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Multilevel Modeling with R

Spirin Nikita

Dorodnicyn Computing Center of the Russian Academy of Sciences

03.24.2010, Moscow

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Packages covered

SAS MySQL

Python

Mathematica

R

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Agenda

R programming language and R Paradigm Basic operations in R

Graphics with R

Statistics with R

Multilevel Models and ML with R

8 min. times 5 equals 40 min.

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Overview

Free and commercialized GNU GPL

R core team

http://cran.r-project.org

Interpreter

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

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Concepts

Actions with in-memory objects function()

function

library

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Basic Notation

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Basic Notation

A-Z and a-z _

.

0-9

Case Sensitive

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Basic operations in R

assign operator

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Basic operations in R

ls() function

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Basic operations in R

HELP

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Reading Data

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Saving Data

save.image()

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Generating Data

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Generating Data

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Generating Data

Cartesian product

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Generating Data

rfunc(n, p1, p2, ...)

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Of course Matrices

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Syntactic sugar

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Graphics with R

Device paradigm

Window()

Pdf()

X11()

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Graphics with R

Legend for a graph

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Graphics with R

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Graphics with R

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Graphics with R

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Graphics with R

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Graphics with R

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Statistics with R

> library(stats)

Key operator ~

@model description operator

y ~ model

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Statistics with R

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Statistics with R

Quiz

y~x1+x2

y~I(x1+x2)

y ~ poly(x, 2)

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Statistics with R

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Multilevel Modeling with R

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Multilevel Modeling with R

Why multilevel modeling?

Using all the data to perform inferences for groups withsmall sample size

Predict an output for a new group Hierarchical models avoid overfitting effect of least

squares regression

Yields accurate measure of predictive uncertainty

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Multilevel Modeling with R

fss = c(0,8,15,33,42,45,49,54,98,143,165,175,179,200)

# include the library

library(caTools)

# read training and scoring data

train

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Multilevel Modeling with R

# build the modelAUClogistic

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Multilevel Modeling with R

lmer()library(matrix)

Examples:

lmer(y ~ 1 + (1 | county))

lmer(y ~ x + (1 | county))

lmer(y ~ x + (1 + x | county))

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Summary

How R works

Basic objects in R

R graphical capabilities

R for statistical analysis

Multilevel modeling in R

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More Information

R for Beginners, Emmanuel Paradis, Institut des Sciencesde l' Evolution Universite Montpellier II,

F-34095 Montpellier cedex 05, France

http://cran.r-project.org

Data Analysis Using Regression and MultilevelHierarchical Models, A. Gelman J.Hill

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

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Acknowledgements

Thank you!