Bias correction in logistic regression with missing categorical covariates

Logistic regression plays an important role in many fields. In practice, we often encounter missing covariates in different applied sectors, particularly in biomedical sciences. Ibrahim (1990) proposed a method to handle missing covariates in generalized linear model (GLM) setup. It is well known that logistic regression estimates using small or medium sized missing data are biased. Considering the missing data that are missing at random, in this paper we have reduced the bias by two methods; first we have derived a closed form bias expression using Cox and Snell (1968), and second we have used likelihood based modification similar to Firth (1993). Here we have analytically shown that the Firth type likelihood modification in Ibrahim led to the second order bias reduction. The proposed methods are simple to apply on an existing method, need no analytical work, with the exception of a little change in the optimization function. We have carried out extensive simulation studies comparing the methods, and our simulation results are also supported by a real world data.     

Corrected likelihood-ratio tests in logistic regression using small-sample data

Likelihood-ratio tests (LRTs) are often used for inferences on one or more logistic regression coefficients. Conventionally, for given parameters of interest, the nuisance parameters of the likelihood function are replaced by their maximum likelihood estimates. The new function created is called the profile likelihood function, and is used for inference from LRT. In small samples, LRT based on the profile likelihood does not follow χ² distribution. Several corrections have been proposed to improve LRT when used with small-sample data. Additionally, complete or quasi-complete separation is a common geometric feature for small-sample binary data. In this article, for small-sample binary data, we have derived explicitly the correction factors of LRT for models with and without separation, and proposed an algorithm to construct confidence intervals. We have investigated the performances of different LRT corrections, and the corresponding confidence intervals through simulations. Based on the simulation results, we propose an empirical rule of thumb on the use of these methods. Our simulation findings are also supported by real-world data.     

Collapsibility of regression coefficients and its extensions

Collapsibility with respect to a measure of association implies that the measure of association can be obtained from the marginal model. We first discuss model collapsibility and collapsibility with respect to regression coefficients for linear regression models. For parallel regression models, we give simple and different proofs of some of the known results and obtain also certain new results. For random coefficient regression models, we define (average) A$A$-collapsibility and obtain conditions under which it holds. We consider Poisson regression and logistic regression models also, and derive conditions for collapsibility and A$A$-collapsibility, respectively. These results generalize some of the results available in the literature. Some suitable examples are also discussed.     

Value‐Driven Creation of Functionality in Software Projects: Optimal Sequencing and Reuse

We study the problem of optimally sequencing the creation of elements in a software project to optimize a time‐weighted value objective. As elements are created, certain parts of the system (referred to as “groups”) become functional and provide value, even though the entire system has not been completed. The main tradeoff in the sequencing problem arises from elements that belong to multiple groups. On the one hand, creating groups with common elements early in the project reduces the effort required to build later functionality that uses these elements. On the other hand, the early creation of such groups can delay the release of some critical functionality. We formulate the element sequencing problem and propose a heuristic to solve it. This heuristic is compared against a lower bound developed for the problem. Next, we study a more general version of the element sequencing problem in which an element requires some effort to be made reusable. When a reusable element is used in another group, some more effort is needed to specialize the element to work as desired in that group. We study reuse decisions under a weighted completion time objective (i.e., the sum of the completion time of each group weighted by its value is minimized), and show how these decisions differ from those under a traditional makespan objective (i.e., only the final completion time of the project is minimized). A variety of analytical and numerical results are presented. The model is also implemented on data obtained from a real software project. A key finding of this work is that the optimal effort on reuse is never increased (typically lowered) when a weighted completion time objective is used. This finding has implications for managing reuse in projects in which user value influences the order in which functionality is created.     

Rationality in Strategic Information Technology Decisions: The Impact of Shared Domain Knowledge and IT Unit Structure*

Rationality is a fundamental concept to several models of IT planning and implementation. Though the importance of following rational processes in making strategic IT decisions is well acknowledged, there is not much understanding on why discrepancies occur in the IT decision‐making process and what factors affect rationality. Drawing upon structural and resource‐based perspectives of strategy, this study examines the influence of shared domain knowledge and IT unit structure on rationality in strategic IT decisions. Data were gathered from 223 senior IT executives using a survey to examine the relationships among the research constructs. The results suggest a positive impact of shared domain knowledge and formalization of IT unit structure on rationality in strategic IT decisions. Further, a highly centralized IT unit structure was found to negatively influence shared domain knowledge. On the other hand, formalization of IT structure positively influenced shared domain knowledge. The implications of the findings for research and practice are presented.     

Construct Measurement in Information Systems Research: An Illustration in Strategic Systems

This study seeks to highlight construct measurement issues in information systems (IS) research. It describes the normative process of construct measurement and identifies the difficult problems involved in measurement and some ways in which these difficulties may be overcome. An illustrative construct-operationalization study in the area of strategic systems outlines how the normative guidelines may be applied to IS. Some specific recommendations for IS include developing a preliminary model of the construct even if there is little previous measurement research, devoting greater attention to predictive validity because a lack of theories in IS precludes the examination of nomological validity, verifying the assumptions underlying the computation of an overall index, and examining the measurement properties of the index.     

A Virtual Cellular Manufacturing Approach to Batch Production*

In this paper, Virtual Cellular Manufacturing (VCM), an alternative approach to implementing cellular manufacturing, is investigated. VCM combines the setup efficiency typically obtained by Group Technology (GT) cellular manufacturing (CM) systems with the routing flexibility of a job shop. Unlike traditional CM systems in which the shop is physically designed as a series of cells, family-based scheduling criteria are used to form logical cells within a shop using a process layout. The result is the formation of temporary, virtual cells as opposed to the more traditional, permanent, physical cells present in GT systems. Virtual cells allow the shop to be more responsive to changes in demand and workload patterns. Production using VCM is compared to production using traditional cellular and job shop approaches. Results indicate that VCM yields significantly better flow time and due date performance over a wide range of common operating conditions, as well as being more robust to demand variability.     

The Prevalence and Types of Gambling Among Undocumented Mexican Immigrants in New York City

Objectives To examine the prevalence of gambling and types of gambling activities in a sample of undocumented Mexican immigrants. Design Non-probability cross-sectional design. Setting New York City. Sample The 431 respondents ranged in age from 18 to 80 (mean age 32), 69.7% were male. Results More than half (53.8%) reported gambling in their lifetime and of those most (43.9%) played scratch and win tickets or the lottery. In multivariate analyses men reported gambling more than women [2.13, 95% CI = (1.03, 4.38)]. The odds of gambling in their lifetime were higher among those reporting sending money to family or friends in the home country [2.65, 95% CI = 1.10, 6.38)], and those who reported 1–5 days as compared to no days of poor mental health in the past 30 days [2.44, 95% CI = 1.22, 4.89)]. Conversely, those who reported entering the U.S. to live after 1996 were less likely to report gambling [0.44, 95% CI = (0.22, 0.89)] as compared to those who had lived in the U.S. longer. Conclusion There is a need to further explore both the prevalence and the severity of gambling amongst the growing population of undocumented Mexican immigrants in the U.S.