2021
Management Research
Methods 2
A SUMMARY FOR PRE-MASTER ACCOUNTANCY & CONTROL (5
EC) / VERSION 1.0
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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.â€
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
The null hypothesis (H0): The communication skills of the boss will not influence the relationship
between the commitment of the boss and employee satisfaction.
The alternative hypothesis (H2): Bosses that are more committed will increase the satisfaction level
of employees but only when they have good communication skills.
1.1.3 Mediation
Lastly, we have mediation. This has the same effect but the proposed relationship goes via another
variable. So if we have the research question: “What underlying mechanism drives the effect of boss’
commitment on employee satisfaction?†For example, quality of work environment, leads to better
employee satisfaction.
Commitment of Boss
Employee Satisfaction
Quality of the work
environment
The null hypothesis (H0): The effect of boss’ commitment on employee satisfaction is not mediated
by quality of the work environment.
The alternative hypothesis (H3): Positive effect of boss’ commitment on employee satisfaction is
mediated by quality of the work environment.
1.2
ANOVA
ANOVA, which stands for: “Analysis of Variance†is a type of analysis that is able to the test the
main effect and, if any, the moderating effect. There are some conditions that have to be met to be
able to perform a ANOVA test, which are:
• The outcome variables is a quantitative variable.
• The predicted variable(s) are categorical with more than two groups.
For example, there are math students and they are assigned into three subgroups. Each group
receives a different teaching method. You want to test which teaching method is the best and which
one is the worst. You are able to test that with the exam results. You might see one does better than
the other, while one teaching method is more spread evenly. With ANOVA you can determine exact
how much significant one does better than the other, and you are able to determine what the
differences are.
ANOVA compares the variability between the groups (Explainable) against the variability within the
groups (Not explainable). In other words: “Does it matter in which group you are, with regard to your
math score.â€
ANOVA statisically examines how much of this variability in our outcome variable can be explained by
our predictor variable. This is because ANOVA breaks down different measures of variability through
calculating the Sum of Squares (SS). Thanks to these calculations, we can test if the mean scores of
the groups are statistically different. We will be using: “One Way Between Subjects ANOVAâ€, when:
• The outcome variable is quantitative; and
• The predictor variable is categorical with more than two groups.
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