Statistik für Fortgeschrittene

Transcription

Statistik für Fortgeschrittene
Dr. Kateřina Schindlerová
Faculty of Psychology
University of Vienna
Multivariate Data Analysis
Wintersemester 2014-2015
K. Schindlerová
Introduction
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Vorlesungsverzeichnis
200088 VO - Statistik für Fortgeschrittene
Studienprogrammleitung Psychologie
2 Stunde(n), 5,0 ECTS credits
Kapitel: 20.01
Katerina Schindlerova
DO wtl von 09.10.2014 bis 29.01.2015 08.00-09.30
Ort: Hörsaal I NIG Erdgeschoß
K. Schindlerová
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Tutors: contacts
1
2
Title of the lecture: Advanced Statistics
Tutoring: Dr. Kateřina Schindlerová
Consultation hours: Mondays 1:00-2:00 a.m.
email: katerina.schindlerova@univie.ac.at
3
Student Assistant Sandra Peer
Consultation hours on request:
email: sandra.peer@univie.ac.at
4
Languages: German and English
5
A vocabulary of relevant English statistical terms will be
provided on-line before every lecture;
6
The final exam is planned to be in German with the optional
choice in English
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Description of the Lectures
Introduction of terms, definitions and methods, problems and
applications of multivariate data analysis.
The lectures will be given in seven modules:
1
2
3
4
5
6
7
Introduction into classification methods: cluster analysis and
discrimination analysis;
Introduction into exploratory dimensional analytical methods of
principal component analysis and factor analysis;
Regression modeling: regression of generalized linear models and
logistic regression;
Analysis of variance from the perspective of generalized linear models;
Structural equation modeling;
Log-linear modeling;
Configural frequency analysis;
The last modules will be taught depending how much time allows.
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Requirements on the Students
Presence in lectures helps the student considerably; not
everything said is in slides;
Knowledge of the definitions and methods of the intermediary
statistics as well as understanding their algebraic and statistical
elements;
Ability to select a correct method in SPSS for solution
and handling an appropriate software;
SPSS available in Rechenzentrum of University Vienna,
www.univie.ac.at/zid/software-shop;
In principle, the on-line lectures cover the required knowledge
to the final exam;
The expected duration of the final exam: 60 to 90 minutes
The concrete form of the exam will be announced in the last lecture
of the semester
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Literature
There is no one-volume textbook which would cover all methods
discussed in this course;
These two-volume book covers all methods except structural equation
modeling and configural frequency analysis:
Jobson, J.D. (1991). Applied multivariate data analysis. Volume I:
Regression and experimental design. New York: Springer.
Jobson, J.D. (1992) Applied multivariate data analysis. Volume II:
Categorical and multivariate data methods. New York: Springer.
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Literature
The following text is for advanced, statistically interested readers:
it treats modeling out of the perspective of the general linear models:
Fahrmeir, L., Tutz, G. (2001). Multivariate statistical modelling
based on generalized linear models, 2nd ed. New York:
Springer.
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Literature
Both the following texts are easier to read.
However, configural freuquency analysis, structural equation models
and general linear models are not discussed:
Bartholomew, D.J., Steele, F., Moustaki, I, Galbraith, J.I. (2002).
The analysis and interpretation of multivariate data for social
scientists. Boca Raton: Chapman and Hall.
Raykov, T., Marcoulides, G. (2008). An introduction to applied
multivariate analysis. New York, NY: Taylor and Francis.
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Literature
The following text is recommended for general linear models:
Kutner, M.H., Nachtsheim, C.J., Neter, J. Li, W. (2005).
Applied linear statistical models, 5th ed., Boston,
MA. McGraw Hill.
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Literature
Both the following books offer an introduction into structural equation
models:
Kline, R.B. (2011). Principles and and practice of structural equation
modeling, 3rd ed. New York: The Guilford Press.
Raykov, T., Marcoulides, G.A. (2006). A first course in structural
equation modeling, 2n d ed. Mahwah, NJ: Erlbaum.
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Literature
The following text can be applied to explain the LISREL applications
more in detail:
Jöreskog, K.G., Sörbom, D. (2004). LISREL 8.7 for Windows.
Lincolnwood, IL: Scientific Software International.
An instructive introduction into in LISREL and SEM can be
downloaded for free under:
http://www.ssicentral.com/
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Literature
The description of structural equation models for special application can
be found in:
Pugesek, B., Tomer, A., von Eye, A., (Eds.)(2003). Structural
equation modeling. Applications in Ecological and Evolutionary
Biology. Cambridge, UK: Cambridge University Press.
Von Eye, A., Clogg, C. (Eds.)(1994). Latent variables analysis Applications for developmental research. Newbury Park, CA:
Sage.
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Literature
An introduction into cluster analysis can be found in:
Everitt, B.S., Landau, S., Leese, M. (2001). Cluster analysis.
4th ed. New York: Oxford University Press.
Z. Huang. Extensions to the k-means algorithm for clustering large
data sets with categorical values”. Data Mining and Knowledge
Discovery, 2:283304, 1998.
The following is a classics in area of categorical data analysis:
Agresti, A. (2013). Categorical data analysis, 3th ed. New York,
Wiley.
The following book gives an introduction into log-linear models:
von Eye, A., Mun, E.-Y. (2013). Log -linear modeling Concepts, interpretation and applications. New York: Wiley.
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Literature
The following two books deal with configural freuquency analysis:
von Eye, A. (2002). Configural Freuquency Analysis - Methods,
Models, and Approximations, Mahwab, NJ: Lawrence Erlbaum.
von Eye, A., Mair. P., Mun, E.-Y. (2010). Advances in Configural
Freuquency Analysis, new York: Guilford Press.
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Organisation of the Course and Grading
Organisation of the Course:
The course consists of lectures, in which methods of multivariate
data analysis will be explained theoretically and in concrete
applications and examples. Recommendation to reading as well
as voluntary homework will be given.
The topics as well as the order of the lectures can change.
Grading:
In the last meeting in semester the written final exam will take
place. Its results are the basis for the grade of the course. Other
dates for exams will be given in the following semester.
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List of topics - Themenliste
Modul
I
II
III
IV
V
VI
VII
List of topics - Themenliste
Topic
Literature
classification methods
Jobson, 1992 for discrimination
analysis; Everitt et al. (2001)
for cluster analysis
dimensional methods
Jobson, 1992
regression
Jobson, 1991; Neter et al.,
2005; Agresti, 2013; von Eye
and Mun, 2013
ANOVA
Jobson, 1991; Neter et al.,
2005
SEM
Kline, 2011
Log-linear models
Agresti, 2013; von Eye and
Mun, 2013
CFA
von Eye, 2002; von Eye et al.,
2010
K. Schindlerová
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Statistik für Fortgeschrittene

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