Global benefit-risk assessment in designing clinical trials and some statistical considerations of the method

When characterizing a therapy, the efficacy and the safety are two major aspects under consideration. In prescribing a therapy to a patient, a clinician puts the two aspects together and makes a decision based on a consolidated thought process. The global benefit-risk (GBR) measures proposed by Chuang-Stein et al. (Stat. Med. 1991; 10:1349-1359) are useful in facilitating the thinking, and creating the framework for making statistical comparisons based on benefit-risk point of view. This article describes how a GBR linear score was defined and used as the primary outcome measure in a clinical trial design. The robustness of the definitions of 'benefit' and 'risk' are evaluated using different criteria. The sensitivity of the pre-specified weights is also analyzed using alternative weights; one of those was determined by the relative to an identified distribution integral transformation approach (Biometrics 1958; 14:18-38). Statistical considerations are illustrated using pooled data from clinical trials studying antidepressant. The pros and cons for using GBR assessments in the setting of clinical trials are discussed.     

The Effect of Household Wealth on Educational Attainment: Evidence from 35 Countries

The authors use household survey data from the Demographic and Health Surveys (DHS) from 44 surveys (in 35 countries) to document different patterns in the enrollment and attainment of children from rich and poor households. They overcome the lack of income or expenditure data in the DHS by constructing a proxy for long-run wealth of the household from the asset information in the surveys, using the statistical technique of principal components. There are three major findings. First, the enrollment profiles of the poor differ across countries but fall into distinctive regional patterns: in some regions the poor reach nearly universal enrollment in first grade, but then drop out in large numbers leading to low attainment (typical of South America), while in other regions the poor never enroll in school (typical of South Asia and Western/Central Africa). Second, there are enormous differences across countries in the “wealth gap,” the difference in enrollment and educational attainment of the rich and poor. While in some countries the difference in the median years of school completed of the rich and poor is only a year or two, in other countries the wealth gap in attainment is 9 or 10 years. Third, the attainment profiles can be used as diagnostic tools to suggest issues in the educational system, such as the extent to which low attainment is attributable to physical unavailability of schools.     

Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India*

Using data from India, we estimate the relationship between household wealth and children's school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children's enrollment across Indian states. On average a "rich" child is 31 percentage points more likely to be enrolled than a "poor" child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.     

Income per Natural: Measuring Development for People Rather Than Places

It is easy to learn the average income of a resident of El Salvador or Albania. But there is no systematic source of information on the average income of a Salvadoran or Albanian. We estimate a new statistic: income per natural—the mean annual income of all people born in a given country, regardless of where those people now reside. Income per natural often differs substantially from income per resident, both in its mean and in its distribution. A large part of this difference is caused by movement across borders. Indeed, for people from a number of developing countries, departing their country of birth is one of the most important sources of poverty reduction and material advancement. If economic development is that which raises human well‐being, then crossing international borders is not an alternative to economic development; it is a form of economic development.     

What do child characteristics contribute to outcomes from care: A PRISMA review

This article presents the findings from a systematic review of the literature regarding factors related to positive placement outcomes. Children in care are particularly vulnerable to problems with their emotional and behavioural development. It is important to know which factors affect whether children will have a positive placement outcome or not. Previous research has aimed to examine this, and has found that certain child characteristics can affect placement outcome. Reviews have not reported their search strategy in line with PRISMA guidelines, nor have they always reported the source of the data. This review was particularly interested in which studies had contact with the children or carers themselves, as opposed to a reliance on administrative data. There appear to be child characteristics that affect placement outcome, but findings need to be interpreted with caution due to a high volume of results from administrative data. Future research should aim to conduct full assessments with children when they come into care.     

Team effects on compensation: an application to salary determination in the National Hockey League

Studies of salary determination largely model pay as a function of the attributes of the individual and the workplace (i.e., employer size, job characteristics, and so forth). This article empirically investigates an additional factor that may influence individual pay, specifically coworker productivity. Data from professional sports are used to evaluate this question because both salary and teammate performance measures are readily available. We find that team attributes have both direct effects on an individual's pay, and indirect effects through altering the rates at which individual player productive characteristics are valued.