Substantive Interest Research Articles

A Bayesian Latent Variable Selection Model for Nonignorable Missingness

Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as leaving the data incomplete and failing to accommodate incomplete covariates with interactions, non-linear terms, and random slopes. We propose a Bayesian latent variable imputation approach to impute missing data due to MNAR (and other missingness mechanisms) and estimate the model of substantive interest simultaneously. In addition, even when the incomplete covariates involves interactions, non-linear terms, and random slopes, the proposed method can handle missingness appropriately. Computer simulation results suggested that the proposed Bayesian latent variable selection model (BLVSM) was quite effective when the outcome and/or covariates were MNAR. Except when the sample size was small, estimates from the proposed BLVSM tracked closely with those from the complete data analysis. With a small sample size, when the outcome was less predictable from the covariates, the missingness proportions of the covariates and the outcome were larger, and the missingness selection processes of the covariates and the outcome were more MNAR and MAR, the performance of BLVSM was less satisfactory. When the sample size was large, BLVSM always performed well. In contrast, the method with an MAR assumption provided biased estimates and undercoverage confidence intervals when the missingness was MNAR. The robustness and the implementation of BLVSM in real data were also illustrated. The proposed method is available in the Blimp software application, and the paper includes a data analysis example illustrating its use.

Mediated Contestations About the Political Agency of Youth in Zimbabwe

ABSTRACT The political agency of youth has been the subject of much theoretical debate within the domains of political science, youth studies, conflict studies and development studies. This paper adopts a media studies perspective to contestations about the political agency of Zimbabwean youth. Motivation for doing so derives from the recognition that modern politics is predominantly a mass-mediated politics. Relatedly, the subject of youth and politics has received extensive media coverage in Zimbabwean media. Using the critical political economy approach and qualitative frame analysis, the paper explores two purposively sampled case studies that illustrate the contestations about the political agency of Zimbabwean youth. Findings reveal that media framings of youth agency sidestep the substantive policy and public interest issues that animate and motivate young politicians. Such normatively deficient framing is attributable to the political parallelism and media polarisation that characterises Zimbabwean political discourse.

И. А. Гончаров и философия науки его времени (проблема науки и религии)

During the period of rapid development of science and technology among the main representatives of Russian classical literature, only Alexander Herzen and Ivan Goncharov experienced a deep and substantive interest in the philosophy of science. For the author of “The Precipice,” this interest was associated with the main issue around which the dominant problematics of his work is concentrated: this is the question of the compatibility of scientific thinking and traditional faith. This work examines mainly one aspect of the topic: the writer's interest in natural science and, above all, in astronomy. Darwinism, with its thesis on the origin of man from ape, and astronomical discoveries that activated thoughts about life on other planets, gave rise to doubts in the mass consciousness about the established religious picture of the world. Goncharov defined his attitude to these changes long before the outbreak of the crisis of religious consciousness in the 1860s. As a conservative and deeply religious person, he took scientific progress seriously, not opposing it to religion and considering it an instrument of God's Providence for humanity. The crisis of religious consciousness in Russian society of the 19th century is regarded as the main subject of Goncharov's artistic research, which binds “A Common Story,” “Oblomov” and “The Precipice” into a trilogy.

Responsive and Adaptive Survey Design: Use of Bias Propensity During Data Collection to Reduce Nonresponse Bias

Abstract Reduction in nonresponse bias has been a key focus in responsive and adaptive survey designs, through multiple phases of data collection, each defined by a different protocol, and targeting interventions to a subset of sample elements. Key in this approach is the identification of nonrespondents who, if interviewed, can reduce nonresponse bias in survey estimates. From a design perspective, we need to identify an appropriate model to select targeted cases, in addition to an effective intervention (change in protocol). From an evaluation perspective, we need to compare estimates to a control condition that is often omitted from study designs, in addition to the need for benchmark estimates for key survey measures to provide estimates of nonresponse bias. We introduced a bias propensity approach for the selection of sample members to reduce nonresponse bias. Unlike a response propensity approach in which the objective is to maximize the prediction of nonresponse, this new approach deliberately excludes strong predictors of nonresponse that are uncorrelated with survey measures and uses covariates that are of substantive interest to the study. We also devised an analytic approach to simulate which sample members would have responded in a control condition. This study also provided a rare opportunity to estimate nonresponse bias, using rich sampling frame information, prior round survey data, and data from extensive nonresponse follow-up. The bias propensity model yielded reasonable fit despite the exclusion of the strongest predictors of nonresponse. The intervention was found to be effective in increasing participation among identified sample members. On average, the responsive and adaptive survey design reduced nonresponse bias by more than one-quarter—almost one percentage point—regardless of the choice of benchmark estimates. Effort under the control condition did not reduce nonresponse bias. While results are strongly encouraging, we argue for replication with varied populations and methods.

ИНТЕНСИФИКАЦИЯ ПРОЦЕССА ФУМИГАЦИИ СЕМЯН ЗЕРНОБОБОВЫХ КУЛЬТУР ЭЛЕКТРОФИЗИЧЕСКИМ МЕТОДОМ

Post-harvest processing of seeds of leguminous crops is an urgent task of the agro-industrial complex. The improvement of the known processes for disinfection and protection against insect pests is of substantive interest for research. The most effective and used is the fumigation process. The article describes a method for fumigation of seeds of leguminous crops with an ionized flow in a drum-type installation.

A Note on the Usefulness of Constrained Fourth-Order Latent Differential Equation Models in the Case of Small T

Constrained fourth-order latent differential equation (FOLDE) models have been proposed (e.g., Boker et al. 2020) as alternative to second-order latent differential equation (SOLDE) models to estimate second-order linear differential equation systems such as the damped linear oscillator model. When, however, only a relatively small number of measurement occasions T are available (i.e., T=50), the recommendation of which model to use is not clear (Boker et al. 2020). Based on a data set, which consists of T=56 observations of daily stress for N=44 individuals, we illustrate that FOLDE can help to choose an embedding dimension, even in the case of a small T. This is of great importance, as parameter estimates depend on the embedding dimension as well as on the latent differential equations model. Consequently, the wavelength as quantity of potential substantive interest may vary considerably. We extend the modeling approaches used in past research by including multiple subjects, by accounting for individual differences in equilibrium, and by including multiple instead of one single observed indicator.

Development of a plant for electrostatic fumigation of grain crops in a perfled layer

Improving the processes of post-harvest processing of leguminous crops is an urgent task for enterprises of the agro-industrial complex. The issues of ensuring reliable protection of leguminous crops from the effects of pathogenic microflora, quarantine insect pests are of sub-stantive interest for research. To date, fumigation is considered a common method of disinfecting products - the elimination of insect pests and pathogens by a gaseous or vaporous poisonous chemist. The article describes the design features of the installation for carrying out the process of fumigation of leguminous crops with an ionized flow of an air-dispersed mixture, and also presents some dependences characterizing the course of the process of electrostatic fumigation of legumes in the device being developed. The use of the proposed design of the installation for electrostatic fumigation of leguminous crops in an overflowing layer will allow for a uniform and high-quality fumigation process.

How to Compare Psychometric Factor and Network Models.

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples.

Defining and Identifying Per-protocol Effects in Randomized Trials.

In trials with noncompliance to assigned treatment, researchers might be interested in estimating a per-protocol effect-a comparison of two counterfactual outcomes defined by treatment assignment and (often time-varying) compliance with a well-defined treatment protocol. Here, we provide a general counterfactual definition of a per-protocol effect and discuss examples of per-protocol effects that are of either substantive or methodologic interest. In doing so, we seek to make more concrete what per-protocol effects are and highlight that one can estimate per-protocol effects that are more than just a comparison of always taking treatment in two distinct treatment arms. We then discuss one set of identifiability conditions that allow for identification of a causal per-protocol effect, highlighting some potential violations of those conditions that might arise when estimating per-protocol effects.

Cross-classified multilevel models (CCMM) in health research: A systematic review of published empirical studies and recommendations for best practices.

Recognizing that health outcomes are influenced by and occur within multiple social and physical contexts, researchers have used multilevel modeling techniques for decades to analyze hierarchical or nested data. Cross-Classified Multilevel Models (CCMM) are a statistical technique proposed in the 1990s that extend standard multilevel modeling and enable the simultaneous analysis of non-nested multilevel data. Though use of CCMM in empirical health studies has become increasingly popular, there has not yet been a review summarizing how CCMM are used in the health literature. To address this gap, we performed a scoping review of empirical health studies using CCMM to: (a) evaluate the extent to which this statistical approach has been adopted; (b) assess the rationale and procedures for using CCMM; and (c) provide concrete recommendations for the future use of CCMM. We identified 118 CCMM papers published in English-language literature between 1994 and 2018. Our results reveal a steady growth in empirical health studies using CCMM to address a wide variety of health outcomes in clustered non-hierarchical data. Health researchers use CCMM primarily for five reasons: (1) to statistically account for non-independence in clustered data structures; out of substantive interest in the variance explained by (2) concurrent contexts, (3) contexts over time, and (4) age-period-cohort effects; and (5) to apply CCMM alongside other techniques within a joint model. We conclude by proposing a set of recommendations for use of CCMM with the aim of improved clarity and standardization of reporting in future research using this statistical approach.

Eventual periodicity in the two-sector RSL model: equilibrium vis-à-vis optimum growth

This paper investigates the well-known phenomenon of eventual periodicity of Li–Yorke chaos in the context of the two-sector Robinson–Shinkai–Leontief model of economic growth. It locates its (i) presence under specific parameter restrictions that include the extreme classical saving specification, and its (ii) absence in savings generated by the optimization of an infinitely-lived representative agent with perfect foresight. These results in which rare events, chaos and stability are all brought together under the rubric of upward and downward inertia, while of substantive economic interest of their own, also highlight phenomena in economic dynamics that may go towards a clearer definitional understanding of chaotic systems.

Using a Projection IRT Method for Vertical Scaling When Construct Shift Is Present

AbstractIn vertical scaling, results of tests from several different grade levels are placed on a common scale. Most vertical scaling methodologies rely heavily on the assumption that the construct being measured is unidimensional. In many testing situations, however, such an assumption could be problematic. For instance, the construct measured at one grade level may differ from that measured in another grade (e.g., construct shift). On the other hand, dimensions that involve low‐level skills are usually mastered by almost all students as they progress to higher grades. These types of changes in the multidimensional structure, within and across grades, create challenges for developing a vertical scale. In this article, we propose the use of projective IRT (PIRT) as a potential solution to the problem. Assuming that a test measures a primary dimension of substantive interest as well as some peripheral dimensions, the idea underlying PIRT is to integrate out the secondary dimensions such that the model provides both item parameters and ability estimates for the primary dimension. A simulation study was conducted to evaluate the effectiveness of the PIRT as a method for vertical scaling. An example using empirical data from a measure of foundational reading skills is also presented.

U.S. Supreme Court Brief of Professors of Civil Procedure and Federal Courts as Amici Curiae in Support of Respondents, Ford Motor Co. v. Montana Eighth Judicial District Court, No. 19-368

This brief was filed on behalf of fifteen procedural and jurisdictional scholars desiring to promote an approach to personal jurisdiction that reflects fundamental principles of due process and respects precedent. Amici believe the car accidents prompting the underlying products-liability suits against Ford are so centered in Montana and Minnesota that requiring plaintiffs to litigate elsewhere would contradict traditional principles of state sovereignty and undermine the due-process interests at stake in the Fourteenth Amendment. Ford’s argument that specific personal jurisdiction requires a causal connection between its forum activities and the plaintiffs’ claim — such that it can only be sued where it designed, manufactured, or originally sold an allegedly defective vehicle — is not supported by any traditional due-process interest. Ford sought to induce Montana and Minnesota citizens to buy and trust Ford products, and the specific vehicles at issue were purchased second-hand in Montana and Minnesota before accidents on the States’ roadways involving State citizens. Ford’s conduct thus implicates the sovereign authority of Montana and Minnesota, as “every State owes protection to its own citizens,” Pennoyer v. Neff, and each State possesses a “significant interest in redressing injuries” within its borders to regulate and deter wrongful conduct. Keeton v. Hustler Magazine, Inc. Ford suggests that exercising jurisdiction would violate its substantive due-process interest because it would be unable to predict or control its jurisdictional exposure. But the exercise of jurisdiction in these cases neither violates historical limits on the “contacts, ties, or relations” necessary to subject nonresident defendants to binding judgments, nor contravenes Ford’s expectations about amenability to suit. Courts, including the Supreme Court, have long acknowledged and upheld State sovereign judicial power to protect citizens from allegedly dangerous products by compelling product manufacturers conducting extensive in-state marketing and sales to answer claims for their products causing in-state injuries, irrespective of where the products were originally designed, manufactured, or sold. See Asahi Metal Industry Co. v. Superior Court; World-Wide Volkswagen Corp. v. Woodson. Ford also argues that allowing Montana and Minnesota to exercise jurisdiction would violate horizontal-federalism interests. But a State’s sovereign power within its borders necessarily includes some ability to regulate conduct outside its borders. The question, then, is not whether the State’s regulatory authority reached out-of-state conduct, but whether regulating out-of-state conduct encroaches on the interest of a sister State more tightly connected to the conduct at issue. In these cases, the vehicles were purchased second-hand in the forum, registered in the forum, and the plaintiffs suffered injury in the forum. No other State has a greater interest in regulating these incidents. The plaintiffs thereby established the necessary “connection between the forum and the specific claims at issue” to satisfy the traditional demands of the Due Process Clause.

Extreme and Inconsistent: A Case-Oriented Regression Analysis of Health, Inequality, and Poverty

A methodological paradox characterizes macro-comparative research: it routinely violates the assumptions underlying its dominant method, multiple regression analysis. Comparative researchers have substantive interest in cases, but cases are largely rendered invisible in regression analysis. Researchers seldom recognize the mismatch between the goals of macro-comparative research and the demands of regression methods, and sometimes they end up engaging in strenuous disputes over particular variable effects. A good example is the controversial relationship between income inequality and health. Here, the authors offer an innovative method that combines variable-oriented and case-oriented approaches by turning ordinary least squares regression models “inside out.” The authors estimate case-specific contributions to regression coefficient estimates. They reanalyze data on income inequality, poverty, and life expectancy across 20 affluent countries. Multiple model specifications are dependent primarily on two countries with values on the outcome that are extreme in magnitude and inconsistent with conventional theoretical expectations.

GUARANTEES OF ACCESS TO ADMINISTRATIVE JUDICIARY

Introduction. Administrative proceedings for Ukrainian administrative law, as well as for the administrative law of most post-Soviet states, are a relatively new legal phenomenon. This presupposes the existence of many problems of its formation, which are connected, in particular, with the socio-political transformations that are still going on. These are, first of all, such problems as the formation and legislative consolidation of the legal basis for guaranteeing access and protection in the administrative court. Unhindered access to court and access to justice are necessary conditions for the exercise of the constitutional right to judicial protection. The main results of the study. Access to justice is one of the prerequisites for the establishment of this branch of government as a full-fledged and self-sufficient mechanism for the protection of human rights and freedoms. The Constitution of Ukraine laid the foundations for the formation of access to justice, stipulating that recourse to the court for the protection of human and civil rights and freedoms is guaranteed directly on the basis of the Basic Law. The influence of international normative legal acts on the development of national legislation regulating a person's right to apply to an administrative court for protection was considered. The Constitution of Ukraine guarantees the right of a person to judicial protection and appeal against decisions, actions or omissions of public authorities, local governments, officials and officials. Administrative justice is called upon to implement this provision. Conclusions. The article determined that the right to appeal against decisions, actions or omissions of public authorities, local governments, officials and officials, a component of which is the right to go to court (right to access to court proceedings), is not abstract, but has a connection. connection with the right of a particular person in whose interests the trial is taking place, and with his conviction that the state, represented by public authorities and local governments, officials and officials have unlawfully interfered with his rights or freedoms. The obligatory feature of a public law dispute was that a person believes that there is a violation of his rights and freedoms as a result of the performance or non-performance of government functions. In order to go to court, a person who is a plaintiff must have a substantive legal interest in resolving a public law dispute. The article highlighted and analyzed some problems of ensuring access to justice by administrative courts in resolving public law disputes. His own vision for solving and eliminating the problems of access to justice in administrative proceedings is offered.

‘The Book of the City of Ladies’ and Other Writings by Christine de Pizan

MLR, .,   and understanding of the theorists with whom Germana puts him in conversation. (e extended discussion of how Ellison was so influenced by Northrop Frye’s book e Fools of Time: Studies in Shakespearean Tragedy in itself makes the book worth reading.) e major chapters focus on, in order: Invisible Man and the historical/temporal concepts of Nietzsche and Bergson; Invisible Man and the historical figure of Henry Box Brown (as far as I am aware, this correspondence has never been remarked in Ellison scholarship); Ellison’s extensive collection of Polaroid pictures and his unfinished second novel; Ellison’s ‘polyrhythmic and metric techniques’ (p. ) both in his short fiction and in ree Days before the Shooting . . .; and finally Ellison’s substantial body of music criticism and musicology and how that work interweaves with his fiction writing throughout his career. e close readings and textual discussions are suggestive and learned. Although certain terms and concepts are at times confusing or perhaps overdone, the dense philosophical web of allusions and concepts does yield new readings of Ellison’s primary writings. e results are indeed profound, as Germana concludes that Ellison’s ‘commitment to reclaiming the protean within the persistent, the chaos within certainty’ is precisely what ‘makes his work not merely relevant, but truly indispensable in the twenty-first century’ (p. ). W  L U M C. C ‘e Book of the City of Ladies’ and Other Writings. By C  P. Ed. by S B and R K. Trans. by I H. Indianapolis: Hackett. . $; £. (pbk $; £.). ISBN –– –– (pbk ––––). is new English translation of Christine de Pizan’s Cité des dames is accompanied by selections from her Advision Cristine (Christine’s Vision), Corps de Policie (Book of the Body Politic) and Lamentation sur les maux de la France (Lamentation on France’s Ills), all of which are a pleasure to read in Ineke Hardy’s renderings. In a stimulating introductory essay, editors Sophie Bourgault and Rebecca Kingston argue that the Cité, a work generally read for its defence of women, also makes ‘a worthy contribution’ to ‘traditions of political reflection’ and to ‘philosophical debates about the nature of the virtues and their place in the well lived life’ (p. xviii). at welcome orientation takes us further into understanding the work of this brilliant fieenth-century writer. Substantive modern interest in Christine and her work, which initially coincided with the attention brought to women’s issues in the s and s, at first focused on her writing about women, and especially on the Cité. While the Cité remains a centrepiece of Christine Studies, scholars have now broadened their enquiry to examine other texts from Christine’s large body of writing, especially those that illuminate her political views and her strong interest in virtue ethics. One rewarding result has been concentrated research into Christine’s thoughts about government  Reviews (especially France’s government), and into her recommendations for a well-run society . e Cité itself is an engaged and erudite rebuke both to the historical method Christine knew and to the specific historical narratives of her time, which both justified and structured the assumptions, institutions, and political practices of the generations for whom they were written. Some recent studies by French researchers could have lent additional support to Bourgault and Kingston’s thesis. ese include Françoise Autrand, Christine de Pizan : une femme en politique (Paris: Fayard, ); Claire Le Ninan, Le Sage Roi et la clergesse: l’écriture du politique dans l’œuvre de Christine de Pizan (Paris: Champion, ); and Anne Paupert, ‘“Te donrai preuve par exemples”: statut et fonction des exemples dans Le Livre de la Cité des Dames de Christine de Pizan’, Elseneur,  (), –. Works by Christine translated or mentioned in this volume are unfortunately given by their English titles only; the Ditié de Jehanne d’Arc is a curious exception but one misses any reference to the authoritative edition and translation of the poem by Angus J. Kennedy and Kenneth Varty (Medium Ævum Monographs,   (Oxford: Society for the Study of Mediaeval Languages and Literature, )). is City is the third expert English translation of the work published in the last four decades. Hardy comments very briefly on how her translation...

Review of Outlier Detection and Identifying Using Robust Regression Model

Outliers are observations that have extreme value relations. Herewith leverage is a measure of how an independent variable deviates from its mean. An observation with an extreme value on a predictor variable is a point with high leverage. The presence of outliers can lead to inflated error rates and substantial distortions of parameter and statistic estimates when using either parametric or nonparametric tests. Casual observation of the literature suggests that researchers rarely report checking for outliers of any sort and taking remedial measures for outliers. Outliers can have positive deleterious effects on statistical analyses. For instance, they serve to increase error variance and reduce the power of statistical tests; they can decrease normality, altering the odds of making both Type I and Type II errors for non- randomly distributed; and they can seriously bias or influence estimates that may be of substantive interest. These outliers are cased from incorrect recording data, intentional or motivated mis-reporting, sampling error and Outliers as legitimate cases sampled from the correct population. According to some literatures; Point outliers, Contextual Outliers and Collective Outliers are the three types of outliers. Robust regression estimators can be a powerful tool for detection and identifying outliers in complicated data sets. Robust regression, deals with the problem of outliers in a regression and produce different coefficient estimates than OLS does.

The danger of conflating level-specific effects of control variables when primary interest lies in level-2 effects.

In the multilevel modelling literature, methodologists widely acknowledge that a level-1 variable can have distinct within-cluster and between-cluster effects, and that failing to disaggregate these can yield a slope estimate that is an uninterpretable, conflated blend of the two. Methodologists have stated, however, that including conflated slopes of level-1 variables in a model is not problematic if substantive interest lies only in effects of level-2 predictors. Researchers commonly follow this advice and use methods that do not disaggregate effects of level-1 control variables (e.g., grand mean centering) when examining effects of level-2 predictors. The primary purpose of this paper is to show that this is a dangerous practice. When level-specific effects of level-1 variables differ, failing to disaggregate them can severely bias estimation of level-2 predictor slopes. We show mathematically why this is the case and highlight factors that can exacerbate such bias. We corroborate these findings with simulations and present an empirical example, showing how such distortions can severely alter substantive conclusions. We ultimately recommend that simply including the cluster mean of the level-1 variable as a control will alleviate the problem.

Objective Bayes model selection of Gaussian interventional essential graphs for the identification of signaling pathways

A signalling pathway is a sequence of chemical reactions initiated by a stimulus which in turn affects a receptor, and then through some intermediate steps cascades down to the final cell response. Based on the technique of flow cytometry, samples of cell-by-cell measurements are collected under each experimental condition, resulting in a collection of interventional data (assuming no latent variables are involved). Usually several external interventions are applied at different points of the pathway, the ultimate aim being the structural recovery of the underlying signalling network which we model as a causal Directed Acyclic Graph (DAG) using intervention calculus. The advantage of using interventional data, rather than purely observational one, is that identifiability of the true data generating DAG is enhanced. More technically a Markov equivalence class of DAGs, whose members are statistically indistinguishable based on observational data alone, can be further decomposed, using additional interventional data, into smaller distinct Interventional Markov equivalence classes. We present a Bayesian methodology for structural learning of Interventional Markov equivalence classes based on observational and interventional samples of multivariate Gaussian observations. Our approach is objective, meaning that it is based on default parameter priors requiring no personal elicitation; some flexibility is however allowed through a tuning parameter which regulates sparsity in the prior on model space. Based on an analytical expression for the marginal likelihood of a given Interventional Essential Graph, and a suitable MCMC scheme, our analysis produces an approximate posterior distribution on the space of Interventional Markov equivalence classes, which can be used to provide uncertainty quantification for features of substantive scientific interest, such as the posterior probability of inclusion of selected edges, or paths.

A SEMIPARAMETRIC MODELING APPROACH USING BAYESIAN ADDITIVE REGRESSION TREES WITH AN APPLICATION TO EVALUATE HETEROGENEOUS TREATMENT EFFECTS.

Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and covariates and interactions among covariates. We extend BART to a semiparametric regression framework in which the conditional expectation of an outcome is a function of treatment, its effect modifiers, and confounders. The confounders are allowed to have unspecified functional form, while treatment and effect modifiers that are directly related to the research question are given a linear form. The result is a Bayesian semiparametric linear regression model where the posterior distribution of the parameters of the linear part can be interpreted as in parametric Bayesian regression. This is useful in situations where a subset of the variables are of substantive interest and the others are nuisance variables that we would like to control for. An example of this occurs in causal modeling with the structural mean model (SMM). Under certain causal assumptions, our method can be used as a Bayesian SMM. Our methods are demonstrated with simulation studies and an application to dataset involving adults with HIV/Hepatitis C coinfection who newly initiate antiretroviral therapy. The methods are available in an R package called semibart.