Preface to First Edition - lib

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SUMMARY 41Ex. 2.2 Mortality rates per 100, 000 from male suicides for a number of agegroups and a number of countries are given in Table 2.4. Construct sideby-sidebox plots for the data from different age groups, and comment onwhat the graphic tells us about the data.Table 2.4:suicides2 data. Mortality rates per 100, 000 frommale suicides.A25.34 A35.44 A45.54 A55.64 A65.74Canada 22 27 31 34 24Israel 9 19 10 14 27Japan 22 19 21 31 49Austria 29 40 52 53 69France 16 25 36 47 56Germany 28 35 41 49 52Hungary 48 65 84 81 107Italy 7 8 11 18 27Netherlands 8 11 18 20 28Poland 26 29 36 32 28Spain 4 7 10 16 22Sweden 28 41 46 51 35Switzerland 22 34 41 50 51UK 10 13 15 17 22USA 20 22 28 33 37Ex. 2.3 The data set shown in Table 2.5 contains values of seven variablesfor ten states in the US. The seven variables arePopulation: population size divided by 1000,Income: average per capita income,Illiteracy: illiteracy rate (% population),Life.Expectancy: life expectancy (years),Homicide: homicide rate (per 1000),Graduates: percentage of high school graduates,Freezing: average number of days per below freezing.With these data1. Construct a scatterplot matrix of the data labelling the points by statename (using function text).2. Construct a plot of life expectancy and homicide rate conditional onaverage per capita income.© 2010 by Taylor and Francis Group, LLC
Table 2.5:USstates data. Socio-demographic variables for tenUS states.Population Income Illiteracy Life.Expectancy Homicide Graduates Freezing3615 3624 2.1 69.05 15.1 41.3 2021198 5114 1.1 71.71 10.3 62.6 202861 4628 0.5 72.56 2.3 59.0 1402341 3098 2.4 68.09 12.5 41.0 50812 4281 0.7 71.23 3.3 57.6 17410735 4561 0.8 70.82 7.4 53.2 1242284 4660 0.6 72.13 4.2 60.0 4411860 4449 1.0 70.43 6.1 50.2 126681 4167 0.5 72.08 1.7 52.3 172472 3907 0.6 71.64 5.5 57.1 16842 DATA ANALYSIS USING GRAPHICAL DISPLAYS© 2010 by Taylor and Francis Group, LLC
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A Handbook ofStatisticalAnalysesUsi
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DedicationTo our wives, Mary-Elizab
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Preface to First EditionThis book i
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List of Figures1.1 Histograms of th
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Page 13 and 14: 12.2 R output of the linear mixed-e
Page 15 and 16: 18.7 Within-cluster sum of squares
Page 17 and 18: 4.6 Lanza data. Misoprostol randomi
Page 19 and 20: 15.2 BCG data. Meta-analysis on BCG
Page 21 and 22: 6 Simple and Multiple Linear Regres
Page 23 and 24: CHAPTER 1An Introduction to R1.1 Wh
Page 25 and 26: INSTALLING R 3One can change the ap
Page 27 and 28: DATA OBJECTS IN R 5http://CRAN.R-pr
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Page 31 and 32: DATA IMPORT AND EXPORT 9As a simple
Page 33 and 34: BASIC DATA MANIPULATION 11The funct
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Page 37 and 38: COMPUTING WITH DATA 15Max. : 20.960
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Page 45 and 46: SUMMARY 23examples of these functio
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Page 49 and 50: Table 2.2:CHFLS data. Chinese Healt
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Page 67 and 68: INTRODUCTION 47table. Here there ar
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ANALYSIS USING R 93Df Roy approx F
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SUMMARY 95Table 5.4:schooldays data
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CHAPTER 6Simple and Multiple Linear
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SIMPLE LINEAR REGRESSION 99hours be
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MULTIPLE LINEAR REGRESSION 101The e
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ANALYSIS USING R 1036.3.1 Regressio
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ANALYSIS USING R 105R> layout(matri
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ANALYSIS USING R 107R> data("clouds
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ANALYSIS USING R 109R> summary(clou
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ANALYSIS USING R 111R> psymb plot(
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SUMMARY 113R> plot(clouds_fitted, c
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SUMMARY 115R> plot(clouds_lm)Cook's
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CHAPTER 7Logistic Regression and Ge
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INTRODUCTION 119Table 7.2:womensrol
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LOGISTIC REGRESSION AND GENERALISED
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ANALYSIS USING R 123R> data("plasma
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ANALYSIS USING R 125R> summary(plas
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ANALYSIS USING R 1277.3.2 Women’s
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ANALYSIS USING R 129R> myplot(role.
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ANALYSIS USING R 131R> role.fitted2
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ANALYSIS USING R 133R> summary(poly
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ANALYSIS USING R 1357.3.4 Driving a
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SUMMARY 137Table 7.5:bladdercancer
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CHAPTER 8Density Estimation: Erupti
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DENSITY ESTIMATION 141The Hertzspru
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DENSITY ESTIMATION 143rectangular:
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DENSITY ESTIMATION 1451 R> plot(xgr
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ANALYSIS USING R 1478.3 Analysis Us
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2.2ANALYSIS USING R 149R> library("
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ANALYSIS USING R 1510.360891 54.612
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ANALYSIS USING R 153The results are
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SUMMARY 155R> layout(matrix(1:2, nc
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SUMMARY 157Table 8.4: birthdeathrat
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SUMMARY 159Table 8.5:schizophrenia
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162 RECURSIVE PARTITIONINGTable 9.1
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164 RECURSIVE PARTITIONINGBoth sets
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166 RECURSIVE PARTITIONINGR> librar
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168 RECURSIVE PARTITIONINGR> DEXfat
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170 RECURSIVE PARTITIONINGOne way o
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172 RECURSIVE PARTITIONINGR> librar
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174 RECURSIVE PARTITIONINGR> plot(g
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CHAPTER 10Scatterplot Smoothers and
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INTRODUCTION 179Table 10.2:USairpol
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SMOOTHERS AND GENERALISED ADDITIVE
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ANALYSIS USING R 187R> plot(time ~
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ANALYSIS USING R 189R> x y men150
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ANALYSIS USING R 195ter 9) where th
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198 SURVIVAL ANALYSISTable 11.1:gli
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200 SURVIVAL ANALYSISspect to time
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202 SURVIVAL ANALYSISHazard0.00 0.0
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204 SURVIVAL ANALYSISIn the Cox mod
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206 SURVIVAL ANALYSISExact Logrank
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208 SURVIVAL ANALYSISR> summary(GBS
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210 SURVIVAL ANALYSISR> layout(matr
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212 SURVIVAL ANALYSISmodels includi
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214 ANALYSING LONGITUDINAL DATA Iti
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216 ANALYSING LONGITUDINAL DATA ITa
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218 ANALYSING LONGITUDINAL DATA Iot
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220 ANALYSING LONGITUDINAL DATA IR>
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226 ANALYSING LONGITUDINAL DATA IKe
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228 ANALYSING LONGITUDINAL DATA Ido
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CHAPTER 13Analysing Longitudinal Da
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METHODS FOR NON-NORMAL DISTRIBUTION
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ANALYSIS USING R: GEE 239R> summary
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ANALYSIS USING R: RANDOM EFFECTS 24
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ANALYSIS USING R: RANDOM EFFECTS 24
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SUMMARY 251Table 13.3:schizophrenia
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254 SIMULTANEOUS INFERENCE AND MULT
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CHAPTER 15Meta-Analysis: Nicotine G
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SYSTEMATIC REVIEWS AND META-ANALYSI
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STATISTICS OF META-ANALYSIS 271Sele
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ANALYSIS USING R 273the parameters
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ANALYSIS USING R 275R> plot(smoking
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PUBLICATION BIAS 277R> summary(BCG_
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SUMMARY 279R> summary(BCG_mod)Call:
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SUMMARY 2811 / standard error2 4 6
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Table 15.4:aspirin data. Meta-analy
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CHAPTER 16Principal Component Analy
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PRINCIPAL COMPONENT ANALYSIS 287nie
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ANALYSIS USING R 289R> score plot(
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ANALYSIS USING R 293Yuping (CHN) Ha
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SUMMARY 295R> biplot(heptathlon_pca
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SUMMARY 297rainJuly: rainfall in Ju
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Table 17.1:watervoles data. Water v
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302 MULTIDIMENSIONAL SCALINGn in nu
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304 MULTIDIMENSIONAL SCALINGwill be
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308 MULTIDIMENSIONAL SCALINGR> libr
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310 MULTIDIMENSIONAL SCALINGR> plot
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Table 17.3:eurodist data (package d
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CHAPTER 18Cluster Analysis: Classif
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INTRODUCTION 317mass, mass), the pe
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CLUSTER ANALYSIS 319x 20 2 4 6 8 10
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CLUSTER ANALYSIS 32141031678925Figu
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CLUSTER ANALYSIS 3231. Find some in
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ANALYSIS USING R 32518.3 Analysis U
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ANALYSIS USING R 333R> scatterplot3
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BibliographyAdler, D. and Murdoch,
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BIBLIOGRAPHY 337Chambers, J. M. and
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BIBLIOGRAPHY 339Everitt, B. S. and
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BIBLIOGRAPHY 341Heitjan, D. F. (199
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BIBLIOGRAPHY 343Leisch, F. and Ross
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BIBLIOGRAPHY 345Proudfoot, J., Gold
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BIBLIOGRAPHY 347Stevens, J. (2001),
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