A Handbook of Statistical Analyses using SAS SECOND EDITION

A Proven Guide for Easily Using R to Effectively Analyze DataLike its bestselling predecessor, A Handbook of Statistical Analyses Using R, Second Edition provides a guide to data analysis using the R system for statistical computing. Each chapter includes a brief account of the relevant statistical background, along with appropriate references.New to the Second EditionNew chapters on graphical displays, generalized additive models, and simultaneous inference A new section on generalized linear mixed models that completes the discussion on the analysis of longitudinal data where the response variable does not have a normal distributionNew examples and additional exercises in several chaptersA new version of the HSAUR package (HSAUR2), which is available from CRANThis edition continues to offer straightforward descriptions of how to conduct a range of statistical analyses using R, from simple inference to recursive partitioning to cluster analysis. Focusing on how to use R and interpret the results, it provides students and researchers in many disciplines with a self-contained means of using R to analyze their data.

[1]  D. Collett.  Modelling Binary Data , 1991 .

[2]  A. Hossain,et al.  A comparative study on detection of influential observations in linear regression , 1991 .

[3]  Friedrich Leisch,et al.  Sweave, Part II: Package Vignettes Reading, writing and interacting with R package primers in Sweave format. , 2003 .

[4]  Robert Tibshirani,et al.  An Introduction to the Bootstrap , 1994 .

[5]  T. Hothorn,et al.  Simultaneous Inference in General Parametric Models , 2008, Biometrical journal. Biometrische Zeitschrift.

[6]  David J. Hand,et al.  Construction and Assessment of Classification Rules , 1997 .

[7]  D. J. Hand,et al.  Recent advances in error rate estimation , 1986, Pattern Recognit. Lett..

[8]  M Greenacre,et al.  Correspondence analysis in medical research , 1992, Statistical methods in medical research.

[9]  G. W. Milligan,et al.  A study of standardization of variables in cluster analysis , 1988 .

[10]  A. Tamhane,et al.  Multiple Comparison Procedures , 1989 .

[11]  Brian Everitt,et al.  Making Sense of Statistics in Psychology: A Second-Level Course , 1996 .

[12]  R. Plackett,et al.  Introduction to Statistical Analysis. , 1952 .

[13]  S. Geisser,et al.  On methods in the analysis of profile data , 1959 .

[14]  P. Grambsch,et al.  Modeling Survival Data: Extending the Cox Model , 2000 .

[15]  Deepayan Sarkar,et al.  Lattice: Multivariate Data Visualization with R , 2008 .

[16]  Henry Braun,et al.  The Collected Works of John W. Tukey: Volume VIII Multiple Comparisons 1948-1983. , 1995 .

[17]  Henry F. Dizney,et al.  Predictive Validity and Differential Achievement on Three Mla—Cooperative Foreign Language Tests , 1967 .

[18]  H. Hotelling.  Analysis of a complex of statistical variables into principal components. , 1933 .

[19]  S Senn,et al.  Analysis of serial measurements in medical research. , 1990, BMJ.

[20]  D. Clayton,et al.  Statistical Models in Epidemiology , 1993 .

[21]  P. Diggle.  Analysis of Longitudinal Data , 1995 .

[22]  D. Cox,et al.  An Analysis of Transformations , 1964 .

[23]  P. McCullagh,et al.  Generalized Linear Models , 1972, Predictive Analytics.

[24]  N. Campbell,et al.  Variable selection techniques in discriminant analysis: I. Description , 1982 .

[25]  Debashis Ghosh,et al.  Statistical Aspects of the Design and Analysis of Clinical Trials , 2002 .

[26]  John D. Kalbfleisch,et al.  The Statistical Analysis of Failure Data , 1986, IEEE Transactions on Reliability.

[27]  K. Hornik,et al.  A Lego System for Conditional Inference , 2006 .

[28]  Peter Dalgaard,et al.  Introductory statistics with R , 2002, Statistics and computing.

[29]  A. Zeileis.  Econometric Computing with HC and HAC Covariance Matrix Estimators , 2004 .

[30]  D. Goodin.  The cambridge dictionary of statistics , 1999 .

[31]  J. Stevens.  Applied Multivariate Statistics for the Social Sciences , 1986 .

[32]  S. Chatterjee,et al.  Regression Analysis by Example (2nd ed.). , 1992 .

[33]  David J. Hand,et al.  A Handbook of Small Data Sets , 1993 .

[34]  Adrian E. Raftery,et al.  Model-Based Clustering, Discriminant Analysis, and Density Estimation , 2002 .

[35]  H. Riedwyl,et al.  Multivariate Statistics: A Practical Approach , 1988 .

[36]  F. Leisch.  FlexMix: A general framework for finite mixture models and latent class regression in R , 2004 .

[37]  J. Studd,et al.  Transdermal oestrogen for treatment of severe postnatal depression , 1996, The Lancet.

[38]  Bernhard N Flury.  Multivariate Statistics: A Practical Approach , 1988 .

[39]  Paul Murrell,et al.  R Graphics , 2006, Computer science and data analysis series.

[40]  David J. Hand,et al.  Discrimination and Classification , 1982 .

[41]  H. Rouanet,et al.  COMPARISON BETWEEN TREATMENTS IN A REPEATED‐MEASUREMENT DESIGN: ANOVA AND MULTIVARIATE METHODS , 1970 .

[42]  Richard A. Becker,et al.  The New S Language , 1989 .

[43]  S. Skevington.  A standardised scale to measure beliefs about controlling pain (B.P.C.Q.): A preliminary study , 1990 .

[44]  Karl Pearson F.R.S..  LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[45]  Susan Quine.  Achievement orientation of aboriginal and white Australian adolescents , 1973 .

[46]  D. Bates,et al.  Mixed-Effects Models in S and S-PLUS , 2001 .

[47]  B. Everitt.  Statistics for Psychologists: An Intermediate Course , 2001 .

[48]  K. Berk.  Tolerance and Condition in Regression Computations , 1977 .

[49]  Michael L. Davidson.  Univariate versus multivariate tests in repeated-measures experiments. , 1972 .

[50]  Gordon Johnston,et al.  Statistical Models and Methods for Lifetime Data , 2003, Technometrics.

[51]  J N Matthews,et al.  A refinement to the analysis of serial data using summary measures. , 1993, Statistics in medicine.

[52]  Friedrich Leisch,et al.  Sweave: Dynamic Generation of Statistical Reports Using Literate Data Analysis , 2002, COMPSTAT.

[53]  G. H. Morrey.  Designing Experiments and Analysing Data , 1991 .

[54]  Robert Gentleman,et al.  Statistical Applications in Genetics and Molecular Biology , 2005 .

[55]  H. Akaike.  A new look at the statistical model identification , 1974 .

[56]  Brian Everitt,et al.  Linear Mixed Models I , 2001 .

[57]  M. Friendly.  Mosaic Displays for Multi-Way Contingency Tables , 1994 .

[58]  Edward R. Tufte,et al.  The Visual Display of Quantitative Information , 1986 .

[59]  Trevor Hastie,et al.  Statistical Models in S , 1991 .

[60]  Peter Buhlmann,et al.  BOOSTING ALGORITHMS: REGULARIZATION, PREDICTION AND MODEL FITTING , 2007, 0804.2752.

[61]  D.,et al.  Regression Models and Life-Tables , 2022 .

[62]  N. Campbell,et al.  Variable selection techniques in discriminant analysis: II. Allocation , 1982 .

[63]  A. Tamhane,et al.  Multiple Comparison Procedures , 2009 .

[64]  John M. Chambers,et al.  Programming With Data , 1998 .

[65]  J. Nelder.  A Reformulation of Linear Models , 1977 .

[66]  Achim Zeileis.  Object-oriented Computation of Sandwich Estimators , 2006 .

[67]  H. Huynh,et al.  Estimation of the Box Correction for Degrees of Freedom from Sample Data in Randomized Block and Split-Plot Designs , 1976 .

[68]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.