bluuebunny/crossref_metadata_2025 huggingface dataset:
Developments in nonconventional machining for sustainable production: A state-of-the-art review
Authors: Gupta Kapil , Gupta Munish Kumar
Published: November 2018

Nonconventional or advanced machining processes such as electric discharge machining, electrochemical machining, abrasive water jet machining, and laser beam machining have been widely used as a viable alternate to the conventional processes to manufacture high-quality engineered parts having certain typical features. In spite of their special features, wider acceptance, and use, they suffer from certain inherent limitations with regard to sustainability such as high consumption of energy and resources; generation of toxic liquid, gases, and solid wastes; risk for health and safety; air pollution; generation of waste and its disposal problems; and workpiece contamination and thermal damage to the parts being produced. It is found that these factors all adversely affect the environment to a certain extent. Innovative sustainable techniques such as dry, near-dry, and green electric discharge machining; green and hybrid electrochemical machining; ice-jet machining; and eco- and underwater laser beam machining, etc. have been developed to address sustainability challenges and greatly benefited with improvements in quality, productivity, and sustainability. This review article first introduces four major nonconventional machining processes, discusses their inherent sustainability issues and challenges, and presents state-of-the-art review of the work conducted using sustainable innovative techniques and strategies with an aim to encourage academics, researchers, and engineers for research and developments in order to establish the field further. The literature review offered in this article is based on over 80 articles published from 1975 to 2017. Finally, the article ends up with concluding remarks and recommending possible avenues to stimulate future research.
Relative train length and the infrastructure required to mitigate delays from operating combinations of normal and over-length freight trains on single-track railway lines in North America
Authors: Dick C Tyler , Atanassov Ivan , Kippen F Bradford , Mussanov Darkhan
Published: November 2018

Distributed power locomotives have facilitated longer heavy-haul freight trains that improve the efficiency of railway operations. In North America, where the majority of mainlines are single track, the potential operational and economic advantages of long trains are limited by the inadequate length of many existing passing sidings (passing loops). To alleviate the challenge of operating trains that exceed the length of passing sidings, railways preserve the mainline capacity by extending passing sidings. However, industry practitioners rarely optimize the extent of infrastructure investment for the volume of over-length train traffic on a particular route. This paper investigates how different combinations of normal and over-length trains, and their relative lengths, relate to the number of siding extensions necessary to mitigate the delay performance of over-length train operation on a single-track rail corridor. The experiments used Rail Traffic Controller simulation software to determine train delay for various combinations of short and long train lengths under different directional distributions of a given daily railcar throughput volume. Simulation results suggest a relationship between the ratio of train lengths and the infrastructure expansion required to eliminate the delay introduced by operating over-length trains on the initial route. Over-length trains exhibit delay benefits from siding extensions while short trains are relatively insensitive to the expanded infrastructure. Assigning directional preference to over-length trains improves the overall average long-train delay at the expense of delay to short trains. These results will allow railway practitioners to make more informed decisions on the optimal incremental capital expansion strategy for the operation of over-length trains.
Promoting policy consistency and continuity in the EU through the trio: Alcohol-related harm on the council presidency agenda
Authors: Ugland Trygve
Published: November 2018

To what extent has the new trio group presidency model that was implemented in 2007 contributed to improved policy consistency and continuity in the European Union (EU)? This article addresses this question by comparing the role alcohol, as a health and social policy issue, has played on the agenda of individual national and trio Council presidencies since the EU Alcohol Strategy was adopted in 2006. Based on systematic analyses of 21 national and 7 trio Council presidency work programmes in the period between 2007 and 2017, the article concludes that the new trio presidency model has led to improved policy consistency and continuity through its promotion of the wider EU agenda, thus contributing to strengthen the image of the Council as a ‘club’. The close relationship between the European Commission and the trio presidencies in the preparation of the joint trio work programmes is here a key factor.
A 12,700-year history of paleolimnological change from an Andean microrefugium
Authors: de Novaes Nascimento Majoi , Laurenzi Anne Gail , Valencia Bryan G , Van Robert , Bush Mark
Published: November 2018

We present a 12,6700-yr limnological history of Lake Miski, a high-elevation lake in a wet section of the Peruvian Andes. While many shallow Andean lakes dried up during the mid-Holocene, loss-on-ignition, magnetic susceptibility, and diatom analysis showed that Lake Miski was a constant feature in the landscape. Overall, fluctuations in the fossil diatom communities of Lake Miski tracked changes in insolation, but this was not the only mechanism influencing observed variability. We identify periods when insolation and interactions with the Pacific Ocean may have played a role in structuring local climate and diatom assemblages. The true mid-Holocene Dry Event (MHDE) is manifested in this record between 8000 and 5000 cal BP, but the carbonate stratigraphy and the diatom community indicated that although the level of the lake decreased, it never completely dried out, instead there was higher availability of planktic habitat and stronger mixing than in much of the Holocene. High rates of biological change observed during the late-Holocene in other records from Peru associated with human amplification of climatic signals were not observed in Lake Miski, as this lake may have been too wet and remote to be strongly influenced by human activity. Because of the presence of a woodland microrefugium, Lake Miski was suggested to have been an unusually climatically stable and wet location during the regional drying associated with the MHDE. Our new limnological information provides additional insights relating to this discussion. The presence of the observed woodland apparently withstood fluctuations that induced state changes in the lake and diatom flora, underscoring that microrefugia do not equate to ‘unchanging’ hydrologies or climates.
Plasma cytokines as potential biomarkers of kidney damage in patients with systemic lupus erythematosus
Authors: Pacheco-Lugo L. , Sáenz-García J. , Navarro Quiroz E , González Torres H. , Fang L. , Díaz-Olmos Y. , Garavito de Egea G. , Egea Bermejo E. , Aroca Martínez G.
Published: November 2018

Background

Systemic lupus erythematosus is a heterogeneous chronic inflammatory autoimmune disorder characterized by an exacerbated expression of cytokines and chemokines in different tissues and organs. Renal involvement is a significant contributor to the morbidity and mortality of systemic lupus erythematosus, and its diagnosis is based on renal biopsy, an invasive procedure with a high risk of complications. Therefore, the development of alternative, non-invasive diagnostic tests for kidney disease in patients with systemic lupus erythematosus is a priority.

Aim

To evaluate the plasma levels of a panel of cytokines and chemokines using multiplex xMAP technology in a cohort of Colombian patients with active and inactive systemic lupus erythematosus, and to evaluate their potential as biomarkers of renal involvement.

Results

Plasma from 40 systemic lupus erythematosus non-nephritis patients and 80 lupus nephritis patients with different levels of renal involvement were analyzed for 39 cytokines using Luminex xMAP technology. Lupus nephritis patients had significantly increased plasma eotaxin, TNF-α, interleukin-17-α, interleukin-10, and interleukin-15 as compared to the systemic lupus erythematosus non-nephritis group. Macrophage-derived chemokine, growth regulated oncogene alpha, and epidermal growth factor were significantly elevated in systemic lupus erythematosus non-nephritis patients when compared to lupus nephritis individuals. Plasma eotaxin levels allowed a discrimination between systemic lupus erythematosus non-nephritis and lupus nephritis patients, for which we performed a receiver operating characteristic curve to confirm. We observed a correlation of eotaxin levels with active nephritis (Systemic Lupus Erythematosus Disease Activity Index). Our data indicate that circulating cytokines and chemokines could be considered good predictors of renal involvement in individuals with systemic lupus erythematosus.
HEART pathway and Emergency Department Assessment of Chest Pain Score–Accelerated Diagnostic Protocol application in a local emergency department of Hong Kong: An external prospective validation study
Authors: Yang Siu Ming , Chan Chi Ho , Chan Tung Ning
Published: November 2018

Background:

The conventional chest pain protocol using thrombolysis in myocardial infarction score as the risk stratifying tool may not perform well in the emergency department in which a mix of low- and high-risk patients are encountered. Newer chest pain scores such as HEART pathway and Emergency Department Assessment of Chest Pain Score–Accelerated Diagnostic Protocol (EDACS-ADP) are found to have high sensitivity with good specificity.

Objectives:

This study aims to validate and compare two chest pain scores: HEART pathway and EDACS-ADP in the Accident and Emergency Department of a local hospital in Hong Kong.

Methods:

A prospective cohort study was carried out at the Accident and Emergency Department of Kwong Wah Hospital in Hong Kong from 1 June 2016 to 31 May 2017. Patients ⩾18 years old with chest pain lasting 5 min or more who were observed with chest pain protocol on observation ward were recruited.

Results:

A total of 238 patients were recruited; 231 eligible patients completed follow-up. There were five patients with major adverse cardiac events in 30 days of follow-up. The sensitivity, specificity, and negative predictive values of HEART pathway and EDACS-ADP were 100%, 74.3%, 100% and 100%, 73.5.0% and 100%, respectively. Both scores had almost the same performance in terms of major adverse cardiac events at 30 days (area under the curve = 0.87).

Conclusion:

Our study showed both EDACS-ADP (modified) and HEART pathway achieved high sensitivity (~100%) for detecting major adverse cardiac events in 30 days while being able to discharge more than 70% of patients as low risk for early discharge.
Pulmonary Embolism Response Teams: A Novel Approach for the Care of Complex Patients With Pulmonary Embolism
Authors: Porres–Aguilar Mateo , Anaya-Ayala Javier E. , Heresi Gustavo A. , Rivera-Lebron Belinda N.
Published: November 2018

Pulmonary embolism represents the third most common cause of cardiovascular death in the United States. Reperfusion therapeutic strategies such as systemic thrombolysis, catheter directed therapies, surgical pulmonary embolectomy, and cardiopulmonary support devices are currently available for patients with high- and intermediate-high–risk pulmonary embolism. However, deciding on optimal therapy may be challenging. Pulmonary embolism response teams have been designed to facilitate multidisciplinary decision-making with the goal to improve quality of care for complex cases with pulmonary embolism. Herein, we discuss the current role and strategies on how to leverage the strengths from pulmonary embolism response teams, its possible worldwide adoption, and implementation to improve survival and change the paradigm in the care of a potentially deadly disease.
Unique Biology and Single-Channel Properties of GluN2A- and GluN2C-Containing Triheteromeric N-Methyl-D-Aspartate Receptors
Authors: Bhattacharya Subhrajit , Traynelis Stephen F
Published: November 2018

Triheteromeric N-methyl-D-aspartate receptors (NMDARs) are assemblies of two different types of GluN2 subunits that endow receptors with properties distinct from their diheteromeric counterparts. Previous studies show an abundance of triheteromeric NMDARs across the central nervous system (CNS), making them an important receptor population to investigate and potential drug target. A recent study by Bhattacharya et al. (1) demonstrated the prevalence of GluN1/GluN2A/GluN2C triheteromeric NMDARs in cerebellar granule cells (CGCs), (2) suggested that GluN2C subunits seldom express as diheteromers, (3) suggested that GluN2A subunits are the preferred partners for GluN2C to functionally express at the cell surface, and (4) revealed unique single-channel properties of these triheteromeric assemblies, which may enable these cells to perform unique tasks. Taken together, this work demonstrates the physiological existence of GluN1/GluN2A/GluN2C receptors in the CGCs.
More than stigma: Interrogating counter narratives of abortion
Authors: Baird Barbara , Millar Erica
Published: November 2018

A large body of feminist scholarship identifies and examines modes of representing abortion, focusing on themes such as stigma and the production of an autonomous foetal subject. In recent years, there has been a proliferation of cultural representations of abortion that do not conform with, and even explicitly reference and rebuke, stigmatising and foetocentric depictions of abortion. Focusing on the Australian context and two sets of online sites—the websites of Australian abortion clinics and widely circulated pro-choice, feminist commentary on abortion—this article provides a critical reading of new, ‘unapologetic’ modes of representing abortion. We argue that they increase the cultural legitimacy of abortion and are therefore incredibly important, but have limitations because of their reification of the neoliberal autonomous subject. Nevertheless, we urge feminist scholars to pay more attention to discourses that presume abortion is unproblematic and beneficial to women. Scholarship on abortion has performative effects, and we hope that identifying and nurturing counter narratives of abortion is one means by which abortion can be normalised.
Gendering asexuality and asexualizing gender: A qualitative study exploring the intersections between gender and asexuality
Authors: Gupta Kristina
Published: November 2018

In this article, I explore the intersections between gender and asexuality, drawing on data collected from in-depth interviews with 30 asexually-identified individuals living in the United States. I examine the differential effects that gendered sexual norms have on asexually-identified men and women and begin to explore the relationship between asexuality, gender non-conformity, and trans* identities. Based on these findings, I argue that while white, middle-class asexually-identified men may live in greater conflict with dominant gendered sexual norms than white, middle-class asexually-identified women, the sexual autonomy of these asexually-identified men – specifically their right to refuse sexuality – may be greater than the sexual autonomy of these asexually-identified women.
Telling a poor man he can become rich: Reparative therapy in contemporary Poland
Authors: Mikulak Magdalena
Published: November 2018

This article investigates the practice of sexual reorientation therapy, or reparative therapy (RT), in contemporary Poland. Focusing on three groups – Odwaga (Courage), Pomoc 2002 (Help 2002) and Pascha (Passover) – and informed by interviews with their past participants, it examines the ways in which RT in Poland is gendered, as well as investigating the individualizing and self-responsibilizing understandings of the self it rests on. This article then demonstrates how the neoliberal ideas of selfhood permeate the practice of RT, mobilizing the tropes of individual effort and responsibility for the reorientation of one’s sexual desire, obscuring the inherent inequality on which the practice is based.
Coping with the unfamiliar: How do children cope with hospitalization in relation to acute and/or critical illness? A qualitative metasynthesis
Authors: Jepsen Stine Leegaard , Haahr Anita , Eg Marianne , Jørgensen Lene Bastrup
Published: November 2018

The aim of this study was to identify and describe how young children cope with hospitalization in relation to acute and/or critical illness. The study is a qualitative metasynthesis inspired by the approach described by Sandelowski and Barroso. Based on an exhaustive literature search, six studies were included. Data were analyzed through a taxonomic analysis. The findings revealed that the hospitalized children face a variety of challenges during admission to the hospital due to acute and/or critical illness. The main challenge was that hospitalized children strive to cope with different aspects of ‘the unfamiliar’ that emerge in their illness treatment and hospital stay. The unfamiliar refers to unknown experiences on a physical, emotional, and relational level. Subsequently, children cope with the unfamiliar by striving to convert the hospital stay into something more similar to everyday life, using strategies to secure basic needs and constructing familiarity in the hospital stay. The consequences of the children’s coping behavior are discussed and how children strive to keep their integrity intact during illness and hospitalization are revealed.
Green bonds in China and the Sino-British collaboration: More a partnership of learning than commerce
Authors: Zhang Le-Yin
Published: November 2018

This article explores the role of Sino-British collaboration in promoting green bond development in China, the extent to which it meets the United Kingdom’s wider objectives regarding the UK-China bilateral relationship and the underlying factors. Drawing on desk research and interviews, it tests and validates the hypothesis that the key driving force for this development is the coupling of the financialisation of the Chinese economy and the politics of ‘ecological civilisation’, although learning through international interaction has also played a role. It further shows that the scope for the United Kingdom to benefit from this growth is limited by the structure of UK-China trade, China’s strong macro-economic control and its approach to international relations that prioritises learning and identity transformation rather than the opening up of its markets. Inter-hub competition also plays a part.
Peer researchers in post-professional healthcare: A glimpse at motivations and partial objectivity as opportunities for action researchers
Authors: Eaton Andrew D , Tsang A Ka Tat , Craig Shelley L , Ginocchio Galo F
Published: November 2018

Peer researchers are members of a population under study who have a decision-making role or staff position on a research team. Peer researchers are increasingly required for funding proposals to succeed in Canadian HIV/AIDS research, and are strongly recommended for community-based participatory research in other fields. There is a need to better understand peer researchers’ motivations and their impact, both positive and negative, on studies they take part in. The emerging theory of post-professionalism informed a bounded system case study approach, whereby four peer researchers from an HIV, social work, and brain health study were conveniently sampled, then interviewed concerning their experiences and insider-outsider positioning. Personal interest and community leadership were key motivations behind their involvement; language barriers and managing multiple roles were key challenges. Participants identified a risk inherent in the performative interval, considering whether their contributions were a projection of self rather than a representation of participant contributions. Tension between social location and the insider positioning expected of peer researchers requires that academic researchers recognize the personal and social investments that peers make to a study. This paper presents considerations for how healthcare researchers can better engage as peers with peer researchers.
In search of policy that supports educational innovation: Perspective of a place- and community-based elementary school
Authors: Blenkinsop Sean , Maitland Clayton , MacQuarrie Jodi
Published: November 2018

This paper, based upon our experiences starting a school, is part dialogue and part theory. The three authors have all played important roles in the design, creation, and ongoing support of an innovative public elementary school. The first part of the paper describes the impetus behind the creation of this “buildingless,” environmentally focused school with a mandate toward cultural change. There follows a discussion of the kinds of policy that have appeared over the lifespan of the school and includes the identification of those that hindered and those that helped. The final section uses some recent work in social innovation policy to inform a discussion with regard to our policy recommendations for those interested in supporting the kinds of local, place- and community-based educational innovations described here.
Informing Human Trafficking Clinical Care Through Two Systematic Reviews on Sexual Assault and Intimate Partner Violence
Authors: Menon Blaine , Stoklosa Hanni , Van Dommelen Kaylee , Awerbuch Adam , Caddell Luke , Roberts Ken , Potter Jonell
Published: November 2018

Background:

There is a lack of evidence on the clinical management of patients who have suffered human trafficking. Synthesizing the evidence from similar patient populations may provide valuable insight. This review summarizes findings on therapeutic interventions for survivors of sexual assault and intimate partner violence (IPV).

Method:

We conducted two systematic reviews using the MEDLINE database. We included only randomized controlled trials of therapies with primary outcomes related to health for survivors of sexual assault and IPV. For the sexual assault review, there were 78 abstracts identified, 16 full-text articles reviewed, and 10 studies included. For the IPV review, there were 261 abstracts identified, 24 full-text articles reviewed, and 17 studies included. Analysis compared study size, intervention type, patient population, primary health outcomes, and treatment effect.

Results:

Although our search included physical and mental health outcomes, almost all the studies meeting inclusion and exclusion criteria focused on mental health. The interventions for sexual assault included spiritually focused group therapy, interference control training, image rehearsal therapy, sexual revictimization prevention, educational videos, cognitive behavioral therapy, and exposure therapy. The interventions in the IPV review included group social support therapy, exposure therapy, empowerment sessions, physician counseling, stress management programs, forgiveness therapy, motivational interviewing, and interpersonal psychotherapy.

Conclusions:

Insights from these reviews included the importance of culturally specific group therapy, the central role of survivor empowerment, and the overwhelming focus on mental health. These key features provide guidance for the development of interventions to improve the health of human trafficking survivors.
Acute high-intensity interval exercise induces greater levels of serum brain-derived neurotrophic factor in obese individuals
Authors: Rodriguez Alexandra L , Whitehurst Michael , Fico Brandon G , Dodge Katelyn M , Ferrandi Peter J , Pena Gabriel , Adelman Avraham , Huang Chun-Jung
Published: November 2018

Obesity may attenuate the expression of brain-derived neurotrophic factor (BDNF), thereby increasing the risk of cognitive dysfunction. High-intensity interval exercise (HIIE) has been shown to be as or more effective than continuous moderate-intensity exercise (CME) in promoting the expression of BDNF in normal-weight individuals. Therefore, the primary purpose of this study was to examine whether or not acute HIIE could be utilized as a practical model to explore the BDNF response in obese versus normal-weight subjects when compared to acute CME. The potential relationship of exercise-induced BDNF with blood lactate and cortisol was also examined. Twelve male subjects (six obese and six normal-weight) participated in a counterbalanced and caloric equated experiment: HIIE (30 min, 4 intervals of 4 min at 80%–90% of VO2max with 3 min of active recovery at 50–60% VO2max) and CME (38 min at 50%–60% VO2max). Blood samples were collected prior to, immediately following exercise, and 1 h into recovery for measurements of serum BDNF, blood lactate, and plasma cortisol. Our results showed that the BDNF response to acute HIIE was greater than CME in obese subjects when compared to normal-weight subjects. Similarly, although acute HIIE induced greater blood lactate and plasma cortisol levels than CME, obese subjects produced less blood lactate, but no difference in cortisol than normal-weight subjects. These findings suggest that acute HIIE may be a more effective protocol to upregulate BDNF expression in an obese population, independent of increased lactate and cortisol levels.

Impact statement

High-intensity interval exercise (HIIE) has been shown to be a time-efficient exercise strategy that provides similar or superior physiological benefits as traditional continuous moderate-intensity exercise (CME). Our previous study demonstrated an equivalent elevation on the BDNF response in both obese and normal-weight individuals following 30 min of acute CME. To discover a time-efficient exercise strategy to improve brain health in an obese population, the present study found that obese individuals elicit a greater level of BDNF following acute HIIE versus CME than normal-weight individuals. These findings indicate that acute HIIE may be an effective strategy to upregulate BDNF expression in obese individuals.
Predicted Probabilities for Count Models
Authors: Long J. Scott , Freese Jeremy
Published: November 2018

The post-estimation command prcounts for generating predicted probabilities after using poisson, nbreg, zip, and zinb is introduced and illustrated.
Speaking Stata: How to Repeat Yourself without going Mad
Authors: Cox Nicholas J.
Published: November 2018

This column will focus on how to improve your fluency in Stata. Over the next issues we will look at Stata problems of intermediate size which turn out to be soluble with a few command lines. As an introduction, systematic ways of repeating the same or similar operations are surveyed to give one overview of the territory to be covered.
Generalized Lorenz Curves and Related Graphs: An Update for Stata 7
Authors: Van Kerm Philippe , Jenkins Stephen P.
Published: November 2018

The glcurve command is updated to a Stata 7 version, glcurve7, which is described and illustrated.
Analyzing Distances
Authors: Fenty Justin
Published: November 2018

Gower and Krzanowski (1999) described the analysis of a multivariate dataset that violated the assumptions of normality for multivariate analysis of variance. They developed a method comprising two aspects: a graphical representation of the points in a fewer number of dimensions, known as principal coordinate analysis; and a technique similar to MANOVA except that it was based on partitioning the distances between subjects, rather than sums of squares, and did not assume that the data followed any particular distribution. This article summarizes both aspects of their analysis and describes the Stata pco and aod commands, which perform principal coordinate analysis and analysis of distance.
Semi-nonparametric Estimation of Extended Ordered Probit Models
Authors: Stewart Mark B.
Published: November 2018

This paper presents a semi-nonparametric estimator for a series of generalized models that nest the ordered probit model and thereby relax the distributional assumption in that model. It describes a new Stata command for fitting such models and presents an illustration of the approach.
Review of Regression Models for Categorical Dependent Variables Using Stata by Long and Freese
Authors: Hendrickx John
Published: November 2018

The new book Long and Fresse (2001) is reviewed.
Estimation of Sensitivity and Specificity Arising from Validity Studies with Incomplete Designs
Authors: Reichenheim Michael E. , de Leon Antônio Ponce
Published: November 2018

This insert introduces valides, validesi, and validesu, a set of commands that allow the calculations of point and precision estimates of sensitivity and specificity obtained in validity studies with incomplete designs.
Two-graph Receiver Operating Characteristic
Authors: Reichenheim Michael E.
Published: November 2018

The command roctg allows visualizing sensitivity (Se)and specificity (Sp) curves according to the range of values of a new diagnostic test, given a “true” state of an event, the reference test. On request, several options for displaying Se and Sp estimates in, or enhancements for, the graphs are also available.
Speaking Stata: On Getting Functions to do the Work
Authors: Cox Nicholas J.
Published: November 2018

Functions in Stata take two main forms, built-in functions that are part of the executable and egen functions written in Stata's own language. These are surveyed, giving a variety of tips and tricks, and noting the large number of user-written egen functions available for download from the Internet. Two substantial examples, the calculation of percentile ranks and plotting positions, and the calculation of measures summarizing properties of the other members of a group, provide detailed illustrations of egen in action.
Speaking Stata: Problems with Lists
Authors: Cox Nicholas J.
Published: November 2018

Various problems in working through lists are discussed in view of changes in Stata 8. for is now undocumented, which provokes a detailed examination of ways of processing lists in parallel with foreach, forvalues, and other devices, including new, concise ways of incrementing and decrementing macros and evaluating other expressions to do with macros in place. New features for manipulating lists held in macros and the new levels command are also reviewed.
Odds Ratios and Logistic Regression: Further Examples of their use and Interpretation
Authors: Hailpern Susan M. , Visintainer Paul F.
Published: November 2018

Logistic regression is perhaps the most widely used method for adjustment of confounding in epidemiologic studies. Its popularity is understandable. The method can simultaneously adjust for confounders measured on different scales; it provides estimates that are clinically interpretable; and its estimates are valid in a variety of study designs with few underlying assumptions. To those of us in practice settings, several aspects of applying and interpreting the model, however, can be confusing and counterintuitive. We attempt to clarify some of these points through several examples. We apply the method to a study of risk factors associated with periventricular leucomalacia and intraventricular hemorrhage in neonates. We relate the logit model to Cornfield's 2 x 2 table and discuss its application to both cohort and case–control study design. Interpretations of odds ratios, relative risk, and β0 from the logit model are presented.
Tools for Analyzing Multiple Imputed Datasets
Authors: Carlin John B. , Li Ning , Greenwood Philip , Coffey Carolyn
Published: November 2018

The method of multiple imputation (MI) is used increasingly for analyzing datasets with missing observations. Two sets of tasks are required in order to implement the method: (a) generating multiple complete datasets in which missing values have been imputed by simulating from an appropriate probability distribution and (b) analyzing the multiple imputed datasets and combining complete data inferences from them to form an overall inference for parameters of interest. An increasing number of software tools are available for task (a), although this is difficult to automate, because the method of imputation should depend on the context and available covariate data. When the quantity of missing data is not great, the sensitivity of results to the imputation model may be relatively low. In this context, software tools that enable task (b) to be performed with similar ease to the analysis of a single dataset should facilitate the wider use of multiple imputation. Such tools need not only to implement techniques for inference from multiple imputed datasets but also to allow standard manipulations such as transformation and recoding of variables. In this article, we describe a set of Stata commands that we have developed for manipulating and analyzing multiple datasets.
Multivariate Probit Regression using Simulated Maximum Likelihood
Authors: Cappellari Lorenzo , Jenkins Stephen P.
Published: November 2018

We discuss the application of the GHK simulation method for maximum likelihood estimation of the multivariate probit regression model and describe and illustrate a Stata program mvprobit for this purpose.
Lean Mainstream Schemes for Stata 8 Graphics
Authors: Juul Svend
Published: November 2018

The new Stata 8 graphics are powerful and flexible. Now, a few months after the first release, the graphics still have some shortcomings—both in design and in the manual documenting the program—but progress is being made. The graph layout used throughout the Graphics Reference Manual has led some users to underestimate the potential of the program. This paper presents two schemes for a lean layout, conforming to the mainstream in scientific publishing.
Speaking Stata: Problems with Tables, Part I
Authors: Cox Nicholas J.
Published: November 2018

Tables in some form or another are part and parcel of data management and analysis. The main general-purpose tabulation commands, tabulate, table, and tabstat, are reviewed and compared. When these do not provide a tabulation solution, one key strategy is to prepare the material for tabulation as a set of variables, after which the table itself can be presented with tabdisp or list. This is the first of two papers on this topic.
From the Help Desk: Polynomial Distributed Lag Models
Authors: McDowell Allen
Published: November 2018

Polynomial distributed lag models (PDLs) are finite-order distributed lag models with the impulse–response function constrained to lie on a polynomial of known degree. You can estimate the parameters of a PDL directly via constrained ordinary least squares, or you can derive a reduced form of the model via a linear transformation of the structural model, estimate the reduced-form parameters, and recover estimates of the structural parameters via an inverse linear transformation of the reduced-form parameter estimates. This article demonstrates both methods using Stata.
Speaking Stata: Graphing Categorical and Compositional Data
Authors: Cox Nicholas J.
Published: November 2018

A variety of graphs have been devised for categorical and compositional data, ranging from widely familiar to more unusual displays. Both official Stata commands and user-written programs are available. After a stacking trick for binary responses is explained, bar charts and related displays for cross-tabulations are discussed in detail. Tips and tricks are introduced for plotting cumulative distributions of graded (ordinal) data. Triangular plots are explained for three-way compositions, such as three proportions or percentages.
Review of a Handbook of Statistical Analyses Using Stata by Rabe-Hesketh and Everitt
Authors: Winter Nicholas
Published: November 2018

The new edition of the book by Rabe-Hesketh and Everitt (2004) is reviewed.
Generalized Power Calculations for Generalized Linear Models and more
Authors: Newson Roger
Published: November 2018

The powercal command can compute any one of the five quantities involved in power calculations from the other four. These quantities are power, significance level, detectable difference, sample number, and the standard deviation (SD) of the influence function, which is equal to the standard error multiplied by the square root of the sample number. powercal can take arbitrary expressions (involving constants, scalars, or variables) as input and calculate the output as a new variable. The user can therefore plot input variables against output variables, and this often communicates the tradeoffs involved better than a point calculation as output by the sampsi command. General formulas are given for calculating the SD of the influence function when the detectable difference is a linear combination of link functions of subpopulation means for an outcome variable distributed according to a generalized linear model (GLM). This general case includes a very broad range of special cases, where the parameters to be estimated are differences between subpopulation proportions, arithmetic means and algebraic means, or ratios between subpopulation proportions, arithmetic means, geometric means, and odds. However, powercal is not limited to GLMs and can even be used with rank methods.
Confidence Intervals for the Variance Component of Random-effects Linear Models
Authors: Bottai Matteo , Orsini Nicola
Published: November 2018

We present the postestimation command xtvc to provide confidence intervals for the variance components of random-effects linear regression models. This command must be used after xtreg with option mle. Confidence intervals are based on the inversion of a score-based test (Bottai 2003).
From the Help Desk: Seemingly Unrelated Regression with Unbalanced Equations
Authors: McDowell Allen
Published: November 2018

This article demonstrates how to estimate the parameters of a system of seemingly unrelated regressions when the equations are unbalanced, i.e., when the equations have an unequal number of observations. With estimators that require the data to be in wide format, such as Stata's sureg, the equations must be balanced. Any additional observations that are available for some equations, but not for all, are discarded, potentially resulting in a loss of efficiency. Reshaping and scaling the data allows us to use Stata's xtgee command to fit the model and obtain estimates utilizing all the available data. The resulting estimator is potentially more efficient when the equations are unbalanced.
Stata: The Language of Choice for Time-Series Analysis?
Authors: Baum Christopher F.
Published: November 2018

This paper discusses the use of Stata for the analysis of time series and panel data. The evolution of time-series capabilities in Stata is reviewed. Facilities for data management, graphics, and econometric analysis from both official Stata and the user community are discussed. A new routine to provide moving-window regression estimates—rollreg—is described, and its use illustrated.
Multiple Imputation of Missing Values: Update
Authors: Royston Patrick
Published: November 2018

This article describes a substantial update to mvis, which brings it more closely in line with the feature set of S. van Buuren and C. G. M. Oudshoorn's implementation of the MICE system in R and S-PLUS (for details, see http://www.multiple-imputation.com ). To make a clear distinction from mvis, the principal program of the new Stata release is called ice. I will give details of how to use the new features and a practical illustrative example using real data. All the facilities of mvis are retained by ice. Some improvements to micombine for computing estimates from multiply imputed datasets are also described.
Mata Matters: Translating Fortran*
Authors: Gould William
Published: November 2018

Mata is Stata's matrix language. In the Mata matters column, we show how Mata can be used interactively to solve problems and as a programming language to add new features to Stata. In this column, we demonstrate how Fortran programs can be translated and incorporated into Stata.
Extended Generalized Linear Models: Simultaneous Estimation of Flexible Link and Variance Functions
Authors: Basu Anirban
Published: November 2018

I describe a command that simultaneously solves the extended estimating equations estimator for parameters in the link and variance functions along with those of the linear predictor in a generalized linear model. The method addresses difficulties in choosing the correct link and variance functions in these models. It decouples the scale of estimation for the mean model, determined by the link function, from the scale of interest for the scientifically relevant effects. It also estimates a flexible variance structure from the data, leading to efficient estimation.
Review of Data Analysis Using Stata by Kohler and Kreuter
Authors: Schumm L. Philip
Published: November 2018

The new book by Kohler and Kreuter (2005) is reviewed.
Estimating Variance Components in Stata
Authors: Marchenko Yulia V.
Published: November 2018

This article gives a brief overview of the popular methods for estimating variance components in linear models and describes several ways to obtain such estimates in Stata for various experimental designs. The article's emphasis is on using xtmixed to estimate variance components. Prior to Stata 9, loneway could be used to estimate variance components for one-way random-effects models. For other experimental designs, variance components could be computed manually using saved results after anova. The latter approach is viable but requires tedious computations for complicated experimental designs. Instead, as of Stata 9, variance components are easily obtained by using xtmixed.
Generalized Least Squares for Trend Estimation of Summarized Dose–response Data
Authors: Orsini Nicola , Bellocco Rino , Greenland Sander
Published: November 2018

This paper presents a command, glst, for trend estimation across different exposure levels for either single or multiple summarized case–control, incidence-rate, and cumulative incidence data. This approach is based on constructing an approximate covariance estimate for the log relative risks and estimating a corrected linear trend using generalized least squares. For trend analysis of multiple studies, glst can estimate fixed- and random-effects metaregression models.
Goodness-of-fit Test for a Logistic Regression Model Fitted using Survey Sample Data
Authors: Archer Kellie J. , Lemeshow Stanley
Published: November 2018

After a logistic regression model has been fitted, a global test of goodness of fit of the resulting model should be performed. A test that is commonly used to assess model fit is the Hosmer–Lemeshow test, which is available in Stata and most other statistical software programs. However, it is often of interest to fit a logistic regression model to sample survey data, such as data from the National Health Interview Survey or the National Health and Nutrition Examination Survey. Unfortunately, for such situations no goodness-of-fit testing procedures have been developed or implemented in available software. To address this problem, a Stata ado-command, svylogitgof, for estimating the F-adjusted mean residual test after svy: logit or svy: logistic estimation has been developed, and this paper describes its implementation.
Generating Halton Sequences using Mata
Authors: Drukker David M. , Gates Richard
Published: November 2018

This paper discusses the advantages of Halton sequences over pseudorandom uniform numbers when using simulation to approximate integrals numerically. We describe two types of sequences and give Mata examples. Finally, we document the Mata function halton(), currently in release 9.1 of Stata, which computes both a Halton sequence and its Hammersley variant. Options to use these point sets are available in the Stata 9 program asmprobit, a multinomial-probit estimator, and in the Stata 9.1 Mata function ghk(), the Geweke–Hajivassiliou–Keane multivariate-normal simulator.
Graphical Representation of Interactions
Authors: Barthel Friederike Maria-Sophie , Royston Patrick
Published: November 2018

We provide a program to illustrate interactions between treatment and covariates or between two covariates by using forest plots under either the Cox proportional hazards or the logistic regression model. The program is flexible in both the possibility of illustrating more than one interaction at a time and variable specifications of scale.
Review of a Gentle Introduction to Stata by Acock
Authors: Mulcahy Michael
Published: November 2018

This article reviews A Gentle Introduction to Stata by Acock.
Practical Fixed-Effects Estimation Methods for the Three-Way Error-Components Model
Authors: Andrews Martyn , Schank Thorsten , Upward Richard
Published: November 2018

Methods for fixed-effects estimation of the three-way error-components model are not yet standard. Where possible, we make the fixed-effects methods originally developed by Abowd, Kramarz, and Margolis ( Econometrica 67: 251–333) for linked worker–firm data more accessible. We also show how these methods can be implemented in Stata. There is a caveat, however. If the researcher wants to recover estimates of the error components themselves, and the number of units at the higher level of aggregation is large, memory or matrix constraints may make using Stata to estimate the components themselves infeasible.
Review of An Introduction to Stata for Health Researchers by Juul
Authors: Carlin John
Published: November 2018

This article reviews An Introduction to Stata for Health Researchers by Svend Juul.
Review of a Stata Companion to Political Analysis by Pollock
Authors: Allard Scott W.
Published: November 2018

This article reviews A Stata Companion to Political Analysis by Philip H. Pollock III.
Rasch Analysis: Estimation and Tests with Raschtest
Authors: Hardouin Jean-Benoit
Published: November 2018

Analyzing latent variables is becoming more and more important in several fields, such as clinical research, psychology, educational sciences, ecology, and epidemiology. The item response theory allows analyzing latent variables measured by questionnaires of items with binary or ordinal responses. The Rasch model is the best known model of this theory for binary responses. Although one can estimate the parameters of the Rasch model with the clogit or xtlogit command (or with the unofficial gllamm command), these commands require special data preparation. The proposed raschtest command easily allows estimating the parameters of the Rasch model and fitting the resulting model.
Sensitivity Analysis for Average Treatment Effects
Authors: Becker Sascha O. , Caliendo Marco
Published: November 2018

Based on the conditional independence or unconfoundedness assumption, matching has become a popular approach to estimate average treatment effects. Checking the sensitivity of the estimated results with respect to deviations from this identifying assumption has become an increasingly important topic in the applied evaluation literature. If there are unobserved variables that affect assignment into treatment and the outcome variable simultaneously, a hidden bias might arise to which matching estimators are not robust. We address this problem with the bounding approach proposed by Rosenbaum (Observational Studies, 2nd ed., New York: Springer), where mhbounds lets the researcher determine how strongly an unmeasured variable must influence the selection process to undermine the implications of the matching analysis.
Mata Matters: Subscripting
Authors: Gould William
Published: November 2018

Mata is Stata's matrix language. In the Mata Matters column, we show how Mata can be used interactively to solve problems and as a programming language to add new features to Stata. Subscripting is the subject of this column. Stata has three subscripting modes, and two of them are about more than accessing an element of a vector or matrix. The advanced forms of subscripting can, by themselves, be the solution to some problems.