The quality–quantity trade-off in fertility across parent earnings levels: a test for credit market failure

The dominant economic theory of the family explains the negative correlation between family size and child achievement, a ‘quality–quantity trade-off’, through borrowing constraints and credit market failure. This paper presents a model in which the opportunity cost of time spent with children is increasing, thus creating a trade-off even in economies with perfect credit markets. While both produce a family size effect, temporal and financial constraints predict different patterns for the trade-off across levels of parent income. Using data from the National Child Development Study, the trade-off is found even among high-earning families who presumably do not face credit constraints. Moreover, the trade-off does not grow as parent earnings diminish. Both of these findings suggest that temporal and not financial constraints explain the quality–quantity trade-off.

A unified approach to interpolation and graduation

The subject of interpolation and graduation is customarily treated by finite difference formulas of great variety and complexity, these having been developed with the convenience of hand calculation in mind. The cheapening of computation which has occurred in the past few years permits a simplification and unification of the subject. This is accomplished by linear equations which express conditions it is desired to impose on the interpolating curve and the elimination of the constants resulting in a determinantal equation. A computer program which evaluates a determinant then suffices for nearly any problem of graduation, interpolation, numerical differentiation and integration, as well as for the calculation of the remainder term or error of any of these.     

Two Population-Environment Regimes in the Great Plains of the United States, 1930–1990

This paper analyzes factors that affect net migration rates in counties in the U.S. Great Plains between 1930 and 1990, emphasizing the roles of weather (especially drought), environmental amenities, employment, and population, making use of a rich county-level data set. Using a pooled time series model the paper shows that environment is important in population processes, with weather and agricultural change more important in the 1930s and 1940s, and environmental amenities more important in later time periods. The paper provides important insights into how environmental impacts on migration might change over time, and how those changes might be measured.     

The Role of Maternal Behavior in the Relation between Shyness and Social Reticence in Early Childhood and Social Withdrawal in Middle Childhood

The moderating effect of maternal behavior in the relations between social reticence and shyness in preschool and subsequent social withdrawal was investigated. Eighty children (47 females) were judged for degree of social reticence during play with unfamiliar peers at the age of four and mothers completed the Colorado child temperament inventory (CCTI). At the age of seven, the children were coded for degree of social withdrawal during peer play and mothers and children were observed during structured and unstructured activities. Two significant interaction effects indicated that maternal report of shyness was a positive predictor of age‐seven social withdrawal when mothers lacked positivity; whereas observed social reticence was associated with higher degrees of social withdrawal when mothers were highly negative. Maternal positivity and negativity differentially influenced the development of social withdrawal in childhood, such that maternal negativity is associated with poor social functioning in children who have an established history of social withdrawal; whereas maternal positivity is associated with better social outcome for preschoolers who are viewed as temperamentally shy.     

Longitudinal patterns of anger reactivity and risk‐taking: The role of peer‐context

The current study examined the interplay between children's dispositional anger and susceptibility to peers' influence in increasing children's risk‐taking behaviors. Participants in the current study were children from a larger study of temperament and social–emotional development who were followed across 9, 24, 36, 48, and 60 months. Dispositional anger was measured using mothers' reports across 9 and 48 months. At 60 months, children played a risk‐taking computer game in presence of an unfamiliar peer who watched the child play. The child's risk‐taking was assessed during the game as the unfamiliar peers' reactions were coded based on comments that were peer directed, reflective of praising the target child's performance, or object directed, indicative of excitement toward the game. A latent profile analysis revealed three longitudinal anger profiles across infancy to early childhood: high stable, average stable, and low stable anger. Results suggested that as peers' object‐directed comments predicted risk‐taking independent of children's anger, the association between peer‐directed comments and risk‐taking was dependent on children's dispositional anger. Specifically, when peers praised the target child's performance, children in the high stable anger profile showed increased risk‐taking propensity. Findings are discussed based on the importance of considering both temperamental characteristics and aspects of the peer context in relation to children's risk‐taking.     

Leveraging historical data into oncology development programs: Two case studies of phase 2 Bayesian augmented control trial designs

Leveraging historical data into the design and analysis of phase 2 randomized controlled trials can improve efficiency of drug development programs. Such approaches can reduce sample size without loss of power. Potential issues arise when the current control arm is inconsistent with historical data, which may lead to biased estimates of treatment efficacy, loss of power, or inflated type 1 error. Consideration as to how to borrow historical information is important, and in particular, adjustment for prognostic factors should be considered. This paper will illustrate two motivating case studies of oncology Bayesian augmented control (BAC) trials. In the first example, a glioblastoma study, an informative prior was used for the control arm hazard rate. Sample size savings were 15% to 20% by using a BAC design. In the second example, a pancreatic cancer study, a hierarchical model borrowing method was used, which enabled the extent of borrowing to be determined by consistency of observed study data with historical studies. Supporting Bayesian analyses also adjusted for prognostic factors. Incorporating historical data via Bayesian trial design can provide sample size savings, reduce study duration, and enable a more scientific approach to development of novel therapies by avoiding excess recruitment to a control arm. Various sensitivity analyses are necessary to interpret results. Current industry efforts for data transparency have meaningful implications for access to patient‐level historical data, which, while not critical, is helpful to adjust for potential imbalances in prognostic factors.