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Vorlesungsverzeichnis >> Fakultät Sozial- und Wirtschaftswissenschaften >> Bachelor-/Masterstudiengang Soziologie >> Master Soziologie >>
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Methoden der empirischen Sozialforschung inkl. Studienschwerpunkt
Lehrveranstaltungen der Modulgruppe B.] Methoden der empirischen Sozialforschung und des Kernbereichs der Modulgruppe C.3] Empirische Sozialforschung
Zur aktuellen Zusammensetzung der Module
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Fortgeschrittene Analysemethoden der quantitativen Sozialforschung: Ereignisanalyse I (Vorlesung) -
- Dozent/in:
- Hans-Peter Blossfeld
- Angaben:
- Vorlesung, 2 SWS, Besuch der Vorlesung ist nur parallel mit der Übung Ereignisanalyse möglich. Eine Anmeldung ist für die Vorlesung und Übung erforderlich.
- Termine:
- Di, 16:00 - 18:00, FMA/00.06
- Inhalt:
- Ziel dieser Vorlesung ist die Einführung in die Theorie und Anwendung der Ereignisanalyse. Die Methoden der Ereignisanalyse haben in den letzten beiden Jahrzehnten mit der zunehmenden Verfügbarkeit von Längsschnittdaten in der Soziologie an Bedeutung gewonnen. Unter "Ereignisdaten" versteht man Daten, die über die genauen Zeitdauern bis zu einem Zustandswechsel und deren Abfolge informieren. Beispiele hierfür sind die Dauern von Arbeitslosigkeitsphasen in der Arbeitsmarktforschung, die "Lebensdauer" politischer Systeme in der politischen Soziologie, die Dauer von Lernprozessen in der Bildungssoziologie, die Zeitspanne bis zu einem Umzug in eine andere Region in der Mobilitätsforschung, der Zeitraum bis zur Rückfälligkeit von Straftätern in der Kriminologie, die Verweildauer von Kindern im elterlichen Haushalt in der Jugend- und Familiensoziologie etc.
Zum Kurs "Ereignisanalyse" wird parallel eine Übung stattfinden, die von Dr. Gwendolin J. Blossfeld mit Hilfe des Programms Stata und auf der Grundlage von Daten aus der Lebensverlaufsforschung und den Nationalen Bildungspanels abgehalten wird. Voraussetzung für den Erwerb eines Leistungsnachweises ist der kontinuierliche Besuch der Vorlesung und der Übung sowie die Durchführung und Abgabe von Hausarbeiten (die Einzelheiten dazu werden in der Übung bekannt gegeben).
- Empfohlene Literatur:
- Blossfeld, Hans-Peter, Götz Rohwer and Thorsten Schneider (2019): Event History Analysis with Stata, London and New York Routledge (Taylor and Francis Group) (Autorenrabatt zu Semesterbeginn möglich)
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Fortgeschrittene Verfahren der Längsschnittanalyse: Ereignisanalyse I (Vorlesung) -
- Dozent/in:
- Hans-Peter Blossfeld
- Angaben:
- Vorlesung, 2 SWS, Besuch der Vorlesung ist nur parallel mit der Übung Ereignisanalyse möglich. Eine Anmeldung ist für die Vorlesung und Übung erforderlich.
- Termine:
- Di, 16:00 - 18:00, FMA/00.06
- Inhalt:
- Ziel dieser Vorlesung ist die Einführung in die Theorie und Anwendung der Ereignisanalyse. Die Methoden der Ereignisanalyse haben in den letzten beiden Jahrzehnten mit der zunehmenden Verfügbarkeit von Längsschnittdaten in der Soziologie an Bedeutung gewonnen. Unter "Ereignisdaten" versteht man Daten, die über die genauen Zeitdauern bis zu einem Zustandswechsel und deren Abfolge informieren. Beispiele hierfür sind die Dauern von Arbeitslosigkeitsphasen in der Arbeitsmarktforschung, die "Lebensdauer" politischer Systeme in der politischen Soziologie, die Dauer von Lernprozessen in der Bildungssoziologie, die Zeitspanne bis zu einem Umzug in eine andere Region in der Mobilitätsforschung, der Zeitraum bis zur Rückfälligkeit von Straftätern in der Kriminologie, die Verweildauer von Kindern im elterlichen Haushalt in der Jugend- und Familiensoziologie etc.
Zum Kurs "Ereignisanalyse" wird parallel eine Übung stattfinden, die von Dr. Gwendolin J. Blossfeld mit Hilfe des Programms Stata und auf der Grundlage von Daten aus der Lebensverlaufsforschung und den Nationalen Bildungspanels abgehalten wird. Voraussetzung für den Erwerb eines Leistungsnachweises ist der kontinuierliche Besuch der Vorlesung und der Übung sowie die Durchführung und Abgabe von Hausarbeiten (die Einzelheiten dazu werden in der Übung bekannt gegeben).
- Empfohlene Literatur:
- Blossfeld, Hans-Peter, Götz Rohwer and Thorsten Schneider (2019): Event History Analysis with Stata, London and New York Routledge (Taylor and Francis Group) (Autorenrabatt zu Semesterbeginn möglich)
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Advanced Methods of Analysis in Quantiative Social Research: Multilevel analysis using comparative micro data (Part A) -
- Dozentinnen/Dozenten:
- Michael Gebel, Jonas Voßemer
- Angaben:
- Seminar, 2 SWS
- Termine:
- Mi, 8:00 - 10:00, RZ/01.02
- Voraussetzungen / Organisatorisches:
- It is not necessary to register for the seminar in advance (e.g. via Flexnow, via email, etc.). More information about the course and registration guidelines will only be provided during the first seminar session.
Students have to be familiar with the contents of the compulsory lecture “Research design” and multiple linear and binary logistic regression analysis. Moreover, students are required to be familiar with the statistics package Stata. These skills could either be acquired or refreshed in self-studies or by attending an additional compact tutorial course (This was offered at the beginning of the winter term).
Language of instruction: English.
Module-related examination: Portfolio (time: 3 months); can be either written in English or German
- Inhalt:
- Learning targets:
The central aim of this course is to empower participants to critically discuss basic concepts and assumptions of multilevel analyses using comparative micro data, to conduct theory-driven empirical research, to choose and specify the appropriate models according to the ideas of modern causal analysis, to take the levels and scales of measurement of variables into account, to independently carry out multilevel analyses using the statistics package Stata, to correctly interpret and clearly present the results of multilevel analyses in tables and graphs.
Course contents:
Multilevel analysis has been especially applied to the case of many clusters and few observations within each cluster, e.g. in education research on pupils nested in classes and schools. However, multilevel analysis is more and more often used in international comparative social research. Following the latter comparative research tradition, this course is devoted to the specific problem of a small number of countries and large numbers of individuals within each country. This course quickly repeats the foundations of multiple regression analysis, introduces the basics of multilevel analysis and focuses on advanced topics of multilevel analysis. Models for continuous and binary dependent variables are presented. Moreover, it is discussed how many and which kind of macro level variables should be included to account for the macro context. A specific focus is on the specification and interpretation of cross-level interactions. Exemplary empirical studies and current debates in multilevel analysis of comparative micro-data are discussed. In lab sessions participants will learn how to practically implement multilevel analyses of comparative microdata using the statistics package Stata. The lab sessions and the portfolio will draw on topical sociological questions and data of the European Social Survey (ESS).
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Advanced Methods of Analysis in Quantiative Social Research: Multilevel analysis using comparative micro data (Part B) -
- Dozentinnen/Dozenten:
- Michael Gebel, Jonas Voßemer
- Angaben:
- Seminar, 2 SWS
- Termine:
- Mi, 10:00 - 12:00, RZ/01.02
- Voraussetzungen / Organisatorisches:
- It is not necessary to register for the seminar in advance (e.g. via Flexnow, via email, etc.). More information about the course and registration guidelines will only be provided during the first seminar session.
Students have to be familiar with the contents of the compulsory lecture “Research design” and multiple linear and binary logistic regression analysis. Moreover, students are required to be familiar with the statistics package Stata. These skills could either be acquired or refreshed in self-studies or by attending an additional compact tutorial course (This was offered at the beginning of the winter term).
Language of instruction: English.
Module-related examination: Portfolio (time: 3 months); can be either written in English or German
- Inhalt:
- Learning targets:
The central aim of this course is to empower participants to critically discuss basic concepts and assumptions of multilevel analyses using comparative micro data, to conduct theory-driven empirical research, to choose and specify the appropriate models according to the ideas of modern causal analysis, to take the levels and scales of measurement of variables into account, to independently carry out multilevel analyses using the statistics package Stata, to correctly interpret and clearly present the results of multilevel analyses in tables and graphs.
Course contents:
Multilevel analysis has been especially applied to the case of many clusters and few observations within each cluster, e.g. in education research on pupils nested in classes and schools. However, multilevel analysis is more and more often used in international comparative social research. Following the latter comparative research tradition, this course is devoted to the specific problem of a small number of countries and large numbers of individuals within each country. This course quickly repeats the foundations of multiple regression analysis, introduces the basics of multilevel analysis and focuses on advanced topics of multilevel analysis. Models for continuous and binary dependent variables are presented. Moreover, it is discussed how many and which kind of macro level variables should be included to account for the macro context. A specific focus is on the specification and interpretation of cross-level interactions. Exemplary empirical studies and current debates in multilevel analysis of comparative micro-data are discussed. In lab sessions participants will learn how to practically implement multilevel analyses of comparative microdata using the statistics package Stata. The lab sessions and the portfolio will draw on topical sociological questions and data of the European Social Survey (ESS).
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Advanced methods of multilevel analysis and international comparsion: Multilevel analysis using comparative micro data -
- Dozentinnen/Dozenten:
- Michael Gebel, Jonas Voßemer
- Angaben:
- Seminar, 4 SWS
- Termine:
- Mi, 8:00 - 12:00, RZ/01.02
- Voraussetzungen / Organisatorisches:
- It is not necessary to register for the seminar in advance (e.g. via Flexnow, via email, etc.). More information about the course and registration guidelines will only be provided during the first seminar session.
Students have to be familiar with the contents of the compulsory lecture “Research design” and multiple linear and binary logistic regression analysis. Moreover, students are required to be familiar with the statistics package Stata. These skills could either be acquired or refreshed in self-studies or by attending an additional compact tutorial course (This was offered at the beginning of the winter term).
Language of instruction: English.
Module-related examination: Portfolio (time: 3 months); can be either written in English or German
- Inhalt:
- Learning targets:
The central aim of this course is to empower participants to critically discuss basic concepts and assumptions of multilevel analyses using comparative micro data, to conduct theory-driven empirical research, to choose and specify the appropriate models according to the ideas of modern causal analysis, to take the levels and scales of measurement of variables into account, to independently carry out multilevel analyses using the statistics package Stata, to correctly interpret and clearly present the results of multilevel analyses in tables and graphs.
Course contents:
Multilevel analysis has been especially applied to the case of many clusters and few observations within each cluster, e.g. in education research on pupils nested in classes and schools. However, multilevel analysis is more and more often used in international comparative social research. Following the latter comparative research tradition, this course is devoted to the specific problem of a small number of countries and large numbers of individuals within each country. This course quickly repeats the foundations of multiple regression analysis, introduces the basics of multilevel analysis and focuses on advanced topics of multilevel analysis. Models for continuous and binary dependent variables are presented. Moreover, it is discussed how many and which kind of macro level variables should be included to account for the macro context. A specific focus is on the specification and interpretation of cross-level interactions. Exemplary empirical studies and current debates in multilevel analysis of comparative micro-data are discussed. In lab sessions participants will learn how to practically implement multilevel analyses of comparative microdata using the statistics package Stata. The lab sessions and the portfolio will draw on topical sociological questions and data of the European Social Survey (ESS).
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