Camera-Related Behaviors during Video Recorded Medical Interactions

Video recording provides an objective record of the content of medical interactions. However, there is concern that cameras may be reactive measurement devices that alter what normally transpires during interactions. This study addressed potential reactivity of cameras in medical interactions. Interactions between 45 patients and 14 medical oncologists were video recorded and coded for camera-related behaviors. Eleven of 45 patients performed none of the behaviors. Among the other patients, camera-related behaviors were infrequent and, on average, constituted about 0.1% (one-tenth of one percent) of total interaction time. Behaviors occurred most often in very early stages of interactions, and when physicians were absent from the room. Seven physicians showed camera-related behaviors, comprising less than 0.1% of the time they were in the interaction. Results suggest video recording can provide nonreactive means of studying medical interactions.

Robust signed-rank estimation and variable selection for semi-parametric additive partial linear models

A fully nonparametric model may not perform well or when the researcher wants to use a parametric model but the functional form with respect to a subset of the regressors or the density of the errors is not known. This becomes even more challenging when the data contain gross outliers or unusual observations. However, in practice the true covariates are not known in advance, nor is the smoothness of the functional form. A robust model selection approach through which we can choose the relevant covariates components and estimate the smoothing function may represent an appealing tool to the solution. A weighted signed-rank estimation and variable selection under the adaptive lasso for semi-parametric partial additive models is considered in this paper. B-spline is used to estimate the unknown additive nonparametric function. It is shown that despite using B-spline to estimate the unknown additive nonparametric function, the proposed estimator has an oracle property. The robustness of the weighted signed-rank approach for data with heavy-tail, contaminated errors, and data containing high-leverage points are validated via finite sample simulations. A practical application to an economic study is provided using an updated Canadian household gasoline consumption data.