Task-Specific Experience and Task-Specific Talent: Decomposing the Productivity of High School Teachers

We use administrative panel data to decompose worker performance into components relating to general talent, task-specific talent, general experience, and task-specific experience. We consider the context of high school teachers, in which tasks consist of teaching particular subjects in particular tracks. Using the timing of changes in the subjects and levels to which teachers are assigned to provide identifying variation, we show that much of the productivity gains to teacher experience estimated in the literature are actually subject-specific. By contrast, very little of the variation in the permanent component of productivity among teachers is subject-specific or level-specific. Counterfactual simulations suggest that maximizing the value of task-specific experience could produce nearly costless efficiency gains on the order of .02 test score standard deviations

Interpretation of the Cosmological Metric

The cosmological Robertson-Walker metric of general relativity is often said to have the consequences that (1) the recessional velocity $v$ of a galaxy at proper distance $\ell$ obeys the Hubble law $v=H\ell$, and therefore galaxies at sufficiently great distance $\ell$ are receding faster than the speed of light $c$; (2) faster than light recession does not violate special relativity theory because the latter is not applicable to the cosmological problem, and because ``space itself is receding'' faster than $c$ at great distance, and it is velocity relative to local space that is limited by $c$, not the velocity of distant objects relative to nearby ones; (3) we can see galaxies receding faster than the speed of light; and (4) the cosmological redshift is not a Doppler shift, but is due to a stretching of photon wavelength during propagation in an expanding universe. We present a particular Robertson-Walker metric (an empty universe metric) for which a coordinate transformation shows that none of these interpretation necessarily holds. The resulting paradoxes of interpretation lead to a deeper understanding of the meaning of the cosmological metric.Comment: REVTeX 4, 20 pages, accepted for publication in Am. J. Phys. Comments: edited version that will appear in the Am. J. Phy

A spot check of the status of music education of grades four, five and six in the elementary schools of Massachusetts as of the year 1956-57.

Thesis (Ed.M.)--Boston Universit

The Design of Intervention Trials Involving Recurrent and Terminal Events

The final publication (Wu, Longyang, and Richard J. Cook. "The Design of Intervention Trials Involving Recurrent and Terminal Events." Statistics in Biosciences 5(2) (2013): 261-285) is available at Springer via http://dx.doi.org/10.1007/s12561-013-9083-zClinical trials are often designed to assess the effect of therapeutic interventions on the incidence of recurrent events in the presence of a dependent terminal event such as death. Statistical methods based on multistate analysis have considerable appeal in this setting since they can incorporate changes in risk with each event occurrence, a dependence between the recurrent event and the terminal event, and event-dependent censoring. To date, however, there has been limited development of statistical methods for the design of trials involving recurrent and terminal events. Based on the asymptotic distribution of regression coefficients from a multiplicative intensity Markov regression model, we derive sample size formulas to address power requirements for both the recurrent and terminal event processes. We consider the design of trials for which separate marginal hypothesis tests are of interest for the recurrent and terminal event processes and deal with both superiority and non-inferiority tests. Simulation studies confirm that the designs satisfy the nominal power requirements in both settings, and an application to a trial evaluating the effect of a bisphosphonate on skeletal complications is given for illustration.Natural Sciences and Engineering Research Council of Canada (RJC RGPIN 155849, JFL RGPIN 8597); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626

Bone and metal - an orthopaedic perspective on osseointegration of metals

The area of implant osseointegration is of major importance, given the predicted significant rise in the number of orthopaedic procedures and an increasingly ageing population. Osseointegration is a complex process involving a number of distinct mechanisms affected by the implant bulk properties and surface characteristics. Our understanding and ability to modify these mechanisms through alterations in implant design is continuously expanding. The following review considers the main aspects of material and surface alterations in metal implants, and the extent of their subsequent influence on osseointegration. Clinically, osseointegration results in asymptomatic stable durable fixation of orthopaedic implants. The complexity of achieving this outcome through incorporation and balance of contributory factors is highlighted through a clinical case report

Sieve estimation in a Markov illness-death process under dual censoring

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Bioinformatics following peer review. The version of record Boruvka, Audrey and Cook, Richard J. (2016). Biostatistics, 17(2): 350-363. DOI: 10.1093/biostatistics/kxv042 is available online at: http://dx.doi.org/10.1093/biostatistics/kxv042Semiparametric methods are well-established for the analysis of a progressive Markov illness-death process observed up to a noninformative right censoring time. However often the intermediate and terminal events are censored in different ways, leading to a dual censoring scheme. In such settings unbiased estimation of the cumulative transition intensity functions cannot be achieved without some degree of smoothing. To overcome this problem we develop a sieve maximum likelihood approach for inference on the hazard ratio. A simulation study shows that the sieve estimator offers improved finite-sample performance over common imputation-based alternatives and is robust to some forms of dependent censoring. The proposed method is illustrated using data from cancer trials.Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626

A dynamic Mover–Stayer model for recurrent event processes

The final publication is available at Springer via http://dx.doi.org/10.1007/s10985-013-9271-7In studies of affective disorder, individuals are often observed to experience recurrent symptomatic exacerbations warranting hospitalization. Interest may lie in modeling the occurrence of such exacerbations over time and identifying associated risk factors. In some patients, recurrent exacerbations are temporally clustered following disease onset, but cease to occur after a period of time.We develop a dynamic Mover-Stayer model in which a canonical binary variable associated with each event indicates whether the underlying disease has resolved. An individual whose disease process has not resolved will experience events following a standard point process model governed by a latent intensity. When the disease process resolves, the complete data intensity becomes zero and no further event will occur. An expectation- maximization algorithm is described for parametric and semiparametric model fitting based on a discrete time dynamic Mover-Stayer model and a latent intensity-based model of the underlying point process.RJC: Natural Sciences and Engineering Research Council of Canada (RGPIN 155849); Canadian Institutes for Health Research (FRN 13887); Canada Research Chair (Tier 1) – CIHR funded (950-226626) HS: Grant from the Division of High Impact Clinical Trials of the Ontario Institute for Cancer Researc