bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementing Intersection Bounds in Stata
Authors: Chernozhukov Victor , Kim Wooyoung , Lee Sokbae , Rosen Adam M.
Published: November 2018

We present the clrbound, clr2bound, clr3bound, and clrtest commands for estimation and inference on intersection bounds as developed by Chernozhukov, Lee, and Rosen (2013, Econometrica 81: 667–737). The intersection bounds framework encompasses situations where a population parameter of interest is partially identified by a collection of consistently estimable upper and lower bounds. The identified set for the parameter is the intersection of regions defined by this collection of bounds. More generally, the methodology can be applied to settings where an estimable function of a vector-valued parameter is bounded from above and below, as is the case when the identified set is characterized by conditional moment inequalities.

The commands clrbound, clr2bound, and clr3bound provide bound estimates that can be used directly for estimation or to construct asymptotically valid confidence sets. clrtest performs an intersection bound test of the hypothesis that a collection of lower intersection bounds is no greater than zero. The command clrbound provides bound estimates for one-sided lower or upper intersection bounds on a parameter, while clr2bound and clr3bound provide two-sided bound estimates using both lower and upper intersection bounds. clr2bound uses Bonferroni's inequality to construct two-sided bounds that can be used to perform asymptotically valid inference on the identified set or the parameter of interest, whereas clr3bound provides a generally tighter confidence interval for the parameter by inverting the hypothesis test performed by clrtest. More broadly, inversion of this test can also be used to construct confidence sets based on conditional moment inequalities as described in Chernozhukov, Lee, and Rosen (2013). The commands include parametric, series, and local linear estimation procedures.
Frailty Models and Frailty-Mixture Models for Recurrent Event Times
Authors: Xu Ying , Cheung Yin Bun
Published: November 2018

The analysis of recurrent event times faces three challenges: between-subject heterogeneity (frailty), within-subject event dependence, and the possibility of a cured fraction. Frailty can be handled by including a latent random-effects term in a Cox-type model. Event dependence may be considered as contributing to the intervention effect, or it may be considered as a source of nuisance, depending on the analysts’ specific research questions. If it is seen as a nuisance, the analysis can stratify the recurrent event times according to event order. If it is seen as contributing to the intervention effect, stratification should not be used. Models with and without stratification for event order estimate two types of treatment effects. They are analogous to per-protocol analysis and intention-to-treat analysis, respectively. In the context of chronic disease treatment, we want to estimate whether there is a cured fraction; for infectious disease prevention, this is called a nonsusceptible fraction. In infectious disease prevention, we want to understand whether an intervention protects each of its recipients to some extent (“leaky” model) or whether it totally protects some recipients but offers no protection to the rest (“all-or-none” model). The truth may be a mixture of the two modes of protection. We describe a class of regression models that can handle all three issues in the analysis of recurrent event times. The model parameters are estimated by the expectation-maximization algorithm, and their variances are estimated by Louis's formula. We provide a new command, strmcure, for implementing these models.
Newspell: Easy Management of Complex Spell Data
Authors: Kröger Hannes
Published: November 2018

Biographical data gathered in surveys are often stored in spell format, allowing for overlaps between spell states. On the one hand, these kind of data provide useful information for researchers. On the other hand, the data structure is often complex and not easy to handle. The newspell program offers a solution to the problem of spell-data management with three important features. First, it can rank spells and cut off overlaps according to the rank order. Second, newspell can combine overlapping parts of spells into new categories of spells, generating entirely new states. Third, it can detect gaps in the spell data that are not yet coded. It also includes subcommands for the management of complex spell data. Spell states can be merged and filled in with information from adjacent spells, and the data can be transformed to long or wide format. The command can be used to clean data, to combine two spell-data sources that have information on different kinds of states, or to deal with spell data that are complex by survey design. newspell is useful for users who are not familiar with complex spell data and have little experience in Stata programming or data management. For experienced users, newspell saves a lot of time and coding work.
Nonparametric Pairwise Multiple Comparisons in Independent Groups using Dunn's Test
Authors: Dinno Alexis
Published: November 2018

Dunn's test is the appropriate nonparametric pairwise multiple-comparison procedure when a Kruskal–Wallis test is rejected, and it is now implemented for Stata in the dunntest command. dunntest produces multiple comparisons following a Kruskal–Wallis k-way test by using Stata's built-in kwallis command. It includes options to control the familywise error rate by using Dunn's proposed Bonferroni adjustment, the Šidák adjustment, the Holm stepwise adjustment, or the Holm–Šidák stepwise adjustment. There is also an option to control the false discovery rate using the Benjamini–Hochberg stepwise adjustment.
Prediction in Linear Index Models with Endogenous Regressors
Authors: Skeels Christopher L. , Taylor Larry W.
Published: November 2018

In this article, we examine prediction in the context of linear index models when one or more of the regressors are endogenous. To facilitate both within-sample and out-of-sample predictions, Stata offers the postestimation command predict (see [R] predict). We believe that the usefulness of the predictions provided by this command is limited, especially if one is interested in out-of-sample predictions. We demonstrate our point using a probit model with continuous endogenous regressors, although it clearly generalizes readily to other linear index models. We subsequently provide a program that offers one possible implementation of a new command, ivpredict, that can be used to address this shortcoming of predict, and we then illustrate its use with an empirical example.
Feasible Fitting of Linear Models with N Fixed Effects
Authors: Rios-Avila Fernando
Published: November 2018

In this article, I describe an alternative approach for fitting linear models with multiple high-order fixed effects. The strategy relies on transforming the data before fitting the model. While the approach is computationally intensive, the hardware requirements for the fitting are minimal, allowing for estimation in models with multiple high-order fixed effects for large datasets. I illustrate implementing this approach using the U.S. Census Bureau Current Population Survey data with four fixed effects. I also present a new Stata command, regxfe, for implementing this strategy.
Network Meta-analysis
Authors: White Ian R.
Published: November 2018

Network meta-analysis is a popular way to combine results from several studies (usually randomized trials) comparing several treatments or interventions. It has usually been performed in a Bayesian setting, but recently it has become possible in a frequentist setting using multivariate meta-analysis and meta-regression, implemented in Stata with mvmeta. I describe a suite of Stata programs for network meta-analysis that perform the necessary data manipulation, fit consistency and inconsistency models using mvmeta, and produce various graphics.
Bootstrap-based Bias Correction and Inference for Dynamic Panels with Fixed Effects
Authors: De Vos Ignace , Everaert Gerdie , Ruyssen Ilse
Published: November 2018

In this article, we describe a new command, xtbcfe, that performs the iterative bootstrap-based bias correction for the fixed-effects estimator in dynamic panels proposed by Everaert and Pozzi (2007, Journal of Economic Dynamics and Control 31: 1160–1184). We first simplify the core of their algorithm by using the invariance principle and subsequently extend it to allow for unbalanced and higher-order dynamic panels. We implement various bootstrap error resampling schemes to account for general heteroskedasticity and contemporaneous cross-sectional dependence. Inference can be performed using a bootstrapped variance–covariance matrix or percentile intervals. Monte Carlo simulations show that the simplification of the original algorithm results in a further bias reduction for very small T. The Monte Carlo results also support the bootstrap-based bias correction in higher-order dynamic panels and panels with cross-sectional dependence. We illustrate the command with an empirical example estimating a dynamic labor–demand function.
Review of Michael N. Mitchell's Stata for the Behavioral Sciences
Authors: Ender Philip B.
Published: November 2018

In this article, I review Stata for the Behavioral Sciences by Michael N. Mitchell (2015 [Stata Press]).
Assessing Inequality Using Percentile Shares
Authors: Jann Ben
Published: November 2018

At least since Thomas Piketty's best-selling Capital in the Twenty-First Century (2014, Cambridge, MA: The Belknap Press), percentile shares have become a popular approach for analyzing distributional inequalities. In their work on the development of top incomes, Piketty and collaborators typically report top-percentage shares, using varying percentages as thresholds (top 10%, top 1%, top 0.1%, etc.). However, analysis of percentile shares at other positions in the distribution may also be of interest. In this article, I present a new command, pshare, that estimates percentile shares from individual-level data and displays the results using histograms or stacked bar charts.
Inference in Regression Discontinuity Designs under Local Randomization
Authors: Cattaneo Matias D. , Titiunik Rocío , Vazquez-Bare Gonzalo
Published: November 2018

We introduce the rdlocrand package, which contains four commands to conduct finite-sample inference in regression discontinuity (RD) designs under a local randomization assumption, following the framework and methods proposed in Cattaneo, Frandsen, and Titiunik (2015, Journal of Causal Inference 3: 1–24) and Cattaneo, Titiunik, and Vazquez-Bare (2016, Working Paper, University of Michigan, http://www-personal.umich.edu/∼titiunik/papers/

CattaneoTitiunikVazquezBare2015_wp.pdf). Assuming a known assignment mechanism for units close to the RD cutoff, these functions implement a variety of procedures based on randomization inference techniques. First, the rdrandinf command uses randomization methods to conduct point estimation, hypothesis testing, and confidence interval estimation under different assumptions. Second, the rdwinselect command uses finite-sample methods to select a window near the cutoff where the assumption of randomized treatment assignment is most plausible. Third, the rdsensitivity command uses randomization techniques to conduct a sequence of hypothesis tests for different windows around the RD cutoff, which can be used to assess the sensitivity of the methods and to construct confidence intervals by inversion. Finally, the rdrbounds command implements Rosenbaum (2002, Observational Studies [Springer]) sensitivity bounds for the context of RD designs under local randomization. Companion R functions with the same syntax and capabilities are also provided.
The Keane and Runkle Estimator for Panel-data Models with Serial Correlation and Instruments that are not Strictly Exogenous
Authors: Keane Michael , Neal Timothy
Published: November 2018

In this article, we introduce the new command xtkr, which implements the Keane and Runkle (1992a, Journal of Business and Economic Statistics 10: 1–9) approach for fitting linear panel-data models when the available instruments are predetermined but not strictly exogenous. This is a common case that includes dynamic panel-data models as a leading example. Monte Carlo simulations show that, in certain situations, this approach offers an improvement over the popular difference generalized method of moments and system generalized method of moments estimators in terms of bias and root mean squared error. An empirical application to cigarette demand also demonstrates its usefulness for applied researchers.
Multiple Imputation for Categorical Time Series
Authors: Halpin Brendan
Published: November 2018

The mict package provides a method for multiple imputation of categorical time-series data (such as life course or employment status histories) that preserves longitudinal consistency, using a monotonic series of imputations. It allows flexible imputation specifications with a model appropriate to the target variable (mlogit, ologit, etc.). Where transitions in individual units’ data are substantially less frequent than one per period and where missingness tends to be consecutive (as is typical of life course data), mict produces imputations with better longitudinal consistency than mi impute or ice.
Dynsimpie: A Command to Examine Dynamic Compositional Dependent Variables
Authors: Philips Andrew Q. , Rutherford Amanda , Whitten Guy D.
Published: November 2018

In this article, we adapt the modeling strategy proposed by Philips, Rutherford, and Whitten (2016, American Journal of Political Science 60: 268–283) and create a user-friendly Stata command, dynsimpie. This command requires the installation of the clarify package of Tomz, Wittenberg, and King (2003, Journal of Statistical Software 8(1): 1–30) and uses the commands in the clarify package to produce estimates from models of compositional dependent variables over time. Users can also examine how counterfactual shocks play through the system with graphs that are easy to interpret. We illustrate this with a model of voter support for the three dominant political parties in the UK.
The Lag-length Selection and Detrending Methods for HEGY Seasonal Unit-root Tests Using Stata
Authors: Del Barrio Castro Tomás , Bodnar Andrii , Sansó Andreu
Published: November 2018

The article extends the previous Hylleberg, Engle, Granger, and Yoo seasonal unit-root test commands (Baum and Sperling, 2001, https://ideas.repec.org/c/boc/bocode/s416502.html ; Depalo, 2009, Stata Journal 9: 422–438), which allow for the use of both quarterly and monthly data. It is also possible to choose between ordinary least-squares and generalized least-squares detrending (Rodrigues and Taylor, 2007, Journal of Econometrics 141: 548–573) procedures to deal with the deterministic part of the process. The command allows for the use of the sequential method proposed by Hall (1994, Journal of Business and Economic Statistics 12: 461–470) and Ng and Perron (1995, Journal of the American Statistical Association 90: 268–281), the adaptation of the modified Akaike information criteria to the case of seasonal unit-root tests (del Barrio Castro, Osborn, and Taylor, 2016, Econometric Reviews 35: 122–168) as well as the inclusion of Akaike information and Bayesian information criteria to determine the order of augmentation of the serial correlation in the augmented Hylleberg, Engle, Granger, and Yoo regression. Finally, the use of the command is illustrated with an empirical application to the case of monthly passenger airport arrivals to Palma de Mallorca.
Estimating Lorenz and Concentration Curves
Authors: Jann Ben
Published: November 2018

Lorenz and concentration curves are widely used tools in inequality research. In this article, I present a new command, lorenz, that estimates Lorenz and concentration curves from individual-level data and, optionally, displays the results in a graph. The lorenz command supports relative, generalized, absolute, unnormalized, custom-normalized Lorenz, and concentration curves. It also provides tools for computing contrasts between different subpopulations or outcome variables. lorenz fully supports variance estimation for complex samples.
Rethinking Literate Programming in Statistics
Authors: Haghish E. F.
Published: November 2018

Literate programming is becoming increasingly trendy for data analysis because it allows the generation of dynamic-analysis reports for communicating data analysis and eliminates untraceable human errors in analysis reports. Traditionally, literate programming includes separate processes for compiling the code and preparing the documentation. While this workflow might be satisfactory for software documentation, it is not ideal for writing statistical analysis reports. Instead, these processes should run in parallel. In this article, I introduce the weaver package, which examines this idea by creating a new log system in HTML or LATEX that can be used simultaneously with the Stata log system. The new log system provides many features that the Stata log system lacks; for example, it can render mathematical notations, insert figures, create publication-ready dynamic tables, and style text, and it includes a built-in syntax highlighter. The weaver package also produces dynamic PDF documents by converting the HTML log to PDF or by typesetting the LATEX log and thus provides a real-time preview of the document without recompiling the code. I also discuss potential applications of the weaver package.
Markdoc: Literate Programming in Stata
Authors: Haghish E. F.
Published: November 2018

Rigorous documentation of the analysis plan, procedure, and computer codes enhances the comprehensibility and transparency of data analysis. Documentation is particularly critical when the codes and data are meant to be publicly shared and examined by the scientific community to evaluate the analysis or adapt the results. The popular approach for documenting computer codes is known as literate programming, which requires preparing a trilingual script file that includes a programming language for running the data analysis, a human language for documentation, and a markup language for typesetting the document. In this article, I introduce markdoc, a software package for interactive literate programming and generating dynamic-analysis documents in Stata. markdoc recognizes Mark-down, LATEX, and HTML markup languages and can export documents in several formats, such as PDF, Microsoft Office .docx, OpenOffice and LibreOffice .odt, LATEX, HTML, ePub, and Markdown.
Tests for Normality Based on the Quantile-mean Covariance
Authors: Alejo Javier , Bera Anil , Montes-Rojas Gabriel , Galvao Antonio , Xiao Zhijie
Published: November 2018

We present a new command, qctest, to implement tests for normality of a random variable based on the quantile-mean covariance. The test procedures are based on recent results by Bera et al. (2016, Econometric Theory 32: 1216–1252) and are an efficient alternative to existing normality tests in the literature.
Announcement of the Stata Journal Editors’ Prize 2017
Authors: Newton H. Joseph , Cox Nicholas J.
Published: November 2018

The editors of the Stata Journal are pleased to invite nominations for their 2017 prize in accordance with the following rules. Nominations should be sent as private email to editors@stata-journal.com by July 31, 2017.
Commands for Testing Conditional Moment Inequalities and Equalities
Authors: Andrews Donald W. K. , Kim Wooyoung , Shi Xiaoxia
Published: November 2018

In this article, we present two commands (cmi_test and cmi_interval) to implement the testing and inference methods for conditional moment inequality or equality models proposed in Andrews and Shi (2013, Econometrica 81: 609–666). The cmi_test command tests the validity of a finite number of conditional moment equalities or inequalities. This test returns the value of the test statistic, the critical values at significance levels 1%, 5%, and 10%, and the p-value. The cmi_interval command returns the confidence interval for a one-dimensional parameter defined by intersection bounds. We obtain this confidence interval by inverting cmi_test. All procedures implemented are uniformly asymptotically valid under appropriate conditions (specified in Andrews and Shi [2013]).
Fitting the Errors-in-variables Model Using High-order Cumulants and Moments
Authors: Erickson Timothy , Parham Robert , Whited Toni M.
Published: November 2018

In this article, we consider a multiple mismeasured regressor errors-in-variables model. We present xtewreg, a command for using two-step generalized method of moments and minimum distance estimators that exploit overidentifying information contained in high-order cumulants or moments of the data. The command supports cumulant or moment estimation, internal support for the bootstrap with moment condition recentering, an arbitrary number of mismeasured regressors and perfectly measured regressors, and cumulants or moments up to an arbitrary degree. We also demonstrate how to use the estimators in the context of a corporate leverage regression.
Spatial Panel-data Models Using Stata
Authors: Belotti Federico , Hughes Gordon , Mortari Andrea Piano
Published: November 2018

xsmle is a new user-written command for spatial analysis. We consider the quasi–maximum likelihood estimation of a wide set of both fixed- and random-effects spatial models for balanced panel data. xsmle allows users to handle unbalanced panels using its full compatibility with the mi suite of commands, use spatial weight matrices in the form of both Stata matrices and spmat objects, compute direct, indirect, and total marginal effects and related standard errors for linear (in variables) specifications, and exploit a wide range of postestimation features, including the panel-data case predictors of Kelejian and Prucha (2007, Regional Science and Urban Economics 37: 363–374). Moreover, xsmle allows the use of margins to compute total marginal effects in the presence of nonlinear specifications obtained using factor variables. In this article, we describe the command and all of its functionalities using simulated and real data.
Analyzing Repeated Measurements while Accounting for Derivative Tracking, Varying Within-subject Variance, and Autocorrelation: The Xtmixediou Command
Authors: Hughes Rachael A. , Kenward Michael G. , Sterne Jonathan A. C. , Tilling Kate
Published: November 2018

Linear mixed-effects models are commonly used to model trajectories of repeated measures of biomarkers of disease. Taylor, Cumberland, and Sy (1994, Journal of the American Statistical Association 89: 727–736) proposed a linear mixed-effects model with an added integrated Ornstein–Uhlenbeck (IOU) process (linear mixed-effects IOU model). This allows for autocorrelation, changing within-subject variance, and the incorporation of derivative tracking (that is, how much a subject tends to maintain the same trajectory for extended periods of time). They argued that the covariance structure induced by the stochastic process in this model was interpretable and more biologically plausible than the standard linear mixed-effects model. However, their model is rarely used, partly because of the lack of available software. In this article, we present the new command xtmixediou, which fits the linear mixed-effects IOU model and its special case, the linear mixed-effects Brownian motion model. The model is fit to balanced and unbalanced data using restricted maximum-likelihood estimation, where the optimization algorithm is the Newton–Raphson, Fisher scoring, or average information algorithm, or any combination of these. To aid convergence, xtmixediou allows the user to change the method for deriving the starting values for optimization, the optimization algorithm, and the parameterization of the IOU process. We also provide a predict command to generate predictions under the model. We illustrate xtmixediou and predict with a simulated example of repeated biomarker measurements from HIV-positive patients.
New Graphic Schemes for Stata: Plotplain and Plottig
Authors: Bischof Daniel
Published: November 2018

While Stata's computational capabilities have intensively increased over the last decade, the quality of its default graphic schemes is still a matter of debate among users. Some of the arguments speaking against Stata's default graphic design are subject to individual taste but others are not, for example, horizontal labeling, unnecessary background tinting, missing gridlines, and oversized markers. In this article, I present two new graphic schemes, plotplain and plottig, that attempt to address these concerns. These schemes provide users a set of 21 colors, of which 7 colors are distinguishable for people suffering from color blindness. I also give an introduction on how users can program their own graphic schemes.
Speaking Stata: Tables as Lists: The Groups Command
Authors: Cox Nicholas J.
Published: November 2018

Tables can often be conveniently considered or produced as lists. The list command is therefore a vehicle for obtaining such tables. The groups command for tabulation is built around a call to list. It has no particular limits on the number of identifiers (row, column, or other variables defining cells). Among other features, it offers support for various kinds of frequencies, percents, and cumulations thereof; for various subsetting and ordering by frequencies, percents, and so on; for reordering of columns from the default display; and for saving tabulated data to new datasets.
Stata Tip 128: Marginal Effects in Log-transformed Models: A Trade Application
Authors: Uberti Luca J.
Published: November 2018

Since the introduction of the margins command in Stata 11, the empirical literature has increasingly used marginal effects, predictive margins, and adjusted predictions in postestimation analysis. Marginal effects are particularly useful for the interpretation of parameter estimates after logit, probit, poisson, and other nonlinear regression models. If the covariate of interest is in logs, however, obtaining meaningful results from margins, dydx() is not straightforward. In this article, I first illustrate these difficulties in the context of estimation with poisson. I then suggest that a researcher should always compute the derivative of interest and code it manually with margins‘s expression() option. Lastly, I illustrate these problems using the gravity equation from the trade literature.
A Command for Fitting Mixture Regression Models for Bounded Dependent Variables Using the Beta Distribution
Authors: Gray Laura A. , Alava Mónica Hernández
Published: November 2018

In this article, we describe the betamix command, which fits mixture regression models for dependent variables bounded in an interval. The model is a generalization of the truncated inflated beta regression model introduced in Pereira, Botter, and Sandoval (2012, Communications in Statistics—Theory and Methods 41: 907–919) and the mixture beta regression model in Verkuilen and Smithson (2012, Journal of Educational and Behavioral Statistics 37: 82–113) for variables with truncated supports at either the top or the bottom of the distribution. betamix accepts dependent variables defined in any range that are then transformed to the interval (0, 1) before estimation.
Ldagibbs: A Command for Topic Modeling in Stata Using Latent Dirichlet Allocation
Authors: Schwarz Carlo
Published: November 2018

In this article, I introduce the ldagibbs command, which implements latent Dirichlet allocation in Stata. Latent Dirichlet allocation is the most popular machine-learning topic model. Topic models automatically cluster text documents into a user-chosen number of topics. Latent Dirichlet allocation represents each document as a probability distribution over topics and represents each topic as a probability distribution over words. Therefore, latent Dirichlet allocation provides a way to analyze the content of large unclassified text data and an alternative to predefined document classifications.
Exploring Marginal Treatment Effects: Flexible Estimation Using Stata
Authors: Andresen Martin Eckhoff
Published: November 2018

In settings that exhibit selection on both levels and gains, marginal treatment effects (MTE) allow us to go beyond local average treatment effects and estimate the whole distribution of effects. In this article, I survey the theory behind MTE and introduce the package mtefe, which uses several estimation methods to fit MTE models. This package provides important improvements and flexibility over existing packages such as margte (Brave and Walstrum, 2014, Stata Journal 14: 191–217) and calculates various treatment-effect parameters based on the results. I illustrate the use of the package with examples.
Baselinetable: A Command for Creating one- and Two-way Tables of Summary Statistics
Authors: Donath Susan
Published: November 2018

In this article, I describe baselinetable, a community-contributed command for creating one- and two-way tables of summary statistics for a list of numeric variables. Unlike other Stata tabulation commands such as tabulate, table, or tabstat, the variables forming the table rows can be a mixture of continuous (summarized by mean, standard deviation, etc.) and categorical (summarized by percentages and frequencies). baselinetable provides considerable flexibility in the way the results are displayed. In particular, the summary statistics and their presentation can be different for each row variable. Additional features include several options for displaying counts of missing and nonmissing data points and the ability to restrict results to subgroups of the data for individual row variables. The contents of the table can be saved as a data file or text file, or they can be exported to Excel. The motivation for baselinetable is the descriptive table commonly seen in health research publications in which the baseline characteristics of two or more groups are compared. This descriptive table usually has only one column for each group, generally with at least two summary statistics in each column (for example, mean and standard deviation for continuous variables or frequency and percentage for categorical variables). The baselinetable command supports reproducible research by enabling researchers to easily create tables whose contents can be used unchanged in publications.
Simulating the Central Limit Theorem
Authors: Taylor Marshall A.
Published: November 2018

Understanding the central limit theorem is crucial for comprehending parametric inferential statistics. Despite this, undergraduate and graduate students alike often struggle with grasping how the theorem works and why researchers rely on its properties to draw inferences from a single unbiased random sample. In this article, I outline a new command, sdist, that can be used to simulate the central limit theorem by generating a matrix of randomly generated normal or nonnormal variables and comparing the true sampling distribution standard deviation with the standard error from the first randomly generated sample. The user also has the option of plotting the empirical sampling distribution of sample means, the first random variable distribution, and a stacked visualization of the two distributions.
Cvcrand and Cptest: Commands for Efficient Design and Analysis of Cluster Randomized Trials Using Constrained Randomization and Permutation Tests
Authors: Gallis John A. , Li Fan , Yu Hengshi , Turner Elizabeth L.
Published: November 2018

Cluster randomized trials (CRTs), where clusters (for example, schools or clinics) are randomized to comparison arms but measurements are taken on individuals, are commonly used to evaluate interventions in public health, education, and the social sciences. Because CRTs typically involve a small number of clusters (for example, fewer than 20), simple randomization frequently leads to baseline imbalance of cluster characteristics across study arms, threatening the internal validity of the trial. In CRTs with a small number of clusters, classic approaches to balancing baseline characteristics—such as matching and stratification—have several drawbacks, especially when the number of baseline characteristics the researcher desires to balance is large (Ivers et al., 2012, Trials 13: 120). An alternative design approach is covariate-constrained randomization, whereby a randomization scheme is randomly selected from a subset of all possible randomization schemes based on the value of a balancing criterion (Raab and Butcher, 2001, Statistics in Medicine 20: 351–365). Subsequently, a clustered permutation test can be used in the analysis, which provides increased power under constrained randomization compared with simple randomization (Li et al., 2016, Statistics in Medicine 35: 1565–1579). In this article, we describe covariate-constrained randomization and the permutation test for the design and analysis of CRTs and provide an example to demonstrate the use of our new commands cvcrand and cptest to implement constrained randomization and the permutation test.
Content Analysis: Frequency Distribution of Words
Authors: Dicle Mehmet F. , Dicle Betul
Published: November 2018

Many academic fields use content analysis. At the core of most common content analysis lies frequency distribution of individual words. Websites and documents are mined for usage and frequency of certain words. In this article, we introduce a community-contributed command, wordfreq, to process content (online and local) and to prepare a frequency distribution of individual words. Additionally, another community-contributed command, wordcloud, is introduced to draw a simple word cloud graph for visual analysis of the frequent usage of specific words.
Event Study Estimations Using Stata: The Estudy Command
Authors: Pacicco Fausto , Vena Luigi , Venegoni Andrea
Published: November 2018

In this article, we introduce the community-contributed command estudy and illustrate how it can be used to perform an event study customizing the statistical framework, from the estimates of abnormal returns to the tests for their statistical significance. Our command significantly improves the existing commands in terms of both completeness and user comprehension.
Ethanol-induced enhancement of inhibitory synaptic transmission in the rat spinal substantia gelatinosa
Authors: Yamada Akihiro , Koga Kohei , Kume Kazuhiko , Ohsawa Masahiro , Furue Hidemasa
Published: November 2018

Recent studies have shown that ethanol produces a widespread modulation of neuronal activity in the central nervous system. It is not fully understood, however, how ethanol changes nociceptive transmission. We investigated acute effects of ethanol on synaptic transmission in the substantia gelatinosa (lamina II of the spinal dorsal horn) and mechanical responses in the spinal dorsal horn. In substantia gelatinosa neurons, bath application of ethanol at low concentration (10 mM) did not change the frequency and amplitude of spontaneous inhibitory postsynaptic currents. At medium to high concentrations (20–100 mM), however, ethanol elicited a barrage of large amplitude spontaneous inhibitory postsynaptic currents. In the presence of tetrodotoxin, such enhancement of spontaneous inhibitory postsynaptic currents was not detected. In addition, ethanol (20–100 mM) increased the frequency of spontaneous discharge of vesicular GABA transporter-Venus-labeled neurons and suppressed the mechanical nociceptive response in wide-dynamic range neurons in the spinal dorsal horn. The present results suggest that ethanol may reduce nociceptive information transfer in the spinal dorsal horn by enhancement of inhibitory GABAergic and glycinergic synaptic transmission.
The effects of colour complexity and similarity on multiple object tracking performance
Authors: Wang Chundi , Hu Luming , Talhelm Thomas , Zhang Xuemin
Published: November 2018

Surface features can be used during multiple object tracking (MOT). Previous studies suggested that surface features might be stored in visual working memory to assist object tracking, and attentive tracking and visual working memory share common attentional resources. However, it is still unknown whether features of both the target and distractor sets will be stored, or features of the target and distractor sets are processed differently. Moreover, how feature distinctiveness and similarity between the target and distractor sets affect tracking and allocation of attentional resources are still not clear. First, we manipulated the colour complexity of the target set (CT) and the colour complexity of the distractor set (CD), respectively, in two experiments, where colours of the target and distractor sets were always distinct, to test their effects on tracking performance. If features of the target and distractor sets are stored, manipulating feature complexity of the target and distractor sets would significantly affect tracking performance. Second, this study tested whether tracking performance was affected by different levels of distinctiveness between the target and distractor sets (DTD) and explored how distinctiveness affected tracking and allocation of attentional resources. Results showed that DTD and CT significantly affect tracking performance and allocation of attentional resources, but not CD. These results indicated that when targets and distractors have distinct features, only the surface features of the targets are maintained in visual working memory. And when targets have the same colour with the distractors, they are more difficult and consume more attentional resources to track.
Reliability of cable insulation under reaction- and diffusion-controlled thermal degradation
Authors: Chang Yuan-Shang , Mosleh Ali
Published: November 2018

Cables transmit signals and power in nuclear power plants. The primary material for the cable insulation is cross-linked polyethylene, which inevitably degrades due to thermal stress. The degradation can become a safety issue, since the brittleness of degraded cross-linked polyethylene may render the exposure of the metal core in a cable. Elongation at break is a widely accepted measurement, evaluating the degree of the brittleness of the insulation. Reaction- and diffusion-controlled kinetics are proposed in this article to quantitatively predict the decrease of the elongation at break as a function of time and temperature. The proposed approaches are based on dichotomy model and Fick’s Law to respectively define the degree of reaction- and diffusion-controlled degradation. Probabilistic techniques are developed by Bayesian parameter estimation to determine the reliability of the cable insulation. These approaches are validated by experimental data.
A Comparison of Various Cervical Muscle Strength Testing Methods Using a Handheld Dynamometer
Authors: Krause David A. , Hansen Kelsey A. , Hastreiter Matthew J. , Kuhn Taylor N. , Peichel Molly L. , Hollman John H.
Published: November 2018

Background:

Cervical muscle strength, proposed as a modifiable risk factor in concussions, can be assessed using various methods. The purpose of this study was to compare the reliability and force outputs of 3 methods that use handheld dynamometry (HHD) for assessing cervical muscle strength.

Hypothesis:

All 3 testing methods are reliable, and force outputs are significantly different between methods.

Study Design:

Repeated-measures reliability.

Level of Evidence:

Level 5.

Methods:

The study used a convenience sample of 30 participants. HHD “make tests” for cervical extension, flexion, and right and left side bending were performed using lying push tests, sitting push tests, and sitting pull tests. A sole examiner performed all tests. Two testing sessions were conducted 1 week apart. Analysis included intraclass correlation coefficients (ICCs), repeated-measures analyses of variance (α = 0.05) with post hoc Bonferroni tests, and minimal detectable change (MDC) calculations.

Results:

All testing methods were reliable; the lying push test had the greatest point estimate values (ICC, 0.89-0.95). Significant differences in force were found between the 3 testing methods. The MDC was most sensitive for the lying push method.

Conclusion:

Of the 3 cervical muscle testing methods investigated, the lying position with a push test had the largest ICC according to the point estimate and the most sensitive MDC. Force values between the 3 methods were significantly different, which suggests that consistent testing methods should be used.

Clinical Relevance:

Results from this study support the clinical use of an HHD “make test” in a lying position for assessing cervical muscle strength. The test is reliable and more sensitive to change compared with tests in a seated position.
Clozapine, HIV and neutropenia: a case report
Authors: Whiskey Eromona , O’Flynn David , Taylor David
Published: November 2018

There is paucity of information on the use of clozapine in patients with HIV. Ethnicity, co-prescribed medications and possible drug-drug interactions are important considerations in evaluating risk of blood dyscrasias during clozapine treatment. Individuals with HIV should not be denied access to the most effective antipsychotic, but a multidisciplinary approach is essential for optimal outcome in such complex patients.
Nurses’ experiences of measuring nursing intensity in home healthcare: A qualitative study
Authors: Flo Jill , Landmark Bjørg , Tønnessen Siri , Fagerström Lisbeth
Published: November 2018

This study was a part of a municipal research and development programme in home healthcare (HHC). The Oulu Patient Classification instrument (OPCq), part of the RAFAELA Nursing Intensity and Staffing system, was used to measure nursing intensity (NI) for the first time in HHC in Norway. The aim was to describe nurses’ work experiences and perceptions of the usability of the OPCq instrument when classifying NI in HHC. Twenty-two members of staff participated in four focus-group interviews. Content analyses were used to analyze and interpret the data. Three themes emerged: 1) Classifying the modified OPCq levels correctly; 2) Technological problems hinder use of the instrument; 3) Classifying NI when time pressure dominates. The OPCq instrument is useful in classifying NI, although some minor adjustments might be needed for its use in HHC. The nurses considered the OPCq instrument useful in illuminating the actual work situation in HHC and the time pressure they experience.
Independent assessment and outcomes of 196 short-tapered stems short-term follow-up and review of the literature
Authors: Nahas Sam , Patel Akash , Blucher Nicola , Vedi Vikas
Published: November 2018

Background:

Longer term outcome data are now becoming available for short-tapered femoral stems for cementless total hip arthroplasty. The shorter stem has a metaphyseal fit, loading the bone in this area, leading to physiological bone remodelling. It is also bone preserving, as it is 35 mm shorter. It may be easier to insert through a smaller incision and potentially reduce complication rates. We present a retrospective single surgeon case series of 196 patients (>53% follow-up over 5 years). All patients had the cementless ‘Microplasty Taperloc’ (Biomet). Primary outcome measures were femoral component revision rates. Secondary outcome measures included complications, patient-reported functional outcome scores (Oxford hip) and radiographic evidence of loosening.

Methods:

Patients were identified using electronic software. All were routinely followed up and assessed in clinic since implant introduction in 2009. Oxford hip scores were routinely obtained. A surgeon who had not carried out the procedure independently assessed radiographs.

Results:

One hundred ninety-six patients were identified. The revision rate was 0.5% due to an intraoperative peri-prosthetic fracture of the femur identified on post-operative radiograph. The complication rate was 2%, attributable to: subsidence of the prosthesis (one hip), post-operative dislocation (two hips), one of which required acetabular revision. Oxford hip scores increased on average from 21 to 45 (pre- to post-operatively). There were no signs of radiographic loosening.

Conclusion:

The results show that using the short-tapered stem is proving so far to be a reliable and safe alternative to its longer counterpart, with low complication rates in the short term.
Effects of Ulnar Collateral Ligament Reconstruction on Pitch Selection in Major League Baseball Pitchers
Authors: Peterson Eric E. , Handwork Patrick , Soloff Lonnie , Schickendantz Mark S. , Frangiamore Salvatore J.
Published: November 2018

Background:

Ulnar collateral ligament (UCL) injuries represent one of the most common impairments to the throwing arm of professional pitchers. Return to play and postoperative performance metrics have been studied extensively, but pitch selection before and after surgery has not been evaluated.

Purpose/Hypothesis:

This study aimed to characterize the effects of UCL reconstruction on pitch selection in Major League Baseball (MLB) pitchers. We hypothesized that pitchers will throw fewer fastballs and a greater percentage of off-speed pitches after undergoing UCL reconstruction.

Study Design:

Retrospective cohort study; Level of evidence, 3.

Methods:

Using publicly available data, we evaluated MLB pitchers who underwent UCL reconstruction between 2003 and 2014. Pitching data were collected for the 2 seasons before UCL reconstruction as well as the first 2 seasons after reconstruction; the data consisted of the total number of pitches thrown and the percentage of fastballs, curveballs, changeups, and sliders. Repeated-measures analysis of variance was used with post hoc least significant difference pairwise t tests to evaluate for statistical significance at P < .05.

Results:

Overall, 87 pitchers (mean age, 28.2 ± 3.5 years) met all inclusion and exclusion criteria. There was a statistically significant difference in the total number of pitches thrown before and after surgery ( P < .01) as well as in the percentage of fastballs thrown before and after surgery ( P = .02). There was also a statistically significant increase in the use of curveballs between 1 and 2 years postoperatively (7.5% and 8.8%, respectively; P = .01). No other findings were statistically significant.

Conclusion:

Pitchers who underwent UCL reconstruction were shown to have a statistically significant decline in the percentage of fastballs thrown postoperatively as compared with before injury, with a compensatory trend toward an increased use of curveballs and sliders.