Summary

Full summary MMSR 2023/2024

7 purchases

Course
Methodology Marketing and Strategic Management

Institution
Radboud Universiteit Nijmegen (RU)

Book
Multivariate Data Analysis

This document is a full summary for the exam Methodology in Marketing and Strategic Management Research (MMSR) at Radboud University. I made this summary from lectures + video clips + article by Henseler + book by Hair. The summary is made in study year 2023/2024.

[Show more]

Preview 4 out of 45 pages

View example

Summarized whole book? Yes
Uploaded on January 9, 2024
Number of pages 45
Written in 2023/2024
Type Summary

statistic
mmsr
marketing
strategic management
business administration
factor analysis
anovaancova
regression analysis
pls sem
methodology in marketing and strategic management
summary

Book Title:Multivariate Data Analysis

Author(s):Joseph F. Hair, William C. Black

Edition:Unknown
ISBN:9780135153093
Edition:7

Institution
Radboud Universiteit Nijmegen (RU)
Education
Business Administration
Course
Methodology Marketing and Strategic Management

Florine98

Member since 7 year 58 documents sold

$8.28

Add to cart

Save

100% satisfaction guarantee
Immediately available after payment
Both online and in PDF
No strings attached

Summary MMSR 2023/2024

Introduction.................................................................................................................................................. 2
Lecture 1 – introduction.......................................................................................................................................2
Overview of multivariate methods.......................................................................................................................4
Examining the data..............................................................................................................................................6
..............................................................................................................................................................................9

Factor analysis............................................................................................................................................. 10
Introduction........................................................................................................................................................10
Exploratory factor analysis.................................................................................................................................11
Confirmatory factor analysis..............................................................................................................................16

Ancova........................................................................................................................................................ 18
Introduction........................................................................................................................................................18
Statistics in An(c)ova..........................................................................................................................................18
Assumptions of Anova........................................................................................................................................19
Interpretation of Anova......................................................................................................................................20
One-way Anova..................................................................................................................................................21
N-way Anova......................................................................................................................................................23
Ancova................................................................................................................................................................25
Repeated-measures anova.................................................................................................................................26
Man(c)ova..........................................................................................................................................................27

Regression analysis...................................................................................................................................... 29
Introduction........................................................................................................................................................29
Multiple regression analysis...............................................................................................................................31
Moderator..........................................................................................................................................................36
Logistic regression..............................................................................................................................................37

PLS-SEM....................................................................................................................................................... 39
Introduction........................................................................................................................................................39
Moderation/mediation......................................................................................................................................40
PLS-SEM..............................................................................................................................................................41

1

, Introduction
Lecture 1 – introduction

Definitions
Hypothesis consists of two parts: the independent variable (condition) that is not influenced by
anything else within the model, and the dependent variable (consequence) that is always
impacted by at least one other variable in the model.

Construct = phenomenon of theoretical interest. Needs to be defined in terms of their object
(what are we measuring), attribute level and the unit of analysis.

Theories = consist of several constructs.

Latent = indirectly observable construct. Examples: beliefs, intention, motivation.

Relationships between constructs
Direct causal relationship = A  B
Can be linear  one goes up, the other goes up.
Can be non-linear  one goes up, the other goes down.
A = exogenous variable = independent variable.
B = endogenous variable = dependent variable.

Mediated causal relationship = A  Z  B
Z is the mediator, A influences B through Z.
Full mediation = effect of A on B is completely absorbed by Z.
Partial mediation = effect of A on B is only partly absorbed by Z.
A = exogenous variable = independent variable
B and Z = endogenous variable = dependent variable.

Moderated causal relationship.
Strength/direction of A on B depends on moderator M.

M

A B
A
Spurious relationship
Z influences A and B. Z
B
Bidirectional causal relationship
AB
AB
A leads to B, and B leads to A. Not necessarily at the same time. Often cross sectional data,
difficult from data point of view.

2

,Unanalyzed relationship
There is a correlation between A and B, but it’s not part of your model so you don’t analyze it.

Two-language concept
Language 1: theoretical language, translates in theoretical variables. Denoted with Greek letters.
Language 2: observational language, translates in observable variables. Denoted with our
alphabet.
The correspondence rules are how is corresponded between the languages.

Definition in model:
- Squares = indicators
- Circles/ovals = latent variables
- Small circle with e = (structural) error
term

Measurement model = how good do the
measures perform to predict the latent
construct.

Structural model = relationship of the
path between the constructs.

3

, Reflective versus formative measurement

Reflective (latent) = causality is from construct to the indicator
(measure). The construct is reflected by the measurement.
The indicators are expected to be correlated, and dropping one
indicator doesn’t alter the meaning of the construct.
Measurement error is taken into account at the item level.
This is similar to factor analysis.
Example: consumer research.

Formative (emerging) = causality is from indicator (measure) to the
construct. The indicators aren’t expected to be correlated. Dropping
one indicator can alter the meaning of the construct.

Within this course we mostly use
reflective measurement models, the
validity of the items is then usually
tested with a factor analysis.

Overview of multivariate methods
Multivariate analysis = all statistical techniques that simultaneously analyze multiple
measurements on individuals or objects under investigation.

Basic concepts
Variate = linear combination of variables with empirically determined weights, the building block
of multivariate analysis.

4

The benefits of buying summaries with Stuvia:

Guaranteed quality through customer reviews

Stuvia customers have reviewed more than 700,000 summaries. This how you know that you are buying the best documents.

Quick and easy check-out

You can quickly pay through credit card or Stuvia-credit for the summaries. There is no membership needed.

Focus on what matters

Your fellow students write the study notes themselves, which is why the documents are always reliable and up-to-date. This ensures you quickly get to the core!

Frequently asked questions

What do I get when I buy this document?

You get a PDF, available immediately after your purchase. The purchased document is accessible anytime, anywhere and indefinitely through your profile.

Satisfaction guarantee: how does it work?

Our satisfaction guarantee ensures that you always find a study document that suits you well. You fill out a form, and our customer service team takes care of the rest.

Who am I buying these notes from?

Stuvia is a marketplace, so you are not buying this document from us, but from seller Florine98. Stuvia facilitates payment to the seller.

Will I be stuck with a subscription?

No, you only buy these notes for $8.28. You're not tied to anything after your purchase.

Can Stuvia be trusted?

4.6 stars on Google & Trustpilot (+1000 reviews)

72997 documents were sold in the last 30 days

Founded in 2010, the go-to place to buy study notes for 15 years now

Start selling

Summary

Full summary MMSR 2023/2024

Document information

Subjects

Connected book

Written for

Seller

Reviews received

Content preview