2021
Management Research
Methods 2
A SUMMARY FOR PRE-MASTER ACCOUNTANCY & CONTROL (5
EC) / VERSION 1.0
, 1
Index
Chapter 1. Introduction to ANOVA ........................................................................................................ 3
1.1 Conceptual models. ................................................................................................................ 3
1.1.1 Measurement scales ....................................................................................................... 3
1.1.2 Moderation ..................................................................................................................... 3
1.1.3 Mediation ........................................................................................................................ 4
1.2 ANOVA .................................................................................................................................... 4
1.2.1 ANOVA: Assumptions ..................................................................................................... 5
1.2.2 ANOVA: Steps ................................................................................................................. 5
1.2.3 ANOVA: Calculations ...................................................................................................... 5
1.2.4 ANOVA: F-test and R^2 ................................................................................................... 7
1.3 Conclusion ............................................................................................................................... 8
Chapter 2. Factorial ANOVA ................................................................................................................... 9
2.1 Conceptual Model (with Moderation) ................................................................................... 9
2.1.1 Example 1 ........................................................................................................................ 9
2.2 Factorial ANOVA: Calculations ............................................................................................. 10
2.2.1 Factorial ANOVA: example 1 ........................................................................................ 10
Chapter 3. Regression ........................................................................................................................... 15
3.1 Concept of regression ........................................................................................................... 15
3.2 Visualization of explained and unexplained variances ....................................................... 15
3.3 Goodness-of-fit of a model and Steps.................................................................................. 16
3.4 Regression: Model fit and testing ........................................................................................ 16
3.4.1 Model fit: 𝑹𝟐................................................................................................................. 16
3.4.2 Model testing: F-ratio ................................................................................................... 17
3.4.3 Regression Example ...................................................................................................... 17
3.5 Coefficient Testing ................................................................................................................ 18
3.5.1 Example ......................................................................................................................... 19
3.5.2 Follow up example........................................................................................................ 19
3.6 Managerial implications ....................................................................................................... 21
3.6.1 How the results of a regression model can help a manager ....................................... 21
3.6.2 Which factors should the manager focus on to influence the OV? ............................ 22
Chapter 4. Regression with categorical predictor variables ............................................................... 23
4.1 Basic Regression → Advanced Regression .......................................................................... 23
4.1.1 Example ......................................................................................................................... 23
4.2 Multicollinearity ................................................................................................................... 25
4.3 Regression: Concept of Mediation. ...................................................................................... 25
, 2
Chapter 5. Logistic Regression.............................................................................................................. 26
5.1 Logistic Regression ................................................................................................................ 26
5.1.1 Steps .............................................................................................................................. 26
5.1.2 Model Testing: Chi Square Test .................................................................................... 26
5.1.3 Model Fit: Pseudo R2 .................................................................................................... 26
5.1.4 Model Fit: Hit Rate ........................................................................................................ 26
5.2 Managerial Implications ....................................................................................................... 28
Chapter 6. Factor analysis: Concept ..................................................................................................... 30
6.1 Factor Analysis ...................................................................................................................... 30
6.2 PCA: Initial Checks ................................................................................................................ 31
6.3 Main Analysis ........................................................................................................................ 33
6.3.1 Main analysis – Component interpretation ................................................................. 34
6.3.2 Main analysis – Comparing component solutions:...................................................... 34
6.3.3 Label the components .................................................................................................. 35
, 3
Chapter 1. Introduction to ANOVA
Welcome to Management Research Methods 2, a follow-up course on Management Research
Methods 1.
1.1 Conceptual models.
Conceptual models visualizing your research question and gives a schematic overview of your
research. This is in fact the beginning of your hypothesis and even helps with creating your research
question. Furthermore it helps with what type of analysis is suitable. This means a conceptual model
is a visual representation between theoretical constructs (The variables) of interests (Also:
visualizes the research question). By model we define it as a simplified description of reality, for
example: Predictor variable (PV) to Outcome variable (OV). This means the PV has effect on the OV.
1.1.1 Measurement scales
Variables have different measurement scales. We have categorical (Nominal and Ordinal), where
subgroups are indicated by numbers or names. The other measurement scale is the quantitative
scale, these are numerical scales, with equal distances between values (Note that we in social
sciences sometimes treat ordinal scales as (pseudo-) interval scales, like Likert Scales. Likert Scale are
most often recognized by ( 1 = Definitely not agree, 2, 3, 4 and 5 = Definitely agree).
Example
Imagine: “Currently, we are doing a research and we are talking about conceptual models.
Furthermore we are talking about cause and effect. Lets say there is a boss and he/she is very boring
and not inspiring to his employees, which causes the employee to be demotivated and not willing to
do more for the company.”
Here the research question would be: “What factors determine employee satisfaction?” Employee
satisfaction is in this case the OV.
Commitment of the boss Employee Satisfaction
The null hypothesis (H0): Commitment of the boss has no effect on employee satisfaction.
The Alternative Hypothesis (Ha/H1): The more commitment from a boss, the higher level of
employee satisfaction.
1.1.2 Moderation
There are different kinds of conceptual models. First, Moderation. This means we have the main
effect, but the proposed effect is stronger in some occasions. For example, like: What is the effect of
boss commitment on employee satisfaction, and how is this relationship moderated by a boss’
communication skills? This means the communication skill is a moderator, which means a boss can
be committed but if he can’t communicate it won’t lead to a better employee satisfaction. When a
boss has both, it will lead to a better employee satisfaction.
Commitment of Boss Employee Satisfaction
Management Research
Methods 2
A SUMMARY FOR PRE-MASTER ACCOUNTANCY & CONTROL (5
EC) / VERSION 1.0
, 1
Index
Chapter 1. Introduction to ANOVA ........................................................................................................ 3
1.1 Conceptual models. ................................................................................................................ 3
1.1.1 Measurement scales ....................................................................................................... 3
1.1.2 Moderation ..................................................................................................................... 3
1.1.3 Mediation ........................................................................................................................ 4
1.2 ANOVA .................................................................................................................................... 4
1.2.1 ANOVA: Assumptions ..................................................................................................... 5
1.2.2 ANOVA: Steps ................................................................................................................. 5
1.2.3 ANOVA: Calculations ...................................................................................................... 5
1.2.4 ANOVA: F-test and R^2 ................................................................................................... 7
1.3 Conclusion ............................................................................................................................... 8
Chapter 2. Factorial ANOVA ................................................................................................................... 9
2.1 Conceptual Model (with Moderation) ................................................................................... 9
2.1.1 Example 1 ........................................................................................................................ 9
2.2 Factorial ANOVA: Calculations ............................................................................................. 10
2.2.1 Factorial ANOVA: example 1 ........................................................................................ 10
Chapter 3. Regression ........................................................................................................................... 15
3.1 Concept of regression ........................................................................................................... 15
3.2 Visualization of explained and unexplained variances ....................................................... 15
3.3 Goodness-of-fit of a model and Steps.................................................................................. 16
3.4 Regression: Model fit and testing ........................................................................................ 16
3.4.1 Model fit: 𝑹𝟐................................................................................................................. 16
3.4.2 Model testing: F-ratio ................................................................................................... 17
3.4.3 Regression Example ...................................................................................................... 17
3.5 Coefficient Testing ................................................................................................................ 18
3.5.1 Example ......................................................................................................................... 19
3.5.2 Follow up example........................................................................................................ 19
3.6 Managerial implications ....................................................................................................... 21
3.6.1 How the results of a regression model can help a manager ....................................... 21
3.6.2 Which factors should the manager focus on to influence the OV? ............................ 22
Chapter 4. Regression with categorical predictor variables ............................................................... 23
4.1 Basic Regression → Advanced Regression .......................................................................... 23
4.1.1 Example ......................................................................................................................... 23
4.2 Multicollinearity ................................................................................................................... 25
4.3 Regression: Concept of Mediation. ...................................................................................... 25
, 2
Chapter 5. Logistic Regression.............................................................................................................. 26
5.1 Logistic Regression ................................................................................................................ 26
5.1.1 Steps .............................................................................................................................. 26
5.1.2 Model Testing: Chi Square Test .................................................................................... 26
5.1.3 Model Fit: Pseudo R2 .................................................................................................... 26
5.1.4 Model Fit: Hit Rate ........................................................................................................ 26
5.2 Managerial Implications ....................................................................................................... 28
Chapter 6. Factor analysis: Concept ..................................................................................................... 30
6.1 Factor Analysis ...................................................................................................................... 30
6.2 PCA: Initial Checks ................................................................................................................ 31
6.3 Main Analysis ........................................................................................................................ 33
6.3.1 Main analysis – Component interpretation ................................................................. 34
6.3.2 Main analysis – Comparing component solutions:...................................................... 34
6.3.3 Label the components .................................................................................................. 35
, 3
Chapter 1. Introduction to ANOVA
Welcome to Management Research Methods 2, a follow-up course on Management Research
Methods 1.
1.1 Conceptual models.
Conceptual models visualizing your research question and gives a schematic overview of your
research. This is in fact the beginning of your hypothesis and even helps with creating your research
question. Furthermore it helps with what type of analysis is suitable. This means a conceptual model
is a visual representation between theoretical constructs (The variables) of interests (Also:
visualizes the research question). By model we define it as a simplified description of reality, for
example: Predictor variable (PV) to Outcome variable (OV). This means the PV has effect on the OV.
1.1.1 Measurement scales
Variables have different measurement scales. We have categorical (Nominal and Ordinal), where
subgroups are indicated by numbers or names. The other measurement scale is the quantitative
scale, these are numerical scales, with equal distances between values (Note that we in social
sciences sometimes treat ordinal scales as (pseudo-) interval scales, like Likert Scales. Likert Scale are
most often recognized by ( 1 = Definitely not agree, 2, 3, 4 and 5 = Definitely agree).
Example
Imagine: “Currently, we are doing a research and we are talking about conceptual models.
Furthermore we are talking about cause and effect. Lets say there is a boss and he/she is very boring
and not inspiring to his employees, which causes the employee to be demotivated and not willing to
do more for the company.”
Here the research question would be: “What factors determine employee satisfaction?” Employee
satisfaction is in this case the OV.
Commitment of the boss Employee Satisfaction
The null hypothesis (H0): Commitment of the boss has no effect on employee satisfaction.
The Alternative Hypothesis (Ha/H1): The more commitment from a boss, the higher level of
employee satisfaction.
1.1.2 Moderation
There are different kinds of conceptual models. First, Moderation. This means we have the main
effect, but the proposed effect is stronger in some occasions. For example, like: What is the effect of
boss commitment on employee satisfaction, and how is this relationship moderated by a boss’
communication skills? This means the communication skill is a moderator, which means a boss can
be committed but if he can’t communicate it won’t lead to a better employee satisfaction. When a
boss has both, it will lead to a better employee satisfaction.
Commitment of Boss Employee Satisfaction
