Joint modelling of longitudinal response and time-to-event data using conditional distributions: a Bayesian perspective

Over the last 20 or more years a lot of clinical applications and methodological development in the area of joint models of longitudinal and time-to-event outcomes have come up. In these studies, patients are followed until an event, such as death, occurs. In most of the work, using subject-specific random-effects as frailty, the dependency of these two processes has been established. In this article, we propose a new joint model that consists of a linear mixed-effects model for longitudinal data and an accelerated failure time model for the time-to-event data. These two sub-models are linked via a latent random process. This model will capture the dependency of the time-to-event on the longitudinal measurements more directly. Using standard priors, a Bayesian method has been developed for estimation. All computations are implemented using OpenBUGS. Our proposed method is evaluated by a simulation study, which compares the conditional model with a joint model with local independence by way of calibration. Data on Duchenne muscular dystrophy (DMD) syndrome and a set of data in AIDS patients have been analysed.     

A Cascaded Inference Model for Evaluation of the Internal Audit Report*

This paper provides a normative framework for how external auditors should evaluate internal audit (IA) work, with a view to assessing the risk of material misstatement. The central issue facing the external auditor when evaluating IA work is the reliability of IA work. Reliability assessments are structured using the cascaded inference framework from behavioral decision theory, in which attributes of source reliability are explicitly modeled and combined using Bayes' rule in order to determine the inferential value of IA work. Results suggest that the inferential value of an IA report is highly sensitive to internal auditor reporting bias, but relatively insensitive to reporting veracity. Veracity refers to internal auditors' propensity to report truthfully, whereas bias refers to the propensity to misreport findings. Results also indicate that this sensitivity to reporting bias is conditional on the level of internal auditor competence, thus suggesting significant interaction effects between the objectivity and competence factors. Collectively, these findings suggest that the impact of source reliability attributes may be more complex than portrayed in the auditing standards and that recognizing these subtleties may lead to greater efficiency and effectiveness.     

Integrality in Stochastic Inventory Models

We study several finite‐horizon, discrete‐time, dynamic, stochastic inventory control models with integer demands: the newsvendor model, its multi‐period extension, and a single‐product, multi‐echelon assembly model. Equivalent linear programs are formulated for the corresponding stochastic dynamic programs, and integrality results are derived based on the total unimodularity of the constraint matrices. Specifically, for all these models, starting with integer inventory levels, we show that there exist optimal policies that are integral. For the most general single‐product, multi‐echelon assembly system model, integrality results are also derived for a practical alternative to stochastic dynamic programming, namely, rolling‐horizon optimization by a similar argument. We also present a different approach to prove integrality results for stochastic inventory models. This new approach is based on a generalization we propose for the one‐dimensional notion of piecewise linearity with integer breakpoints to higher dimensions. The usefulness of this new approach is illustrated by establishing the integrality of both the dynamic programming and rolling‐horizon optimization models of a two‐product capacitated stochastic inventory control system.     

Optimum covariate designs in split-plot and strip-plot design set-ups

The problem considered is that of finding optimum covariate designs for estimation of covariate parameters in standard split-plot and strip-plot design set-ups with the levels of the whole-plot factor in r randomised blocks. Also an extended version of a mixed orthogonal array has been introduced, which is used to construct such optimum covariate designs. Hadamard matrices, as usual, play the key role for such construction.     

A Stochastic Inventory Model With Fast‐Ship Commitments

We present a multiperiod model of a retail supply chain, consisting of a single supplier and a single retailer, in which regular replenishment occurs periodically but players have the option to support fast delivery when customers experience a stockout during a replenishment period. Because expedited shipments increase the supplier's transportation cost, and possibly production/inventory costs, the supplier typically charges a markup over and above the prevailing wholesale price for fast‐shipped items. When fast shipping is not supported, items are backordered if customers are willing to wait until the start of the next replenishment period. We characterize the retailers and the supplier's optimal stocking and production policies and then utilize our analytical framework to study how the two players respond to changes in supply chain parameters. We identify a sufficient condition such that the centralized supply chain is better off with the fast‐ship option. We find a range of markups for fast‐ship orders such that the fast‐ship option is preferred by both the supplier and the retailer in a decentralized chain. However, a markup that is a win–win for both players may not exist even when offering fast‐ship option is better for the centralized chain. Our analysis also shows that depending on how the markup is determined, greater customer participation in fast‐ship orders does not necessarily imply more profits for the two players. For some predetermined markups, the retailer's profit with the fast‐ship option is higher when more customers are willing to wait. However, the retailer may not be able to benefit from the fast‐ship option because the supplier may choose not to support the fast‐ship option when fast‐ship participation increases due to the fact that the fast‐ship participation rate adversely affects the initial order size.     

印度汽车市场崛起

尽管大多数印度人依然在用两轮交通工具，但新兴的印度中产阶级却给汽车销售业带来了有力的推动——至少当下如此。     

Strategy-proof Cardinal Decision Schemes

This paper analyses strategy-proof mechanisms or decision schemes which map profiles of cardinal utility functions to lotteries over a finite set of outcomes. We provide a new proof of Hylland’s theorem which shows that the only strategy-proof cardinal decision scheme satisfying a weak unanimity property is the random dictatorship. Our proof technique assumes a framework where individuals can discern utility differences only if the difference is at least some fixed number which we call the grid size. We also prove a limit random dictatorship result which shows that any sequence of strategy-proof and unanimous decision schemes defined on a sequence of decreasing grid sizes approaching zero must converge to a random dictatorship. We are most grateful to an Associate Editor and two referees for very helpful comments on an earlier version of the paper. An erratum to this article can be found at     

Experiences of Young Indian Girls Transiting out of Residential Care Homes

Leaving the residential care home is one of the most significant occurrence in the life of every care‐leaver. It encompasses vast changes which has a long term impact on the care‐leavers future. This study captures the lived experiences of twenty‐four young Indian girls who have left care in the past four years. It addresses their journey of moving out of care at two levels — their preparation to leave care and their present experience. The primary focus of the study is to explore the interpretation and meanings attributed by these girls to the phenomena of transition out of care; identifying the uniqueness and commonalities that emerges from their experiences. The results exposes a plethora of emotions and episodes the girls have encountered at each step of their path. It also emphasises on the role played by multiple environmental factors — support network (friends, peer group, family, social workers, etc.), residential care home, state and other social processes — operating at different systemic levels, highlighting the interface between the ‘self’ and the ‘environment’, based on the Ecological Framework.     

Provision of basic services in slums: A review of the evidence on top‐down and bottom‐up approaches

This article synthesizes the evidence on the effectiveness of top‐down and bottom‐up approaches in providing basic services in slums in developing countries. The findings indicate that: (1) government‐led top‐down approaches focus predominantly on connectivity, but approaches led by community‐based organizations (CBOs) and non‐government organizations (NGOs) improve many additional dimensions of access; (2) legal recognition of slums improves access to services in both approaches; and (3) NGO and CBO involvement results in the right balance between the technical, social and financial resources required for effective service delivery.     

A semiparametric modeling approach for analyzing clinical biomarkers restricted to limits of detection

Before biomarkers can be used in clinical trials or patients' management, the laboratory assays that measure their levels have to go through development and analytical validation. One of the most critical performance metrics for validation of any assay is related to the minimum amount of values that can be detected and any value below this limit is referred to as below the limit of detection (LOD). Most of the existing approaches that model such biomarkers, restricted by LOD, are parametric in nature. These parametric models, however, heavily depend on the distributional assumptions, and can result in loss of precision under the model or the distributional misspecifications. Using an example from a prostate cancer clinical trial, we show how a critical relationship between serum androgen biomarker and a prognostic factor of overall survival is completely missed by the widely used parametric Tobit model. Motivated by this example, we implement a semiparametric approach, through a pseudo-value technique, that effectively captures the important relationship between the LOD restricted serum androgen and the prognostic factor. Our simulations show that the pseudo-value based semiparametric model outperforms a commonly used parametric model for modeling below LOD biomarkers by having lower mean square errors of estimation.