Question 1

How can we calculate how much of the variation in Y is situated at each level?

Accepted Answer

A)  By dividing the log likelihood on the number of units in the respective levels 
B)  By running your full model and then calculating the intraclass correlation coefficient 
C)  By dividing the level-1 residual on each of the higher-level residuals 
D)  By running an empty model and then calculating the intraclass correlation coefficient 
A)  By dividing the log likelihood on the number of units in the respective levels 
B)  By running your full model and then calculating the intraclass correlation coefficient 
C)  By dividing the level-1 residual on each of the higher-level residuals 
D)  By running an empty model and then calculating the intraclass correlation coefficient D

Question 2

What is a cross-level interaction term?

Accepted Answer

A)  A variable made by multiplying two variables situated at level-1 
B)  A variable made by multiplying two variables situated at level-2 
C)  A variable made up by log transforming any X-variable 
D)  A variable made by multiplying two variables situated at different levels 
A)  A variable made by multiplying two variables situated at level-1 
B)  A variable made by multiplying two variables situated at level-2 
C)  A variable made up by log transforming any X-variable 
D)  A variable made by multiplying two variables situated at different levels D

Question 3

How many identifier variables are required to run a three-level model?

Accepted Answer

A)  1 
B)  2 
C)  3 
D)  4 
A)  1 
B)  2 
C)  3 
D)  4 B

Question 4

What is a level?

Accepted Answer

A)  A level is a given variable chosen from your theoretical approach 
B)  A level is a variable that identifies units sampled from a population 
C)  A level can be any categorical variable in your dataset 
D)  A level can be any continuous variable in your dataset 
A)  A level is a given variable chosen from your theoretical approach 
B)  A level is a variable that identifies units sampled from a population 
C)  A level can be any categorical variable in your dataset 
D)  A level can be any continuous variable in your dataset

Question 5

Which of the following are advantages of multilevel modelling?

Accepted Answer

A)  It is the statistical method that comes closest to experiments in establishing causality 
B)  It takes into account the problem of dependency among observations 
C)  It allows us to model the influence of variables from all levels on our Y 
D)  It allows us to model risk development over time of an event taking place 
A)  It is the statistical method that comes closest to experiments in establishing causality 
B)  It takes into account the problem of dependency among observations 
C)  It allows us to model the influence of variables from all levels on our Y 
D)  It allows us to model risk development over time of an event taking place

Question 6

How many levels is it possible to model through multilevel modelling?

Accepted Answer

A)  1 
B)  2 
C)  3 
D)  There is no theoretical limit 
A)  1 
B)  2 
C)  3 
D)  There is no theoretical limit

Question 7

What is the basic assumption of multilevel modelling?

Accepted Answer

A)  The dependent variable is continuous 
B)  The expected value of Y can be modelled by a combination of unknown parameters 
C)  The units of analysis are measured over time 
D)  A unit at the lowest level is nested into a higher level of unit(s) 
A)  The dependent variable is continuous 
B)  The expected value of Y can be modelled by a combination of unknown parameters 
C)  The units of analysis are measured over time 
D)  A unit at the lowest level is nested into a higher level of unit(s)

Question 8

When is it appropriate to use a cross-classified multilevel model?

Accepted Answer

A)  When it is unclear which level-1 units belong to the different higher-level units 
B)  When level-1 units can be members of more than one higher-level unit at the same time 
C)  When the level-1 units can only be nested into level-3 units 
D)  If your regular model fails to converge 
A)  When it is unclear which level-1 units belong to the different higher-level units 
B)  When level-1 units can be members of more than one higher-level unit at the same time 
C)  When the level-1 units can only be nested into level-3 units 
D)  If your regular model fails to converge

Question 9

What is a random coefficient (slope) model?

Accepted Answer

A)  A multilevel model that allows both the intercept and coefficient(s) to vary 
B)  A multilevel model that allows the intercept to vary 
C)  A multilevel model with a fixed intercept and fixed coefficients 
D)  A multilevel model with statistical interaction 
A)  A multilevel model that allows both the intercept and coefficient(s) to vary 
B)  A multilevel model that allows the intercept to vary 
C)  A multilevel model with a fixed intercept and fixed coefficients 
D)  A multilevel model with statistical interaction

How can we calculate how much of the variation in Y is situated at each level?

What is a cross-level interaction term?

How many identifier variables are required to run a three-level model?

What is a level?

Which of the following are advantages of multilevel modelling?

How many levels is it possible to model through multilevel modelling?

What is the basic assumption of multilevel modelling?

When is it appropriate to use a cross-classified multilevel model?

What is a random coefficient (slope) model?

Research and Statistics

Introduction to STATA

Simple Bivariate Regression

Multiple Regression

Dummy-Variable Regression

Interaction/Moderation Effects Using Regression

Linear Regression Assumptions and Diagnostics

Logistic Regression

Survival Analysis

Panel Data Analysis

Time-Series Analysis

Exploratory Factor Analysis

Structural Equation Modelling and Confirmatory Factor Analysis

Advanced Statistical Techniques

Programming and Dynamic Reporting Using STATA

Filters

Exam 10: Multilevel Analysis

How can we calculate how much of the variation in Y is situated at each level?

What is a cross-level interaction term?

How many identifier variables are required to run a three-level model?

What is a level?

Which of the following are advantages of multilevel modelling?

How many levels is it possible to model through multilevel modelling?

What is the basic assumption of multilevel modelling?

When is it appropriate to use a cross-classified multilevel model?

What is a random coefficient (slope) model?

Research and Statistics

Introduction to STATA

Simple Bivariate Regression

Multiple Regression

Dummy-Variable Regression

Interaction/Moderation Effects Using Regression

Linear Regression Assumptions and Diagnostics

Logistic Regression

Survival Analysis

Panel Data Analysis

Time-Series Analysis

Exploratory Factor Analysis

Structural Equation Modelling and Confirmatory Factor Analysis

Advanced Statistical Techniques

Programming and Dynamic Reporting Using STATA

Filters