports of the distributions of observable characteristics and provides useful insights about the distribution of the unexplained gender differences in pay. The proposed methodology, a non-parametric alternative to the Blinder-Oaxaca (BO) wage gap decomposition, does not require the estimation of earnings equations. It breaks down the gap into four additive elements, two of which are analogous to the elements of the BO decomposition (but computed only over the common support of the distributions of characteristics), while the other two account for differences in the supports. Using data for Peru in the period 1986-2000, I found that this problem of non-comparability accounts for 23% and 30% of the male and female working populations respectively. The matching methodology allows us to quantify the effect of explicitly recognizing these differences in the supports. In this way, the 45% gender wage gap in Peru is decomposed as: 11% explained by differences in the supports, 6% explained by differences in the distributions of individual characteristics and the remaining 28% cannot be explained by differences in observable individuals' characteristics. Approximately half ofthe latter is due to unexplained differences in the highest quintile of the wage distribution.

A New Approach to Group Structure, Burden Sharing, and the Equilibrium Provision of Public Goods

In the received model of the voluntary provision of a pure public good, the usual practice is to proceed from assumptions about the group characteristics to inferences about an implied outcome. The approach advocated in this paper reverses the traditional direction. Assuming a Nash equilibrium, we ask how to characterize the diverse set of group characteristics which will support it. Approaching the problem from this angle we define three crucial characteristics of a group-equilibrium: consumer's “free rider inducing supply,” “zero contribution-inducing wealth” and “voluntary surplus tribute” which is the amount by which a person's actual income exceeds his/her “zero-contribution inducing wealth.” Defining these indicators we show how they form the foundation of a complete mapping between the distribution of individual characteristics of a group, and equilibrium public good supply. Certain questions such as the interaction between size of the group and heterogeneity of incomes and tastes not yet adequately addressed are shown to yield easily to this approach.

Place and personal circumstances in a multilevel account of women's long-term illness

This paper investigates geographical variations in women's reports of limiting long-term illness in terms of individual inequalities and the contribution of area characteristics among wards and county districts. We use multilevel modelling of linked census data from the Office for National Statistics Longitudinal Study for England and Wales. We follow a random sample of 76,374 women aged between 16 and 45 at the time of the 1971 Census for 20 years to observe their reported limiting long-term illness (LLTI) at the 1991 Census. Car and home ownership were useful markers of social and material advantage, apparently protecting against the risk of reporting LLTI. Migration into the South-East region appeared beneficial, but otherwise there was little difference between those who moved home and those who did not. Differences between county districts persist after adjustment for individual circumstances (education and ethnicity), but almost all of these differences are explained by the social profile of wards in these areas. Geographical differences in LLTI are not, therefore, entirely explained by the distribution of individual characteristics; a woman with the same history may face a different risk of illness in different kinds of area. For women, the social composition of the locality (using the ward as a proxy) is more relevant than the broader economic and industrial classification of the surrounding county district, which is more important for health inequalities among men.