Below, you will find an overview of courses from the current academic year of this Master's. This overview is meant to give you an idea of what to expect. The course offer may change in the coming academic year.

Year 1, semester 1

Sociological theory construction and model building

Basic features of problem-driven and systematic (deductive) theory construction, model building, and explanation in social science are illustrated using, among other things, macro- and micro-features of explanatory models as well as macro-micro-macro transitions. Basic micro-models include an introduction to principles of rational choice theory, game theory, behavioral models and applications of theoretical tools in sociology (these models are explicitly or implicitly used in many fields of sociology, including fields such as the interface of stratification and households or social networks and social capital that receive systematic attention in other SaSR-courses). Systematic reconstructions of social science theory emphasize explanations of macro-phenomena based on micro-models of behaviour and macro-micro-macro transitions. Applications will focus on key problems of sociology (cohesion and inequality), with an emphasis on paradigmatic macro-phenomena related to these problems such as effects of networks and institutional arrangements (organizations) on cohesion and inequality, and, conversely, effects of cohesion and inequality on the dynamics of networks and institutional arrangements. Generating testable hypotheses on macro-phenomena from underlying theory and the ability to assess available literature with respect to the 'performance' of such hypotheses in empirical research is a topic of the course.

Family and social inequality

Questions on social stratification, inequality and households are closely connected. Household conditions might create inequality in resources (examples are household characteristics such as the family of origin or divorce of own marriage), and sometimes inequality is measured by a household characteristic (e.g. heterogamy). An unequal distribution of socio-economic resources may also affect the structure of the household (e.g. family size). Both sociological and economic theories are applied to a range of research problems on stratification and households. An overview of research on stratification, inequality and households will be presented and acquired through self-study. Topics that will be covered are among others inequality of educational opportunities, family formation, the occupational career, and work-family balance. For each of these topics, theories to explain the diverse phenomena, accompanying testable hypotheses, research methods, data, and major empirical findings will be discussed.

SASR/MERM03 Methods and Statistics 1: Regression analysis and its generalizations

The first part of the course involves data handling, scale construction (mainly classical test theory, factor analysis), and the disciplined cautious use of syntax in statistical software (MERM: SPSS; SaSR: Stata). The second part of the course addresses statistical models, mostly from the class of generalized linear models. Models to be discussed:(1) Linear regression modeling for continuous dependent variables (such as income), focusing on modeling mediation, interactions and nonlinear relations;
(2) Regression models for binary dependent variables (such as whether or not people are employed): logistic and probit regression, emphasizing different types of interpretaions;
(3) Regression models for ordinal dependent variables (e.g., voting intentions measured by a Likert item): ordinal logit.
(4) Regression models for nominal dependent variables with subject-level and/or alternative-level predictors (e.g., the denomination of the school attended by children): multinomial logit and conditional logit models;
(5) Regression models for the time-until-the-occurrence-of-an-event (e.g., the birth of the first child, the divorce of a marriage, promotion in a career): discrete time survival analysis and Cox regression.

The discussion on these regression-type models focuses on the substantive interpretation of these non-lineair models. In addition, we discuss numerous general statistical issues such as statistical estimation methods; Wald testing versus likelihood ratio testing; Hausman-style tests for model specification; marginal effects, etc. Computer practical for MERM (using SPSS) and SaSR (using Stata) are separate.

Research practicum 1: Work-family issues, organizations, and inequality

Insights will be combined from the preceding theory course SASR1 (Sociological theory construction and model building), SASR2 (Family and social inequality), and the course SaSR3: Methods and Statistics course 1. Students will do so by writing a research paper in the format of a journal article: they choose a relevant research question, study the literature and formulate a theoretical answer, analyze data, and report on their findings. A complex dataset (European Sustainable Workforce Survey) - allowing answers to a considerable number of research questions - will be made available to the students. The European Sustainable Workforce Survey is a multi-actor dataset in which information is gathered from firms and employees in 9 European countries. During the first week, students will work on the research question the introduction of the paper, and get acquainted with the dataset. In the second week, the theory section is written, and preliminary analyses are performed. In the subsequent two weeks, the students will further analyze the data, report the results and write the conclusion. During the course, students will work in groups on their paper using theEuropean Sustainable Workforce Survey and meet the teacher several times per week. In the fourth week students will present their (provisional) results to the other students and discuss each other's work. Using the insights and remarks of the other students, they will finish their paper.

Year 1, semester 2

Social networks - theory and empirics

The notion of social networks has engendered a promising research program. We will discuss core concepts of social networks, its major assumptions, as well as the research problems that it helps to solve. We will deal with, amongst others, the availability of social settings which influence the chance of meeting others; the emergence and the decline of networks; social influence and threshold models; network effects on conflicts and occupational attainment; the role of sour social capital, i.e. having enemies; networks within organizations, like government agencies and the institutional conditioning the effects of networks; and collective social capital.

Starting with your thesis - literature review

At the beginning of the course, students choose a topic for their literature review from a set of topics proposed by the SaSR teachers. The students read relevant literature on the topic they chose and write a short literature review paper. Students get a good understanding of the state-of-the art in their selected field, culminating in a review paper that includes the research problem to be addressed in the student's thesis and an outline for the student's thesis research. The course comprises self-study with individual supervision by a SaSR-teacher in the field of the student's thesis research and, therefore, the likely supervisor of the student's thesis. The course also comprises several class meetings on issues of causality and a peer-feedback meeting to discuss the progress of the literature review. In addition a master class by a senior social scientist from abroad will be an element of the course.

Methods and Statistics 2: Structural equation modelling and multilevel analysis

The course is organized in 2 parts in a flexible format of 5 weeks each.

Part 1: Structural equation models (5 weeks).
The SEM framework integrates two types of models. First are simultaneous equations, i.e., an integrated set of regression models allowing the dependent variable (a `consequence') of one equation to be an independent variable (a `cause') in another equation. Second, `factor analytical' models for the reflexive measurement of latent variables will be introduced. These are widely applied for measuring attitudes, intentions, etc. Topics to be discussed: model specification; model fit; decomposition of effects; categorical variables; multiple group analysis; testing for structural and measurement invariance with dependent and independent groups; interactions involving latent variables; SEM for longitudinal data; latent curve models.
Class schedule: twice a week a short lecture, followed by a short computer practical (on te same day)

Part 2: Multi-level models (5 weeks).
These models are often used for the analysis of `hierarchical problems' in which the causes of outcomes (e.g., the performance of pupils in schools) are located at the level of the individual (e.g., own and parental resources) as well as in the context shared by some of the individuals (e.g., characteristics of the class and of the teacher). Data with this structure violate the assumption of `independent observations' made in, e.g., standard regression analysis. Multilevel models can also be used with longitudinal designs (`time points within persons', panel data). We will focus mostly on the versions of the model with a `continuous' response variable, Time permitting the modification to the binary case, designs with more than two levels (e.g., students within classes within schools), cross-classified designs, and multilevel extensions of SEMs (multilevel path models, multilevel factor analysis) will be introduced.
Class schedule: each week, one 3h lecture and one 3h computer practical on different days.

Research practicum 2: Social network analysis

Social networks are a key concept in numerous sociological theories and empirical applications. Empirically, analyses related to social networks are often quite complex because of interdependencies between actors, which violate the assumptions made in standard statistical methods. In the course, different types of research problems that are central in recent sociological research and that require different statistical approaches will be discussed. We introduce important network characteristics and discuss issues related to the collection and reliability of network data. We inquire into problems related to how social networks of actors affect their behavior and apply this to multi-level models. Lastly, causality issues are addressed in social network research and empirically connected to structural equation modelling. During the whole course, students work on a poster, representing an own research problem, arguments and network analyses. Throughout the course, students will be supplied with recent research articles.

Year 2, semester 1

Electives and research experiences

The Electives will be designed individually for each student. Typically, the Electives will consist of several and separate components. A good Electives “package” could comprise the components listed below. However, the Electives do NOT have to comprise all these components:

  1. Participation in a summer school like Essex, Ljubljana, Ann Arbor etc. Typically, participation in a summer school aims at building up additional M&S-expertise for the master thesis project. Participation in a summer school that is more closely related to building up field-specific knowledge and theoretical expertise in the substantive field of the master thesis project is likewise an option.
  2. Attending relevant courses outside the SaSR-program in Utrecht or at other universities. These courses should contribute to building up useful expertise (theoretical and domain-specific expertise and/or relevant expertise in research methodology and statistical modelling) in the field of the master’s thesis project.
  3. An internship: active participation in a research project that contributes to the skills and expertise needed for a research career at a university or a research institute. Ideally an internship builds up expertise for the student’s master’s thesis project. An internship can take place at Utrecht University, at another university or at a research institute.
  4. Exchange with Mannheim (Germany) or Linköping (Sweden): Students can spend the first semester of the second year following courses and/or doing an internship at the Department of Sociology at University of Mannheim or the Institute for Analytical Sociology at Linköping University.

The course manual describes opportunities and restrictions concerning the electives in more detail. Details on the specific nature of the electives will be decided in close consultation with the thesis supervisor.

Research seminar 1: Building a theory

During the course we will:a) discuss core elements of a master's thesis project and of the master's thesis itself ;
b) provide and discuss examples of previous research that can help students (i) in designing and executing their own research, and (ii) to learn how to review;
c) offer a forum where students can regularly present and discuss their own project and draft versions of (selected parts of) the thesis;
d) provide systematic feedback on the progress of each student's project and thesis. This research seminar focuses on the problem background of the projects, on theories (including theoretical models), and on hypotheses, but students are expected to explore the data as well.

Students are trained in the following academic skills:
- Formulation of research questions- Reconstruction of theories
- Deduction of hypotheses- Search and selection of relevant scientific literature
- Synthesize and structure relevant scientific literature
- Academic writing- Reviewing skills - Presentation skills.

Master's thesis: A publishable article

The criteria for the evaluation of the thesis are: (a) focus on a research problem that is well embedded in the state of the art in the research field of the thesis; (b) a theoretical elaboration of the research problem and testable hypotheses that are generated from underlying theory; (c) an empirical test of some hypotheses; (d) appropriate reporting of the thesis research according to common standards for research articles. The master's thesis is written under individual supervision by a SaSR-teacher and will be evaluated by the supervisor as well as independently by another SaSR teacher.

Year 2, semester 2

Research seminar 2: Analysing, reporting and discussing your findings

Students are instructed and supervised in preparing the empirical part of their thesis: data collection, methods and analysis, reporting on the results. Students present and review their progress in weekly meetings. Students learn (academic skills):

  • to report on their data collection, data manipulation, variable construction, and method in a clear and precise way
  • to present their results, showing understanding of their findings, and reacting to criticism.
  • to report on their results in a correct and clear way.
  • to write a conclusion and discussion
  • to critically review the work of their fellow students and propose improvements.

Master's thesis: A publishable article

The criteria for the evaluation of the thesis are: (a) focus on a research problem that is well embedded in the state of the art in the research field of the thesis; (b) a theoretical elaboration of the research problem and testable hypotheses that are generated from underlying theory; (c) an empirical test of some hypotheses; (d) appropriate reporting of the thesis research according to common standards for research articles. The master's thesis is written under individual supervision by a SaSR-teacher and will be evaluated by the supervisor as well as independently by another SaSR teacher.