Course
Multivariate analysis: applied factor and regression analysis (PHD104)
The aim of this course is to provide students with a good understanding of basic analytical tools with relevance for their Phd-work. Factor- and regression analysis are the main approaches covered, for the most part using the statistical program SPSS. When discussing mediation and moderation, the students will be introduced to Hayes' Process on top of SPSS. In addition, we will go into Confirmatory Factor analysis (CFA) and Structural Equation Modelling (SEM) via the Lisrel program, also with eye on the Mplus package. The course will also take up elements of logistic regression and multi-level analysis. Main focus will be on applications of the various techniques introduced.
Dette er emnebeskrivelsen for studieåret 2018-2019. Merk at det kan komme endringer.
Semesters
Fakta
Emnekode
PHD104
Vekting (stp)
5
Semester undervisningsstart
Spring
Undervisningsspråk
English
Antall semestre
1
Vurderingssemester
Spring
Content
Learning outcome
Knowledge
The Phd-students/participants should have a general knowledge about Causal models and principles of Causal inference. The logic and results of Factor analysis and evaluation alternative factor models are central. Moreover, the student should have knowledge of Multivariate Regression analysis, specification of hypotheses and statistical inference, as well as combined uses of regression- and factor analysis. Participants should also know how to test for indirect and/or moderation effects, and how to make use of dummy-variable and interaction terms in more complex models. The students should become acquainted with how to set up a CFA model and a SEM model in Lisrel (or similar packages).
Skills.
It is central to this course that the student can/should dig into a scientific problem/question at the international research frontier and analyze available data in a proficient manner, preferably with her own project as background. The student must also be competent in clarifying main assumptions of alternative analytical/statistical approaches, and to apply quantitative methods in a real research setting. Participants should have the skills needed to plan, evaluate, facilitate and carry out empirical/statistical studies with a multivariate framework, that could make up the basis for a publication at international level.
General competence
The student should be able to "translate" a research question into more precise hypotheses that could effectively be tested by the factor- or regression model, or more advanced approaches (CFA/SEM). It is central that the participant understands the results coming out from such analyses, and can provide meaningful interpretations of these, in addition to conveying such findings and conclusions to research colleagues at the national or international level.
Forkunnskapskrav
Anbefalte forkunnskaper
Exam
| Form of assessment | Weight | Duration | Marks | Aid | Exam system | Withdrawal deadline | Exam date |
|---|---|---|---|---|---|---|---|
| Paper (6-10 pages) | 1/1 | Passed / Not Passed | — | — | — |
Full participation during the whole course is required.
(One week on intensive lectures and PC-lab exercises, Monday through Friday, 9 -16).
In addition, there is a term paper requirement ( 8-10 pages, demonstrating knowledge and application skills)
Fagperson(er)
Course coordinator:
Espen OlsenCourse teacher:
Espen OlsenMethod of work
The course will consist of one week of intensive lectures and PC-lab exercises, Monday through Friday, from 0915 to 1600. Students are expected to prepare for and review lecture materials on their own.
The expected work loads of this course are:
Lectures: 15 hours
Computer Lab sessions: 20 hours
Preparations and reviews of materials: 65 hours
Paper requirement: 50 hours
TOTAL: 150 hours
Åpent for
Emneevaluering
Litteratur
Information about the literature/reading list will be provided the semester before the course is held.
THIS IS THE TENTATIVE READING LIST AS OF OCTOBER 2017.THE READING LIST COULD BE REVISED AT A LATER STAGE.
THE TENTATIVE READING LIST is made up of classical works in the applied methods literature:
Basic Factor Analysis
Pett, Marjorie, A., Nancy R. Lackey, og John. J. Sullivan, Making Sense of Factor Analysis. Thousand Oaks, CA: Sage 2003. Please read chapters 1 - 7 (225 pages).
Basic Regression, plus Dummy-variable, Interaction effects, Logistic Regression
From Sages "Series" (a-c): a) Michael S Lewis-Beck, Applied Regression, An Introduction. Second edition. Volume:22. 2016. (This is mainly a reprint of previous versions)
b) Melissa A Hardy, Regression with Dummy Variables Volume: 93 1993.
c) James Jaccard, Robert Turrisi and Choi K Wan, Interaction Effects in Multiple Regression Volume:72 1990.
d) Scott Menard , Applied Logistic Regression Analysis Volume:106 1995
CFA/SEM/Lisrel
Byrne, Barbara M., Structural Equation Modeling with Lisrel, Prelis and Simplis. Basic Concepts, Applications and Programming London: Lawrence Erlbaum Associates 1998. Should be available in paper back.
Please read chapters 1,2,4,7,8, (excluding SIMPLIS and PRELIS parts) approximately 150 pages.
Article :
Knudsen, Knud (2009) "Striking a different balance; Work-family conflict for female and male managers in a Scandinavian context". Gender in Management 24 4: 252 - 269. A copy will be made available at the start of the course.
Participants who may want a supplementary text in Norwegian, covering the main regression topics, could also read: Ole-Jørgen Skog, Å forklare sosiale fenomener. Ad Notam 2004 .