Doctoral (PHDSW-GS)

This course is designed to prepare students for the dissertation, focusing primarily on the tasks involved in planning dissertation research. Emphasis will be placed on understanding the elements of a defensible dissertation proposal, with special attention given to the selection of a researchable topic, critical analysis and professional writing skills, and the application of knowledge about research methods to the chosen topic. Students will use the course to begin focusing on their topic of interest and to conceptualize how different research questions within that topic may be answered with appropriate methods. Mutual critique and discussion among students will be an important aspect of the course.

In order to maintain their matriculation status following completion of coursework, students must register for the one-credit course Doctoral Dissertation Research (PHDSW-GS 3026) each semester until they successfully defend their dissertation.

This course reviews the principles of quantitative research methods with the aim of providing a foundation of skills to (1) assess appropriate empirical methodologies and (2) design empirical research studies. The course will cover: - Formulation of research questions and appropriate empirical research methodologies - Assumptions and biases underlying methodologies - Sampling strategies and measurement - Quantitative/survey based observational studies - Experimental and quasi-experimental designs - Research ethics and principles of integrity and open science The course will also guide students on how to review and critique empirical research articles and conduct literature reviews of empirical research. This course assumes working knowledge of statistics and multi-variate regression analysis. Topics such as historical and content analysis, and mixed-methods and related qualitative research approaches, will be lightly incorporated but not formally covered during class. The course will introduce students to sources and resources for collecting and analyzing data, programming, and statistical software for implementing empirical methodologies, but will not explicitly cover these topics. ​

This course provides an introduction to basic methods of statistical analysis used in quantitative social work research. It will focus on both the conceptual understanding and the skills needed to analyze quantitative data. Skills will be applied using the Statistical Package for the Social Sciences (SPSS-PC).

This course is designed to introduce students to the principles and methods of qualitative methods and research. The course will cover the theoretical and disciplinary origins as well as applications of qualitative methods relevant to social work practice, programs, and policy.

This doctoral seminar prepares students for teaching in social work. It introduces students to selected literature on teaching and learning in higher education, including theories of adult learning, the social work education literature, the range of roles and responsibilities of faculty members, and current issues in social work education. Modes of teaching and learning and their relationship to subject matter, settings, and educational outcomes will be considered, and students' concurrent teaching activities will be used for reflective learning. In spring, the course will be project-based. Specifically, the MSW Program at NYU is asking for proposals on how best to evaluate the educational effectiveness of the Program. The instructor and the students will plan together how to develop one or more proposals as well as how the usual topics in the course can be addressed. Hence the course in spring, will offer a real-life exercise in educational planning and the evaluation of social work education.

This course is designed to provide new doctoral students with an introduction to the philosophical foundations of scientific research within the social work field, and with some of the general intellectual tools they will need to be effective participants and leaders in our field's theoretical and intellectual dialogue. There will also be an initial segment focusing on the conceptual foundations of social work as a profession. Philosophy of science enters into our work as intellectual leaders in the clinical-research domain in three ways. First, philosophy of science addresses fundamental general issues concerning the nature of knowledge, the evaluation of research, and preferable research methodologies across the sciences, and how to reason scientifically. Second, within social work itself, the debates in philosophy of science have found expression in specific disputes and divisions among social work researchers that can only be understood in the context of philosophy of science. And third, philosophy of science, in addressing the nature of theory change and rational assessment of beliefs, can be construed as indirectly addressing a perennial question in clinical theory: how can the therapist come to understand the client's theory of the world, by what evidence (or other processes) is the client's theory of the world maintained, and by what techniques might this theory be changed? In the course of these sessions, we will attempt to consider all three of these facets or levels of the interaction of philosophy of science with clinical research.

This course provides an overview of social science theories that are relevant to social work. Students will learn about the distinctions between paradigms, theories and conceptual models. Students will also develop a critical understanding of the history and application of social science concepts to social work. We will cover theories that have a forward trajectory toward contemporary issues and discuss alternative and critical views of social science theories.

This course is required for all PhD students. It is designed to expose students to some of the major cross-cutting themes in the United States social policy today (e.g., poverty and inequality, universalism and selectivity) and to a selected group from among those currently on the public agenda (e.g., the working poor, immigrants). The overarching goals of this course are that students learn about the major social policies and programs that affect people's well-being or quality of life and various aspects of social service delivery; understand the ways in which direct social work practice enacts social policies and is shaped by them; and develop expertise in understanding social policy content, policy actions of agencies, professional associations, and political bodies, and the skills needed to influence social policy. This course emphasizes the roles that social issues, values, power, politics, the economy, discrimination, and advocacy play in the dynamic policy making and implementation environment. This course thus provides students with the policy related competencies and practice skills for conducting research-informed policy analysis and advocating for policy change. In particular, through lecture and discussion this course will explicitly use issues relating to poverty, inequality, and opportunity with special, but not exclusive, emphasis on these phenomena in American society as an example to illustrate social policy analysis. The course will examine theoretical principles of social policy, US social policy history, poverty and inequality, the causes of poverty and inequality, major social program through policy analysis perspectives, and public policies designed to reduce poverty and inequality and promote opportunity. The course assumes some prior background in social policy. Students without this background will be expected to do some supplementary reading. The course reading list provides ample opportunity for students to "fill in" their basic social policy knowledge and enrich their background in areas of special interest.

The Social and Behavioral Intervention Research course focuses on essential conceptual, methodological and practical issues involved in planning and carrying out research on psychosocial and behavioral interventions relevant to social work practice and policy. The purpose of the course is to prepare doctoral students to design and critically assess intervention research studies that address psychosocial needs, problems, and conditions.

This course, the second of the statistics sequence for social work doctoral students, will focus on generalized linear models. Building upon the work done in your prior class, we will first learn how generalized linear models differ from linear models. We will briefly review models for binary (dichotomous) outcomes before examining models for outcomes that are ordinal, nominal (three or more categories), and counts. Then we will examine the idea of two-part models, where you can model outcomes through two (or more) equations, and explore some of its instantiations. You will then be introduced to two key concepts – first, fixed and random effects, which are important to understand if you are considering taking a next course on longitudinal data analysis (aka multilevel models). Second, I will give you a brief introduction to multilevel models, which will lay the conceptual groundwork for such a next course on these models. With your prior class, this class, and a future longitudinal/multilevel class, you will have completed the bulk of the slopes-and-intercept approach to data analysis. A foundation in this family of statistical analyses is necessary to your learning variance-covariance matrix-based approaches (e.g., path models, latent class/growth models, or structural equation models) that you may learn in future classes. All of the approaches that you have learned in this, and in your prior class, are associational, not causal. Causal knowledge, however, is the goal of science. Hence, we will end this course with an introduction to the orthodox theory of causality in research, called the potential outcomes framework. In this section, we will address two important approaches to enhancing causal inference - using existing variables ("observables") or leveraging time or something extraneous ("unobservables").

This course is an introduction to structural equation models as applied to problems in the social sciences, broadly defined. The major purpose of the course is to familiarize students with the technique of structural equation modeling and to provide them with working knowledge of relevant computer programs. Topics include limited information versus full information estimation strategies, single indicator structural modeling, confirmatory factor analysis, latent variable modeling, mediation analysis, and strategies for dealing with diverse error structures in model estimation.

This practicum is intended to provide hands-on experience for first-year PhD students who have complete Statistics I and Statistics II courses. Students will be asked to complete a research project that will entail all components of statistical analyses that were taught in Statistics I and Statistics II courses. Students will need to spend extensive amount of time on producing required statistical analysis outside of the classroom hours. By the end of the course, students are expected to produce a research report on a chosen topic with advanced statistical analysis.

This seminar is required for all first-year PhD students. It is designed with three primary purposes. The first is to provide the nuts-and-bolts in navigating the school and the University in the first year of study. The second is to expose students to the research expertise and scholarly career of the faculty (in an informal manner). The third is to provide students with an opportunity to sharpen their research interests by developing a brief research statement. Throughout the year, students also will have chances to lead the sessions on topics that are important to the learning process to cultivate students’ leadership skills. The overarching goals of this seminar are to immerse students in a learning environment with motivation, to get to know different trajectories in becoming an independent scholar, and to have growing confidence in their own research interests. This seminar thus provides students with the scholarly-related competencies and skills for successfully earning the PhD degree and becoming a promising young scholar.

This course will examine how evidence-based and evidence-informed practices are determined, give an overview of key evidence-based and evidence-informed practices, and consider their impact on clinical social work practice. Within the context of a growing emphasis on accountability and effectiveness in the behavioral health services, the course will explore the assumptions and values of evidence-based practice and how research is utilized to inform direct practice. The course also will examine the implementation of evidence-based and evidence-informed practices in real life settings examining the role of organizational climate, workforce competencies, policies and procedures, financing and community factors. Quantitative, qualitative, mixed methods and participatory research will be presented to demonstrate how these methods can inform different aspects of implementation. The course will use different implementation examples from behavioral health services to discuss issues of tailoring and fidelity in practice settings. Recent developments in implementation science and current healthcare policies will also be considered to understand the broader context for the implementation of evidence-based and evidence-informed practices.

This doctoral-level course seeks to provide students with the knowledge and tools to conduct rigorous research that addresses dimensions of human diversity, including social identities (e.g., race, ethnicity, gender identity, sexual orientation), language, and various forms of culture. Adopting culturally-informed and critical perspectives on social science research, this course guides students towards developing a reflexive stance towards considering issues related to power, positionality, and representation in knowledge production. Practical aspects of conducting research in both U.S. and global contexts, including formulating research questions, developing appropriate research designs and culturally-informed assessments, and sampling and recruitment issues will be discussed. Assignments will focus on the development of a viable research/grant proposal or empirical paper relevant to students' research focus.

This doctoral course is designed to introduce students to the principles and methods of mixed methods (qualitative and quantitative) in research. The course will cover the origins and ongoing development of mixed methods as a separate and evolving mode of inquiry offering notable benefits for addressing topics of research common in social work research, e.g. racial/ethnic disparities, child and family welfare, mental illness and recovery, substance misuse, disabilities, LGBTQI issues, chronic illness, homelessness, aging, etc. Various core and complex designs will be described and exemplified as well as methods of interpretation, integration and presentation of mixed methods studies. Exemplar studies will be used to illustrate the extensive diversity and complexity of mixed methods as practiced including work by scholars in critical theory, anti-racism, participatory action and other inclusive methods.** Prerequisites - must have completed a course in qualitative methods. **Open ONLY to doctoral students.**

This is the first semester of a 2-semester course (spring 2021 and fall 2021) and is designed to assist students writing a predoctoral dissertation grant to a federal funding agency; the skills learned, however are generalizable to other types of funders. Following an orientation to NIH and grant writing, students spend part of spring semester, all summer, and much of fall semester writing specific parts of grant applications, with an aim to submit an application in early December. Individual meetings are a mix of didactic writing strategies, invited speakers, and peer critique. Enrollment in both semesters is required. All participants must have a substantive area mentor (such as a dissertation chair) who will oversee the writing along with the instructional team. **Open to doctoral students in their 2nd year and above.**

This is the second semester of a 2-semester course (spring 2021 and fall 2021) and is designed to assist students writing a predoctoral dissertation grant to a federal funding agency; the skills learned, however are generalizable to other types of funders. Following an orientation to NIH and grant writing, students spend part of spring semester, all summer, and much of fall semester writing specific parts of grant applications, with an aim to submit an application in early December. Individual meetings are a mix of didactic writing strategies, invited speakers, and peer critique. Enrollment in both semesters is required. All participants must have a substantive area mentor (such as a dissertation chair) who will oversee the writing along with the instructional team. ** Prerequisite: PHDSW-GS 3079 Grant Writing I**

A supervised internship experience deemed academically valuable and approved in advance by the program director. It is supervised academically by a faculty member and professionally by an internship supervisor. Must be a full-time Silver PhD student in good academic standing. The experience culminates in a written report from the internship supervisor and a written assignment by the student. Student will receive a letter grade for the internship.

This Ph.D.-level course introduces students to the field of prevention science in the context of social work research and knowledge. The course will examine the prevention science paradigm and its concepts, and how these articulate with other closely related concepts and theoretical constructs in social work and social science. We will examine prevention research designs, methodological approaches and tools to derive preventive descriptive knowledge, introducing longitudinal and trajectory modeling. We will then examine research design and analytic tools that advance preventive change and intervention knowledge from micro to macro. This will include exposure to the prevention research cycle framework and select multi-level strategies.

The research practicum is a training opportunity focused on the development of skills for a successful career as an independent researcher and scholar. Doctoral students are paired with faculty mentors. The mentor pairing aims to foster the development of PhD students as independent researchers and scholars through greater attention to the development of specific research competencies. Each student should have the opportunity to engage in the following types of tasks: Research planning; Study Design; Study implementation; Data collection; Data analysis; Interpretation of findings; Community impact.

Independent study project under faculty supervision