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# 230107 UE EC: Logistic Regression (2022S)

Continuous assessment of course work

## Labels

Covid19 Information zum Unibetrieb - aktuelle Bestimmungen:

https://www.univie.ac.at/ueber-uns/weitere-informationen/coronavirus/?pk_campaign=HomeDE&pk_kwd=Covid-InfolinkRahmenbedingungen für digitale Prüfungen (Soziologie) https://soziologie.univie.ac.at/info/digpruef/Allgemeiner Hinweis: Für die Teilnahme an Lehrveranstaltungen in digitaler Form sind eine - möglichst stabile - Internetverbindung und die technischen Möglichkeiten erforderlich, um an Online-Einheiten partizipieren zu können (Computer, Mikro, ggf. Webcam). Bei Lehrveranstaltungen aus dem Bereich quantitative Methoden kommen mitunter spezielle Programme (z.B. Stata, SPSS) hinzu, die über den zentralen Informatikdienst von Studierenden vergünstig bezogen werden können.

https://www.univie.ac.at/ueber-uns/weitere-informationen/coronavirus/?pk_campaign=HomeDE&pk_kwd=Covid-InfolinkRahmenbedingungen für digitale Prüfungen (Soziologie) https://soziologie.univie.ac.at/info/digpruef/Allgemeiner Hinweis: Für die Teilnahme an Lehrveranstaltungen in digitaler Form sind eine - möglichst stabile - Internetverbindung und die technischen Möglichkeiten erforderlich, um an Online-Einheiten partizipieren zu können (Computer, Mikro, ggf. Webcam). Bei Lehrveranstaltungen aus dem Bereich quantitative Methoden kommen mitunter spezielle Programme (z.B. Stata, SPSS) hinzu, die über den zentralen Informatikdienst von Studierenden vergünstig bezogen werden können.

## Registration/Deregistration

**Note:**The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

- Registration is open from
**We 02.02.2022 10:00**to**Mo 21.02.2022 10:00** - Registration is open from
**Th 24.02.2022 10:00**to**Fr 25.02.2022 10:00** - Deregistration possible until
**Su 20.03.2022 23:59**

## Details

max. 40 participants

Language: English

### Lecturers

### Classes (iCal) - next class is marked with N

Monday
14.03.
10:00 - 14:00
PC-Raum 1 Schenkenstraße 8-10, 1.UG

Monday
21.03.
10:00 - 14:00
PC-Raum 1 Schenkenstraße 8-10, 1.UG

Monday
28.03.
10:00 - 14:00
PC-Raum 1 Schenkenstraße 8-10, 1.UG

## Information

### Aims, contents and method of the course

### Assessment and permitted materials

The format of classes will be informal. Lectures will be short, and the focus of classes will be computer exercises and classroom discussions of results and homework. Lectures will take up at most a third of the overall classroom time as the focus in this class is on practical analysis. Students are encouraged to bring along their own data and research questions.Important Grading Information:If not explicitly noted otherwise, all requirements mentioned in the grading scheme must be met. If a required task is not fulfilled, this will be considered as a discontinuation of the course. In that case, the course will be graded as ‘fail’ (5), unless there is a major and unpredictable reason for not being able to fulfill the task on the student's side (e.g. a longer illness). In such a case, the student may be de-registered from the course without grading. Whether this exception applies is decided by the lecturer.If any requirement of the course has been fulfilled by fraudulent means, be it for example by cheating at an exam, plagiarizing parts of a written assignment or by faking signatures on an attendance sheet, the student's participation in the course will be discontinued, the entire course will be graded as ‘not assessed’ and will be entered into the electronic exam record as ‘fraudulently obtained’. The plagiarism-detection service (Turnitin in Moodle) can be used in course of the grading: Details will be announced by the lecturer.In case you have received three negative assessments of a continuously assessed course and want to register for a fourth attempt, please make sure to contact the StudiesServiceUnit Sociology. (for more information see "third attempt for continuously assessed courses" https://soziologie.univie.ac.at/info/pruefungen/#c56313)

### Minimum requirements and assessment criteria

There will be two homework assignments (30 % each) as well as a final assignment (30 %) that will help participants to gain further understanding and experience in interpreting binary logistic regression models. Participation will account for 10% of the grade. Attendance at all classes is compulsory, though half of one class can be missed.

### Examination topics

### Reading list

Orme, John G. and Terri Combs-Orme (2009) Multiple Regression with Discrete Dependent Variables, Oxford University Press: Oxford.Long, J. Scott (1997) Regression Models for Categorical and Limited Dependent Variables, Sage: Thousand Oaks.Long, J. Scott and Jeremy Freese (2006) Regression Models for Categorical and Dependent Variables using Stata, 2nd edition, Stata Press: College Station.Menard, Scott (2001) Applied Logistic Regression Analysis, 2nd edition, Sage: London.Pampel, Fred C. (2000) Logistic Regression: A Primer, Sage: London

## Association in the course directory

*Last modified: We 09.03.2022 11:49*

- interpret the results of logistic regression models using log odds, odds ratios and predicted probabilities,

- present these results as tables and graphs in ways suitable for general and specialist audiences,

- interpret interaction effects in the appropriate ways,

- distinguish different measures of model fit and include these in presentations of results,

- run straightforward diagnostic tests of their model,

- and use Stata to run and understand logistic regression models.