Garantie de satisfaction à 100% Disponible immédiatement après paiement En ligne et en PDF Tu n'es attaché à rien
logo-home
Full summary MMSR 2023/2024 $8.53
Ajouter au panier

Resume

Full summary MMSR 2023/2024

 7 fois vendu
  • Cours
  • Établissement
  • Book

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.

Aperçu 4 sur 45  pages

  • Oui
  • 9 janvier 2024
  • 45
  • 2023/2024
  • Resume
avatar-seller
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

Les avantages d'acheter des résumés chez Stuvia:

Qualité garantie par les avis des clients

Qualité garantie par les avis des clients

Les clients de Stuvia ont évalués plus de 700 000 résumés. C'est comme ça que vous savez que vous achetez les meilleurs documents.

L’achat facile et rapide

L’achat facile et rapide

Vous pouvez payer rapidement avec iDeal, carte de crédit ou Stuvia-crédit pour les résumés. Il n'y a pas d'adhésion nécessaire.

Focus sur l’essentiel

Focus sur l’essentiel

Vos camarades écrivent eux-mêmes les notes d’étude, c’est pourquoi les documents sont toujours fiables et à jour. Cela garantit que vous arrivez rapidement au coeur du matériel.

Foire aux questions

Qu'est-ce que j'obtiens en achetant ce document ?

Vous obtenez un PDF, disponible immédiatement après votre achat. Le document acheté est accessible à tout moment, n'importe où et indéfiniment via votre profil.

Garantie de remboursement : comment ça marche ?

Notre garantie de satisfaction garantit que vous trouverez toujours un document d'étude qui vous convient. Vous remplissez un formulaire et notre équipe du service client s'occupe du reste.

Auprès de qui est-ce que j'achète ce résumé ?

Stuvia est une place de marché. Alors, vous n'achetez donc pas ce document chez nous, mais auprès du vendeur Florine98. Stuvia facilite les paiements au vendeur.

Est-ce que j'aurai un abonnement?

Non, vous n'achetez ce résumé que pour $8.53. Vous n'êtes lié à rien après votre achat.

Peut-on faire confiance à Stuvia ?

4.6 étoiles sur Google & Trustpilot (+1000 avis)

77071 résumés ont été vendus ces 30 derniers jours

Fondée en 2010, la référence pour acheter des résumés depuis déjà 15 ans

Commencez à vendre!

Récemment vu par vous


$8.53  7x  vendu
  • (0)
Ajouter au panier
Ajouté