High wage workers and low wage firms: negative assortative matching or limited mobility bias?

Summary.  In the empirical literature on assortative matching using linked employer–employee data, unobserved worker quality appears to be negatively correlated with unobserved firm quality. We show that this can be caused by standard estimation error. We develop formulae that show that the estimated correlation is biased downwards if there is true positive assortative matching and when any conditioning covariates are uncorrelated with the firm and worker fixed effects. We show that this bias is bigger the fewer movers there are in the data, which is 'limited mobility bias'. This result applies to any two-way (or higher) error components model that is estimated by fixed effects methods. We apply these bias corrections to a large German linked employer–employee data set. We find that, although the biases can be considerable, they are not sufficiently large to remove the negative correlation entirely.     

Estimates of human immunodeficiency virus prevalence and proportion diagnosed based on Bayesian multiparameter synthesis of surveillance data

Summary.  Estimates of the number of prevalent human immunodeficiency virus infections are used in England and Wales to monitor development of the human immunodeficiency virus–acquired immune deficiency syndrome epidemic and for planning purposes. The population is split into risk groups, and estimates of risk group size and of risk group prevalence and diagnosis rates are combined to derive estimates of the number of undiagnosed infections and of the overall number of infected individuals. In traditional approaches, each risk group size, prevalence or diagnosis rate parameter must be informed by just one summary statistic. Yet a rich array of surveillance and other data is available, providing information on parameters and on functions of parameters, and raising the possibility of inconsistency between sources of evidence in some parts of the parameter space. We develop a Bayesian framework for synthesis of surveillance and other information, implemented through Markov chain Monte Carlo methods. The sources of data are found to be inconsistent under their accepted interpretation, but the inconsistencies can be resolved by introducing additional 'bias adjustment' parameters. The best-fitting model incorporates a hierarchical structure to spread information more evenly over the parameter space. We suggest that multiparameter evidence synthesis opens new avenues in epidemiology based on the coherent summary of available data, assessment of consistency and bias modelling.     

Understanding Management Performance

Current models of the factors underlying management performance make use of a variety of variables at different levels of analysis. A framework is presented in which variables of three different types are linked together. Using data from a sample (n = 437) of British managers this article explores relationships between personality factors (using the big-five factors), work competencies and managerial performance. Results from the analyses reveal a set of underlying competency factors, which show different patterns of correlation with two facets of performance: current proficiency and promotability. In turn, these factors and the facets of performance show relationships with the big-five personality factors. Current proficiency is more closely related to competencies of organization, specialization and analysis – competencies more likely to be displayed by people who are conscientious and introverted. Promotability is linked more closely to competencies concerning action/motivation, flexibility/sensitivity and communication – competencies more likely to be displayed by people who are extroverted with lower conscientiousness and agreeableness.     

Children and Young People “In Care” Participating in a Peer‐Mentoring Relationship: An Exploration of Resilience

The aim of this study was to explore how a 1‐year peer‐mentoring relationship contributed to change in young women “in care.” Twenty semistructured, one‐to‐one interviews were conducted with mentors (n = 11) and mentees (n = 9) recruited from two different London local authorities. Participants’ accounts were interpreted through a developmental lens to uncover developmental aspects and locus mechanisms through which transformative change took place. Resilience as a healthy outcome was the result of the dual function the mentoring relationship performed. The mentoring relationship was protective against the risks associated with transitioning to independent living and/or adulthood, and promoted internal assets and competencies whereby the mentees’ ability to resist them was enhanced. Establishing a trustworthy connection with a role model promoted developmental domains within mentees.     

Confidence estimation via the parametric bootstrap in logistic joinpoint regression

We consider asymptotic properties of the maximum likelihood and related estimators in a clustered logistic joinpoint model with an unknown joinpoint. Sufficient conditions are given for the consistency of confidence bounds produced by the parametric bootstrap; one of the conditions required is that the true location of the joinpoint is not at one of the observation times. A simulation study is presented to illustrate the lack of consistency of the bootstrap confidence bounds when the joinpoint is an observation time. A removal algorithm is presented which corrects this problem, but at the price of an increased mean square error. Finally, the methods are applied to data on yearly cancer mortality in the US for individuals age 65 and over.