Improving propensity score weighting using machine learning

Machine learning techniques such as classification and regression trees (CART) have been suggested as promising alternatives to logistic regression for the estimation of propensity scores. The authors examined the performance of various CART-based propensity score models using simulated data. Hypothetical studies of varying sample sizes (n=500, 1000, 2000) with a binary exposure, continuous outcome, and 10 covariates were simulated under seven scenarios differing by degree of non-linear and non-additive associations between covariates and the exposure. Propensity score weights were estimated using logistic regression (all main effects), CART, pruned CART, and the ensemble methods of bagged CART, random forests, and boosted CART. Performance metrics included covariate balance, standard error, per cent absolute bias, and 95 per cent confidence interval (CI) coverage. All methods displayed generally acceptable performance under conditions of either non-linearity or non-additivity alone. However, under conditions of both moderate non-additivity and moderate non-linearity, logistic regression had subpar performance, whereas ensemble methods provided substantially better bias reduction and more consistent 95 per cent CI coverage. The results suggest that ensemble methods, especially boosted CART, may be useful for propensity score weighting

Generalizability of Randomized Trial Results to Target Populations: Design and Analysis Possibilities

Randomized trials play an important role in estimating the effect of a policy or social work program in a given population. While most trial designs benefit from strong internal validity, they often lack external validity, or generalizability, to the target population of interest. In other words, one can obtain an unbiased estimate of the study sample average treatment effect from a randomized trial; however, this estimate may not equal the target population average treatment effect if the study sample is not fully representative of the target population. This article provides an overview of existing strategies to assess and improve upon the generalizability of randomized trials, both through statistical methods and study design, as well as recommendations on how to implement these ideas in social work research

Hsp70 in mitochondrial biogenesis

The family of hsp70 (70 kilodalton heat shock protein) molecular chaperones plays an essential and diverse role in cellular physiology, Hsp70 proteins appear to elicit their effects by interacting with polypeptides that present domains which exhibit non-native conformations at distinct stages during their life in the cell. In this paper we review work pertaining to the functions of hsp70 proteins in chaperoning mitochondrial protein biogenesis. Hsp70 proteins function in protein synthesis, protein translocation across mitochondrial membranes, protein folding and finally the delivery of misfolded proteins to proteolytic enzymes in the mitochondrial matrix

Target Validity and the Hierarchy of Study Designs

In recent years, increasing attention has been paid to problems of external validity, specifically to methodological approaches for both quantitative generalizability and transportability of study results. However, most approaches to these issues have considered external validity separately from internal validity. Here we argue that considering either internal or external validity in isolation may be problematic. Further, we argue that a joint measure of the validity of an effect estimate with respect to a specific population of interest may be more useful: We call this proposed measure target validity. In this work, we introduce and formally define target bias as the total difference between the true causal effect in the target population and the estimated causal effect in the study sample, and target validity as target bias = 0. We illustrate this measure with a series of examples and show how this measure may help us to think more clearly about comparisons between experimental and nonexperimental research results. Specifically, we show that even perfect internal validity does not ensure that a causal effect will be unbiased in a specific target population

Pre-Training Muscle Characteristics of Subjects Who Are Obese Determine How Well Exercise Training Will Improve Their Insulin Responsiveness

Pre-training muscle characteristics of subjects who are obese determine how well exercise training will improve their insulin responsiveness. J Strength Cond Res 31(3): 798–808, 2017—Only half of prediabetic subjects who are obese who underwent exercise training without weight loss increased their insulin responsiveness. We hypothesized that those who improved their insulin responsiveness might have pretraining characteristics favoring a positive response to exercise training. Thirty nondiabetic subjects who were obese volunteered for 8 weeks of either strength training or endurance training. During training, subjects increased their caloric intake to prevent weight loss. Insulin responsiveness by euglycemic clamps and muscle fiber composition, and expression of muscle key biochemical pathways were quantified. Positive responders initially had 52% higher intermediate muscle fibers (fiber type IIa) with 27% lower slow-twitch fibers (type I) and 23% lower expression of muscle insulin receptors. Whether after weight training or stationary bike training, positive responders\u27 fiber type shifted away from type I and type IIa fibers to an increased proportion of type IIx fibers (fast twitch). Muscle insulin receptor expression and glucose transporter type 4 (GLUT4) expression increased in all trained subjects, but these moderate changes did not consistently translate to improvement in whole-body insulin responsiveness. Exercise training of previously sedentary subjects who are obese can result in muscle remodeling and increased expression of key elements of the insulin pathway, but in the absence of weight loss, insulin sensitivity improvement was modest and limited to about half of the participants. Our data suggest rather than responders being more fit, they may have been less fit, only catching up to the other half of subjects who are obese whose insulin responsiveness did not increase beyond their pretraining baseline

Orbital stability: analysis meets geometry

We present an introduction to the orbital stability of relative equilibria of Hamiltonian dynamical systems on (finite and infinite dimensional) Banach spaces. A convenient formulation of the theory of Hamiltonian dynamics with symmetry and the corresponding momentum maps is proposed that allows us to highlight the interplay between (symplectic) geometry and (functional) analysis in the proofs of orbital stability of relative equilibria via the so-called energy-momentum method. The theory is illustrated with examples from finite dimensional systems, as well as from Hamiltonian PDE's, such as solitons, standing and plane waves for the nonlinear Schr{\"o}dinger equation, for the wave equation, and for the Manakov system

Causal impact: Epidemiological approaches for a public health of consequence

The causal impact framework is a conceptual framework encompassing internal validity, external validity, and population intervention effects, which we argue can help us produce evidence of greater utility to public health decision-making

Consistency between Household and County Measures of Onsite Schooling during the COVID-19 Pandemic

The academic, socioemotional, and health impacts of school policies throughout the COVID-19 pandemic have been a source of many questions that require accurate information about the extent of onsite schooling occurring. This article investigates school operational status datasets during the pandemic, comparing (1) self-report data collected nationally on the household level through a Facebook-based survey, (2) county-level school policy data, and (3) a school-level closure status dataset based on phone GPS tracking. The percentage of any onsite instruction within states and counties are compared across datasets from December 2020 to May 2021. Sources were relatively consistent at the state level and for large counties, but key differences were revealed between units of measurement, showing differences between policy and household decisions surrounding children’s schooling experiences. The consistency levels across sources support the usage of each of the school policy sources to answer questions about the educational experiences, factors, and impacts related to K-12 education across the nation during the pandemic, but it remains vital to think critically as to which unit of measurement is most relevant to targeted research questions

From Predicting Solar Activity to Forecasting Space Weather: Practical Examples of Research-to-Operations and Operations-to-Research

The successful transition of research to operations (R2O) and operations to research (O2R) requires, above all, interaction between the two communities. We explore the role that close interaction and ongoing communication played in the successful fielding of three separate developments: an observation platform, a numerical model, and a visualization and specification tool. Additionally, we will examine how these three pieces came together to revolutionize interplanetary coronal mass ejection (ICME) arrival forecasts. A discussion of the importance of education and training in ensuring a positive outcome from R2O activity follows. We describe efforts by the meteorological community to make research results more accessible to forecasters and the applicability of these efforts to the transfer of space-weather research.We end with a forecaster "wish list" for R2O transitions. Ongoing, two-way communication between the research and operations communities is the thread connecting it all.Comment: 18 pages, 3 figures, Solar Physics in pres

Exawatt-Zettawatt Pulse Generation and Applications

A new amplification method, weaving the three basic compression techniques, Chirped Pulse Amplification (CPA), Optical Parametric Chirped Pulse Amplification (OPCPA) and Plasma Compression by Backward Raman Amplification (BRA) in plasma, is proposed. It is called C3 for Cascaded Conversion Compression. It has the capability to compress with good efficiency kilojoule to megajoule, nanosecond laser pulses into femtosecond pulses, to produce exawatt and beyond peak power. In the future, C3 could be used at large-scale facilities such as the National Ignition Facility (NIF) or the Laser Megajoule (LMJ) and open the way to zettawatt level pulses. The beam will be focused to a wavelength spot size with a f#1. The very small beam size, i.e. few centimeters, along with the low laser repetition rate laser system will make possible the use of inexpensive, precision, disposable optics. The resulting intensity will approach the Schwinger value, thus opening up new possibilities in fundamental physics.Comment: 13 pages, 4 figure