model-based recursive partitioning of network models

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Hallucinations. Paranoia. Yes. No. Sleep loss schizophrenia. (92%) bipolar. (84%) schizophrenia. (60%) bipolar. (62%). No. Yes. No. Yes ...
MODEL-BASED RECURSIVE PARTITIONING OF NETWORK MODELS: A STATISTICAL LEARNING APPROACH TO NETWORK ANALYSIS PAYTON JONES HARVARD UNIVERSITY

English

Engineering

English (20%)

Engineering (40%)

English (20%)

Engineering (40%)

English (20%)

Engineering (40%)

Atheists

Believers

No Effect

Meaningful Subgroups

Meaningful Subgroups

Meaningful Subgroups in Networks

Decision Trees

No

Hallucinations

Sleep loss No schizophrenia (60%)

Yes bipolar (84%)

Yes

Paranoia No bipolar (62%)

Yes schizophrenia (92%)

log(y) = B(hallucinations)X (hallucinations) * B(needforsleep)X(needforsleep) * B(paranoia)X(paranoia) + B(hallucinations)X(hallucinations) * B(needforsleep)X(needforsleep) + B(hallucinations)X(hallucinations) * B(paranoia)X(paranoia) + B(needforsleep)X(needforsleep) * B(paranoia)X(paranoia) +

B B

X X

(hallucinations)

(hallucinations)

+

(needforsleep)

(needforsleep)

+

B

X

(paranoia)

(paranoia)

No

Hallucinations

Sleep loss No schizophrenia (60%)

Yes bipolar (84%)

Yes

Paranoia No bipolar (62%)

Yes schizophrenia (92%)

No

Sleep loss

Hallucinations

Yes

Paranoia

No

Sleep loss

Hallucinations

Yes

Paranoia

Model Based Recursive Partitioning

No

Sleep loss

Hallucinations

Yes

Paranoia

Model Based Recursive Partitioning

Model Based Recursive Partitioning

Model Based Recursive Partitioning

Model Based Recursive Partitioning

Model Based Recursive Partitioning

A

A A

Model Based Recursive Partitioning

Model Based Recursive Partitioning

Model Based Recursive Partitioning

No

Sleep loss

Hallucinations

Yes

Paranoia

> library(devtools) > install_github(“paytonjjones/networktree”) > library(networktree) > data(“workaholic”) > nodeVars splitVars myTree plot(myTree)

Model Based Recursive Partitioning

THANK YOU! Special Thanks: Patrick Mair Achim Zeileis Thorsten Simon Learn more about the method: networktree R package github.com/paytonjjones/networktree