Class notes
Lectures with notes Organization Research Methods
- Course
- Institution
Lectures with notes, including syntax for running different models.
[Show more]
Seller
Follow
demivandepol
Reviews received
Content preview
Lecture 1 – MediationMediation: testing theoretical mechanisms at micro-level (for example: team level)
Moderation: allows to test for changes in two variables as the level of moderator changes, can
flip the sign from positive to negative and vice versa
Conditional process models: models that combine mediation and moderation
What is a mediating variable?
• A mediating variable is one that will change as a result of the influence of the IV (X),
and then will, in turn, cause a change in the DV (Y)
• Therefore, a variable like gender would not be a good candidate to be a mediating
variable
• How about team conflict? (one of the best mediators)
• The mediator has to change as a consequence of change in your IV (X). Hence, some
variables (e.g. personality traits, gender), may/are not good candidates for mediation
variables
So what is the goal of mediation?
• To examine the magnitude and valence of the mechanisms underlying an explanatory
variable (IV) and an outcome variable (DV)
• Provides you with a comparative assessment of the different mechanisms influencing
the outcome variable (DV)
• Basically, it answers the questions “how” does our IV impact your DV?
What is the difference between a theoretical mechanism and a mediator?
• Theoretical mechanism: the argument that connects your variables to each other in
theory and every theoretical mechanism has the potential to become a mediator
(unmeasured mediators)
• Mediator: is a causal argument (Hayes, 2018 argues that you can still run these models
without being able to make 100% causal claims)
• Minimum of three variables X, med
Main assumption: linear relationships between variables (straight line/red line)
Mediator formula includes E = error term → difference between the linear
regression line and the actual data point (black line)
i = intercept
a = slope → one unit change in X, is going to yield 2 unit change in M
The same logic applies to Y formula with the c’X (direct) and bM
(mediator)
,What are the different effect?
• Direct effect = c’ → the effect of your X variable on your Y variables which is not
mediated
• Indirect effect = a*b → the product of your coefficient of your first product and
multiply a by b which is your second coefficient of M, effect of X on Y mediated
through M (indirect effect is also known as the mediated effect)
• Total effect = direct + indirect effect (c’ + a*b)
X = power hierarchy; Y = Team performance; M = Team conflict
Which one is a better hypothesis and why?
• The second one is best, because the second one specified each leg of the mediation.
The first hypothesis did not specify each leg. (logic: if it is not specified it could be
that either a or b is negative, you don’t know which one which is problematic for your
conceptual understanding)
• Most papers already avoid/solve this problem by hypothesizing each leg beforehand
(so in this case, this would mean 3 hypotheses and the final hypothesis is mediation)
,What is missing here?
You need to test for significance, -.33 did not tell you whether the indirect effect is significant
or not.
Logic behind significance testing
Sampling distribution: if we repeatedly sample and the 0 is
not included in 95% than it is statistically significant
Is the indirect effect statistically significant?
• Baron and Kenny (1986) suggested that one could use the Sobel formula to calculate
whether the size of the indirect effect was sufficiently strong to be considered
“statistically significant”.
• Note that the Sobel’s formula is based on multiplying the unstandardized regression
coefficients and standard errors of the a and b pathways.
Testing the indirect effect
Problem
• We are testing the significance of a*b
• To use the Sobel test we need to assume that a*b is normally distributed (and CIs are
symmetric)
• Even if we assume that a and b are each normally distributed, their product will not be
normal
Solution
• We need methods of testing a*b that do not assume normality!
• Bootstrapping → simulation (allow us to simulate what the estimate of sample
distribution is)
Note: when referring to the distributions of a and b, we are talking about coefficients,
not variables
Hypothesis Testing with CIs
• When testing the significance of a*b with bootstrapping etc. we use a CI (confidence
interval) to test our null hypothesis.
• H0: a*b = 0
• If a*b is significant we say there is a less than 5% chance that a*b = 0 in the
population
• A 95% CI provides the same information
• If 0 is not within the 95% CI: In 95% of samples of size n a*b ≠ 0. Significant
mediation effect.
• If 0 is within the 95% CI: : In less than 95% of samples of size n a*b ≠ 0. Non-
significant mediation effect.
, Bootstrapping
• Steps for bootstrapping
1. Draw a sample from the data of size n with replacement
2. Fit your model(s) to this data (e.g., estimate both a and b in two regressions)
3. Save the parameter estimates from Step 2
4. Repeat Steps 1-3 1000s of times
5. The parameter estimates from Step 2 form a distribution for each parameter estimate
6. The 2.5th and 97.5th percentiles of the distribution form the 95% CI
! Bootstrap can pick same teams, because it puts all samples back every time (simple sample).
This is not a problem, because teams are interchangeable. (One team represents all the teams
that are similar to that team, so it does not matter if you pick the same ‘type’ of team twice)
! based on the sample the simulation will create its own equation → normally distribution
does not work very well (model becomes bit asymmetric)
- Plug-in SPSS of Andrew & Hayes to calculate bootstrap
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 demivandepol. Stuvia facilitates payment to the seller.
Will I be stuck with a subscription?
No, you only buy these notes for $13.24. You're not tied to anything after your purchase.
Can Stuvia be trusted?
4.6 stars on Google & Trustpilot (+1000 reviews)
77254 documents were sold in the last 30 days
Founded in 2010, the go-to place to buy study notes for 14 years now