Network Analysis: Lecture 1. Sacha Epskamp

(1)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Teaching Staff Schedule General information R

Why networks?

Seven Bridges of Königsberg Networks in Psychology

Network basics

Building blocks of a network Different kinds of networks Encoding a network

Network dynamics

Social networks Psychopathology as a complex system Comorbidity

References

Introduction to Network Analysis

Network Analysis: Lecture 1

Sacha Epskamp

University of Amsterdam

Department of Psychological Methods

(2)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

I

Who are you?

I

What is your specialization?

I

Why are you here?

I

Are you familiar with the network perspective?

(3)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Sacha Epskamp

Denny Borsboom

Claudia van Borkulo

Jolanda Kossakowski

(4)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Date

Subject

Lecturer

Start

Due

Tu 02/09

Introduction

Sacha Epskamp

Th 04/09

Intro to R

Sacha Epskamp

Assignment 1

Tu 09/09

Correlational structures

Sacha Epskamp

Th 11/09

qgraph workshop

Sacha Epskamp

Assignment 2

Assignment 1

Tu 16/09

Network descriptives

Sacha Epskamp

Th 18/09

Centrality in qgraph

Sacha Epskamp

Assignment 3

Assignment 2

Tu 23/09

Causal networks

Denny Borsboom

Th 25/09

Practical

Denny Borsboom

Assignment 4

Assignment 3

Tu 30/09

Directed networks

Claudia van Borkulo

Th 02/10

Practical

Claudia van Borkulo

Assignment 5

Assignment 4

Tu 07/10

Undirected networks

Sacha Epskamp

Th 09/10

Practical

Sacha Epskamp

Assignment 6

& Final Project

Assignment 5

Tu 14/10

Final project

Th 16/10

Final project

Assignment 6

Tu 21/10

Final project presentations

Th 23/10

Final project presentations

Fr 24/10

Final project

report

(5)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Assignments

I

Assignments are made available during the

practicals on Thursday

I

The deadline for every assignment is the start of the

next practical

I

Assignments should be handed in on blackboard

I

Most assignments contain an essay question

I

_{These should be written as proper scientific reports}

I

Include reference list, correct APA formatting,

etcetera

I

_{These will be graded on writing quality in addition to}

content

I

Assignments have to be written in English

I

Assignment 6 will be significantly smaller than other

(6)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Final Project

I

Groups of 2

I

Choose a dataset

I

Apply the methodology discussed in this course

I

_{Apply the methods of week 5 and 6 to estimate}

network structures

I

_{Apply the methodology discussed in week 3}

I

_{Substantively}

_{interpret the results}

I

_{Conceptually interpret the meaning of network}

analysis on your dataset

I

Write a 1500 word scientific report on your findings

I

10 minute presentations in the last week

I

Creativity is rewarded!

(7)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Grading

I

50 %

Assignments

I

50 %

Final project

(8)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Network Models (2015)

This course is

not

the same course as the Network

Models course given by Lourens Waldorp

I

Generally NM is a followup course to NA (NA is not

required for NM)

I

_{You are allowed to do both!}

I

NA teaches you to apply the network methodology to

psychological data and NM teaches you a deeper

understanding of graph theory

I

More equations in NM and more pretty pictures in NA

(9)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(10)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

I

R is the statistical programming language used

throughout the Research master programme:

I

Multivariate Analysis

I

Programming Skills: R

I

_{SEM and other statistical courses}

I

_{You could very well use it during research projects as}

well

I

This course requires a basic understanding of R

I

Read data into R

I

_{Work with vectors, matrices and data frames}

I

Creating

I

Indexing

I

_{Use functions in R, and consult their help pages}

I

_{Correlate data}

(11)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

If you don’t already know R:

I

Install R from

http://cran.r-project.org/

I

Install RStudio from

http://www.rstudio.com/

I

Introduction to R this Thursday during practical

I

Read the very short introduction to R on blackboard

I

A nice introduction to R is also given at

(12)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(13)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(14)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

MD

Insomnia

Fatigue

Concentration

Worry

(15)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

MD

Insomnia

Fatigue

Concentration

Worry

(16)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

MD

Insomnia

Fatigue

Concentration

Worry

(17)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

MD

Insomnia

Fatigue

Concentration

Worry

(18)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

MD

Insomnia

Fatigue

Concentration

Worry

(19)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

MD

Insomnia

Fatigue

Concentration

Worry

(20)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

MD

Insomnia

Fatigue

Concentration

Worry

(21)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Insomnia

Fatigue

Concentration

Worry

(22)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Insomnia

Fatigue

Concentration

Worry

(23)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Mutualism

(24)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Psychology as a complex system

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●_● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

Disorders usually first diagnosed in infancy, childhood or adolescence Delirium, dementia, and amnesia and other cognitive disorders Mental disorders due to a general medical condition Substance−related disorders Schizophrenia and other psychotic disorders Mood disorders

Anxiety disorders Somatoform disorders Factitious disorders Dissociative disorders Sexual and gender identity disorders Eating disorders Sleep disorders

Impulse control disorders not elsewhere classified Adjustment disorders

Personality disorders Symptom is featured equally in multiple chapters

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

(25)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Building blocks of a network

Different kinds of networks Encoding a network

Network dynamics

References

What is a network?

I

A network is a set of

nodes

connected by a set of

edges

I

_{Nodes are also called vertices}

I

_{Edges are also called links}

(26)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Edge

Node 1

Node 2

(27)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

What is a network?

I

A network is a set of

nodes

connected by a set of

edges

I

_{A node represents an entity, this can be anything:}

I

People

I

Cities

I

Symptoms

I

Psychological constructs

I

_{An edge represents some connection between two}

nodes. Again, this can be anything:

I

Friendship / contact

I

Distance

I

Comorbidity

I

Causality

(28)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Anne is friends with Laura:

Friendship

Anne

(29)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Anne is friends with Laura and Roger, but Laura is not

friends with Roger:

Anne

Laura

Roger

(30)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Different kinds of networks

Encoding a network

Network dynamics

References

Networks can be weighted

Anne is better friends with met Roger than Laura:

Anne

Laura

Roger

(31)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Weights can be signed

Anne is friends with Roger and Laura, but Roger and

Laura don’t like each other at all!

Anne

Laura

Roger

(32)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Edge weights

I

Weights can be positive or negative, and indicates

the

strength

of an edge, with zero indicating no

strength (identical to the absence of an edge)

I

_{Nodes that are connected by a strong edge can be}

seen as close by or easily reachable from one to the

other

I

Sometimes an edge has a

length

rather than a

weight

I

_{This is a positive value indicating the distance}

between two nodes

I

_{A length of}

∞

_{indicates no edge}

I

_{A weight is often recoded to a length by taking the}

(33)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Networks can be directed

Anne likes Laura, but Laura doesn’t like Anne:

Anne

(34)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

I

Edges can be weighted or unweighted

I

_{A network with weighted edges is called a}

_weighted

graph

I

_{Otherwise it is called an}

_{unweighted graph}

I

Edges can be directed or undirected

I

_{If all edges are directed the network is called a}

directed graph

I

_{If all edges are not directed the network is called an}

undirected graph

(35)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

A

B

C

D

Undirected

Unweighted

A

B

C

D

Directed

Unweighted

A

B

C

D

Undirected

Weighted

A

B

C

D

Directed

Weighted

(36)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

I

A directed network with no

cycles

is called a

Directed Acyclic Graph

(DAG)

I

A cycle means that you can not start at a node and

encounter it again by following directed edges

I

This includes no self-loops

I

As we will see in later lectures, DAGs are very useful

in that they represent a clear dependency structure

between the nodes

I

But, the assumption on acylicness is very strict and

(37)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

A

B

C

D

Cyclic

A

B

C

D

Acyclic

(38)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Building blocks of a network Different kinds of networks

Encoding a network

Network dynamics

References

Mathematical notation

In mathematics, a graph

G

is considered an ordered pair

of a

set V

of vertices (nodes) and a set

E

edges:

G

=

{

V

,

E

}

V

=

{

1 ,

2 ,

3 }

E

=

{

(

1 ,

2 )

,

(

2 ,

3 )

,

(

3 ,

1 )

}

1

2

3

(39)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Adjacency matrices

Let

|

V

|

be the number of nodes.

I

An

adjacency matrix

is a square

|

V

| × |

V

|

matrix in

which each element is 0 or 1.

I

_{If there is a 1 in row}

_i

_{and column}

_j

_{it means there is}

an edge from node

i

to node

j

I

_{A 0 denotes that there is no edge}

I

_{Undirected networks are encoded with a symmetrical}

(40)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Adjacency matrices

A

=





0 1 0

0 0 1

1 0 0





1

2

3

(41)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Adjacency matrices

A

=





0 1 1

1 0 1

1 1 0





1

2

3

(42)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Weights Matrices

I

An

weights matrix

is identical to an adjacency matrix

except it encodes the weight of the edge

I

_{A 0 still indicates no edge}

I

_{Higher absolute values indicate stronger edges}

I

_{Undirected networks are encoded with a symmetrical}

(43)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Weights matrices

W

=





0 0

.

5 0

0

1

2

0

0 



1

2

3

(44)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Weights matrices

W

=





0 0

.

5

0

0 −

1

2

0

0 



1

2

3

(45)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Edgelist

Let

|

E

|

be the number of nodes.

I

An edgelist is a

|

E

| ×

2 matrix containing a row for

each edge

I

_{The first column contains the node of origin and the}

second column the node of destination

I

_{In weighted networks, a third column indicates the}

(46)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Edgelist

E

=





1 2

2 3

3 1





1

2

3

(47)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Edgelist

E

=





1 2

2 3

3 1





1

2

3

(48)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Edgelist

E

=





1 2 0

.

5 2 3

1 3 1

2 



1

2

3

(49)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Encoding a network

Network dynamics

References

Edgelist

E

=





1 2 0

.

5 2 3

−

1 3 1

2 



1

2

3

(50)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Interpreting Networks

A network can be interpreted in different ways:

I

As a model of interacting components

I

_{Information can spread from node to node via edges}

I

As a causal model (weeks 4-5)

(51)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Interacting components

(52)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(53)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(54)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(55)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(56)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(57)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(58)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(59)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(60)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(61)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(62)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Friendship

(63)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Friendship

(64)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Relationships

(65)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Sexual contacts

(66)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Networks can be simulated given sufficient information

about a population:

(67)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

If a real network can not be obtained an approximation

can be simulated.

(68)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Psychopathology as a virus...

(69)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Comorbidity

Generalized Anxiety:

I

Chronic Anxiety

I

Anxiety about more than

one event

I

Irritability

I

No control of anxiety

I

Muscle tension

I

Sleep Disturbances

I

Concentration problems

I

Restlessness

I

Fatigue

Major Depression:

I

Depressed mood

I

Loss of interest in

pleasurable things

I

Weight problems

I

Self-reproach

I

(thoughts of) suicide

I

Sleep disturbances

I

Concentration problems

I

Restlessness

(70)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Comorbidity

Generalized Anxiety:

I

Chronic Anxiety

I

Anxiety about more than

one event

I

Irritability

I

No control of anxiety

I

Muscle tension

I

Sleep Disturbances

I

Concentration problems

I

Restlessness

I

Fatigue

Major Depression:

I

Depressed mood

I

Loss of interest in

pleasurable things

I

Weight problems

I

Self-reproach

I

(thoughts of) suicide

I

Sleep disturbances

I

Concentration problems

I

Restlessness

(71)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

(72)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●_● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● _● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

(Borsboom, Cramer, Schmittmann, Epskamp, & Waldorp,

2011)

(73)

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 3.5 3 2.5 2 1.5 1 MDE x D YS MDE x A GPH

MDE x SOPMDE x SIPMDE x PDMDE x APDDYS X A GPH

DYS X SOPDYS X SIPDYS X PDDYS X APDAGPH X SOPAGPH X SIPAGPH X PDAGPH X APDSOP X SIPSOP X PDSOP X APDSIP X PDSIP X APDPD X APD

Network Analysis: Lecture 1. Sacha Epskamp

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Introduction to Network Analysis

Network Analysis: Lecture 1

Sacha Epskamp

University of Amsterdam

Department of Psychological Methods

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

I

Who are you?

I

What is your specialization?

I

Why are you here?

I

Are you familiar with the network perspective?

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Sacha Epskamp

[email protected]

Denny Borsboom

[email protected]

Claudia van Borkulo

[email protected]

Jolanda Kossakowski

Introduction to

Network Analysis

Sacha Epskamp

Course Outline

Why networks?

Network basics

Network dynamics

References

Date

Subject

Lecturer

Start

Due

Tu 02/09

Introduction

Sacha Epskamp

Th 04/09

Intro to R

Sacha Epskamp

Assignment 1

Tu 09/09

Correlational structures

Sacha Epskamp

Th 11/09

qgraph workshop

Sacha Epskamp

Assignment 2

Assignment 1

Tu 16/09

Network descriptives

Sacha Epskamp

Th 18/09

Centrality in qgraph

Sacha Epskamp

Assignment 3

_{These should be written as proper scientific reports}

_{These will be graded on writing quality in addition to}