Spatial smoothing of low birth weight rate in Bangladesh using Bayesian hierarchical model

The term low birth weight refers an event where a newborn baby has a weight that is less than 2500?g. This is an essential indicator while the interest is in public health issues such as infant mortality, maternal complications, and antenatal care, etc. of a country, particularly, for a developing country like Bangladesh. The regional development programs are in the current priority list of Bangladesh government and other policy makers. Many of such regional development programs may need the spatial distribution of relative risk for low birth weight that can be obtained by mapping the risks over small area domains like the districts of Bangladesh. This study aims to find whether is there any spatial dependence among the relative risks of low birth weight for the districts of Bangladesh. This has been investigated using Moran's I statistic and a significant spatial dependence in the relative risks was found. Then, attempt has been made to rediscover the spatial distribution based on the idea of spatial smoothing. A Bayesian hierarchical model is used considering percent received antenatal care and female labor force participation as covariates to smooth the observed relative risks of low birth weight in 64 districts of Bangladesh. Revised spatial distribution taking the spatial dependence under consideration through intrinsic conditional autoregressive model is derived and showed in choropleth map along with its different behaviors.     

Enrolling girls without learning: Evidence from public schools in Afghanistan

While more girls are now attending school in Afghanistan than prior to 2010, there is a lack of evidence on how school attendance is helping their cognitive development. We use data from a large sample of all‐girls state‐funded school students to estimate for the first time the “learning profile” for Afghanistan. Students enrolled in grades 4 to 9 were assessed using the Early Grade Reading Assessment (EGRA) and the Early Grade Mathematics Assessment (EGMA) test items. We find that higher grade progression (particularly in grades 6–9) leads to almost no gain in numeracy (addition and subtraction) skills that should have been achieved in early grades. Similar results follow from the analysis of student performance in the EGRA test, particularly in oral reading fluency (correct words read per minute) and oral reading comprehension (number of correct answers out of 12). These findings warn that simply enrolling girls in school without improving the relationship between grade completion and learning is unlikely to transform the lives of women in Afghanistan.     

Key considerations for choosing a statistical method to deal with incomplete treatment adherence in pragmatic trials

Pragmatic trials offer practical means of obtaining real-world evidence to help improve decision-making in comparative effectiveness settings. Unfortunately, incomplete adherence is a common problem in pragmatic trials. The commonly used methods in randomized control trials often cannot handle the added complexity imposed by incomplete adherence, resulting in biased estimates. Several naive methods and advanced causal inference methods (e.g., inverse probability weighting and instrumental variable-based approaches) have been used in the literature to deal with incomplete adherence. Practitioners and applied researchers are often confused about which method to consider under a given setting. This current work is aimed to review commonly used statistical methods to deal with non-adherence along with their key assumptions, advantages, and limitations, with a particular focus on pragmatic trials. We have listed the applicable settings for these methods and provided a summary of available software. All methods were applied to two hypothetical datasets to demonstrate how these methods perform in a given scenario, along with the R codes. The key considerations include the type of intervention strategy (point treatment settings, where treatment is administered only once versus sustained treatment settings, where treatment has to be continued over time) and availability of data (e.g., the extent of measured or unmeasured covariates that are associated with adherence, dependent confounding impacted by past treatment, and potential violation of assumptions). This study will guide practitioners and applied researchers to use the appropriate statistical method to address incomplete adherence in pragmatic trial settings for both the point and sustained treatment strategies.     

Participation in Decentralized Local Governance: Two Contrasting Cases from the Philippines

Contrary to the popular assumptions among international donor agencies, preceding studies have questioned the causal relations between decentralization, participation and pro-poor policy outcomes. This article introduces two cases of decentralized city governments in the Philippines: one employs radical forms of civil participation, while the other introduces modest ones, but both of them have been successfully launching pro-poor policies. Through referring these contrasting cases to a “participatory governance” model and a “governance with trusts” model, the paper argues that the approach to local governance is not linear.

Quadratic fractional age assumption revisited

This paper introduces a quadratic fractional age assumption which makes the force of mortality and survival function continuous at all ages. The necessary and sufficient condition for the assumption to be valid is derived. Important life table parameters are estimated and applications are shown using several life table data.     

Does location influence executive compensation? Evidence from Canadian SMEs

We examine the impact of geographic location on the level and structure of executive compensation of small and medium enterprises (SMEs) in Canada, using a panel data sample between 2008 and 2011. Our results show that SMEs pay a higher price for talent by paying a large proportion (71%) of compensation as guaranteed cash pay to their executives. We also report a strong influence of location on compensation structure. Specifically, rural firms pay 13% more incentive based equity pay to their executives compared to their size matched urban counterparts. However, there is no difference between the total compensation for managers of rural and urban firms after controlling for the cost of living index. In cross-sectional tests, we observe that total compensation is positively related to CEO/Chair duality and family ownership but is not related to management quality. In addition, we find that rural firms display a higher pay-performance sensitivity.     

Penalized and Shrinkage Estimation in the Cox Proportional Hazards Model

This article considers the shrinkage estimation procedure in the Cox's proportional hazards regression model when it is suspected that some of the parameters may be restricted to a subspace. We have developed the statistical properties of the shrinkage estimators including asymptotic distributional biases and risks. The shrinkage estimators have much higher relative efficiency than the classical estimator, furthermore, we consider two penalty estimators—the LASSO and adaptive LASSO—and compare their relative performance with that of the shrinkage estimators numerically. A Monte Carlo simulation experiment is conducted for different combinations of irrelevant predictors and the performance of each estimator is evaluated in terms of simulated mean squared error. Simulation study shows that the shrinkage estimators are comparable to the penalty estimators when the number of irrelevant predictors in the model is relatively large. The shrinkage and penalty methods are applied to two real data sets to illustrate the usefulness of the procedures in practice.     

A novel weighted likelihood estimation with empirical Bayes flavor

We propose a novel approach to estimation, where a set of estimators of a parameter is combined into a weighted average to produce the final estimator. The weights are chosen to be proportional to the likelihood evaluated at the estimators. We investigate the method for a set of estimators obtained by using the maximum likelihood principle applied to each individual observation. The method can be viewed as a Bayesian approach with a data-driven prior distribution. We provide several examples illustrating the new method and argue for its consistency, asymptotic normality, and efficiency. We also conduct simulation studies to assess the performance of the estimators. This straightforward methodology produces consistent estimators comparable with those obtained by the maximum likelihood method. The method also approximates the distribution of the estimator through the “posterior” distribution.     

Geriatric Care during Public Health Emergencies: Lessons Learned from Novel Corona Virus Disease (COVID-19) Pandemic

ABSTRACT

Geriatric care in public health emergencies is a serious concern, while, high case-fatalities among older adults across the globe in COVID-19 pandemic implies lack of preparedness. Most of the countries irrespective of developing and developed one enormously struggling because of an inchoate response system ignorant of geriatric health needs. Therefore, a robust approach is highly essential that requires an integrated emergency preparedness by addressing geriatric care.     

Comments on ‘Application of an adaptive design to a randomized phase II selection trial in gastric cancer: a report of the study design’ by Satoshi Morita and Junichi Sakamoto. Pharmaceutical Statistics

In this commentary, we show that the treatment selection probabilities in Morita and Sakamoto [1] could be different if safety information is considered. Copyright © 2012 John Wiley & Sons, Ltd.