Reading List

 

Below is a list of useful books that you can use to supplement MASS, all of which are in the University Library, except where indicated. They are grouped by topic.

 

General Resources

 

The SAS manuals often have very good short descriptions of statistical techniques. I have found the writeups for PROC GENMOD (generalized linear models) and survival analysis (PROC LIFEREG, PROC LIFETESR and PROC PHREG) in the SAS version 8 documentation particularly good.

 

The “White Book”: the book “Statistical models in S” (see below for references in the topic sections) has information on fitting linear models, glms/gams, nonlinear models, tree based models, and local regressions (loess).

 

The short articles in the Encyclopedia of Statistical Sciences (9 volumes plus supplement, published by Wiley) are a good way to get started on an unfamiliar topic. Note that you can’t borrow this reference: library use only.

 

Course notes for Stage 3 and 7  courses: The course notes for STATS 302, STATS 330, STATS 340, STATS 761 and STATS 764  are useful resources.

 

Other general books on statistical modelling:

 

Harrell, Frank E. Jr. (2001). Regression Modeling Strategies : With Applications to Linear Models, Logistic Regression, and Survival Analysis.  New York : Springer.

 

Krzanowski, Wojtek J. (1998). An Introduction to Statistical Modelling. London: Arnold.

 

 

 

Plotting/statistical graphics

 

Books

Chambers, John M, William S. Cleveland, Beat Kleiner and Paul A. Tukey. (1983). Graphical Methods for Data Analysis. Belmont, Calif.: Wadsworth.

 

Cleveland, William S. and Marylyn E. McGill (Eds), (1988). Dynamic Graphics for Statistics, Pacific Grove, Calif.: Wadsworth & Brooks/Cole Advanced Books & Software.

 

Cleveland, William S. (1994). The Elements of Graphing Data (Revised Ed).  Murray Hill, N.J. : AT&T Bell Laboratories.

 

Cleveland, William S. (1993). Visualising Data. Summit, N.J.: Hobart Press.

 

Cook, R. Dennis and Stanford Weisberg (1994) Introduction to Regression Graphics. New York: Wiley.

 

Tufte, Edward R. (1983). The Visual Display of Quantitative Information. Cheshire, Conn: Graphics Press.

 

Tufte, Edward R. (1990). Envisioning Information. Cheshire, Conn: Graphics Press.

 

Computer resources

Trellis graphics: The trellis manual (Trellis Graphics Manual)  and the tutorial introduction (A Tour of Trellis Graphics) are both useful. See the resources page for links. The homepage of the American Statistical Association’s Statistical Graphics Section also contains interesting links. The URL is

http://www.bell-labs.com/topic/societies/asagraphics

 

Linear Models

 

Chambers, John M. and Trevor. J Hastie (eds) (1993) Statistical Models in S. London: Chapman and Hall

 

Chatterjee, Samprit, Ali S. Hadi and Bertram Price (2000). Regression Analysis by Example (3rd Ed). New York: Wiley.

 

Cook, R. Dennis  and Sanford Weisberg. (1999). Applied Regression including Computing and Graphics. New York : Wiley, 1999.

 

Draper, Norman and Harry Smith. (1998) Applied Regression Analysis (3rd Ed). New York : Wiley.

 

Montgomery, Douglas C. (2001). Design and Analysis of Experiments (5th Ed). New York : Wiley.

 

Montgomery, Douglas C., Elizabeth A. Peck and  G. Geoffrey Vining. (2001). Introduction to Linear Regression Analysis (3rd Ed). New York : Wiley.

 

Weisberg, Sanford (1985) Applied Linear Regression (2nd Ed). New York : Wiley.

 

Modern Regression

 

Breiman, L., Friedman, J.C., Olshen, R.A. and Stone, C.J. (1984). Classification and Regression Trees. Belmont, Calif.: Wadsworth.

 

Chambers, John M. and Trevor. J Hastie (eds) (1993) Statistical Models in S. London: Chapman and Hall

 

Hardle, W. (1991). Smoothing Techniques with Implementation in S. New York: Springer.

 

Hastie, Trevor, Robert Tibshirani, Jerome Friedman. (2001). The Elements of Statistical Learning : Data Mining, Inference, and Prediction. New York : Springer.

 

Marsh, Lawrence C. and David R. Cormier. (2002) Spline Regression Models. Thousand Oaks, Calif. : Sage Publications

 

Ramsay, James.O. and B.W. Silverman. (2002). Applied Functional Data Analysis: Methods and Case Studies. New York: Springer.

 

Ripley, Brian D. (1996). Pattern Recognition and Neural Networks. Cambridge ; New York : Cambridge University Press

 

 

GLMs/GAMs

 

Agresti, Alan. (2002) Categorical Data Analysis.  New York : Wiley-Interscience

 

Chambers, John M. and Trevor. J Hastie (eds) (1993) Statistical Models in S. London: Chapman and Hall

 

Dobson, Annette J. (2002) An Introduction to Generalized Linear Models (2nd Ed). Boca Raton : Chapman & Hall.

 

Hastie, Trevor and Robert J. Tibshirani. (1990) Generalized Additive Models. London: Chapman and Hall.

 

Hosmer, David W. and Stanley Lemeshow.(2000). Applied Logistic Regression. New York : Wiley.

 

Kleinbaum, David G. and Mitchel Klein. (2002)  Logistic Regression : a Self-Learning Text. New York: Springer.

 

McCullagh, P.  and J.A. Nelder. (1989). Generalized Linear Models (2nd Ed). London ; New York : Chapman and Hall.

 

Menard, Scott (2002). Applied Logistic Regression Analysis. Thousand Oaks, Calif. : Sage Publications.

 

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Multivariate Analysis

 

 

Flury, Bernard and Hans Riedwyl (1988). Multivariate Statistics : a Practical Approach. London ; New York : Chapman and Hall.

 

Flury, Bernard . (1997). A First Course in Multivariate Statistics. New York: Springer.

 

Johnson, Richard A. (2002). Applied Multivariate Statistical Analysis. (5th Ed). Upper Saddle River, NJ: Prentice Hall

 

Manly, Brian F. J. (1994). Multivariate Statistical Methods : a Primer. London: Chapman and Hall.

 

Rencher, Alvin C. (2002). Methods of Multivariate Analysis (2nd Ed). New York: Wiley

 

Seber, G.A.F. (1984). Multivariate Observations. New York: Wiley

 

 

Time Series Analysis

 

Abraham, Bovas and Johannes Ledolter. (1983). Statistical Methods for Forecasting. New York: Wiley.

 

Bloomfield, Peter. (2000). Fourier Analysis of Time Series : an Introduction. New York: Wiley.

 

Box, George E. P. and Gwilym M. Jenkins. (1976). Time Series Analysis: Forecasting and Control. (rev Ed). Englewood Cliffs, N.J.: Prenctice Hall.

 

Brockwell, Peter J. and Richard A. Davis. (2002). Introduction to Time Series and Forecasting. (2nd Ed). New York : Springer.

 

Chatfield, Christopher. (1996).  The Analysis of Time Series: an Introduction. (5th Ed).

London : Chapman & Hall.

 

Diggle, Peter. (1990) Time Series : a Biostatistical Introduction. New York: Oxford University Press

 

Kedem, Benjamin. (2002). Regression models for time series analysis. New York: Wiley.

 

Zivot, Eric and Jiahui Wang. (2002). Modeling financial time series with S-Plus. New York : Springer.

 

Mixed Models

 

Crowder, M.J. and D.J. Hand. (1990). Analysis of Repeated Measures. New York: Chapman and Hall.

 

Diggle, Peter J. et al. (2002). Analysis of Longitudinal Data. Oxford : Oxford University Press.

 

Longford, Nicholas T. (1993). Random Coefficient Models. New York: Oxford University Press.

 

Pinheiro, José C. Pinheiro and Douglas M. Bates. (2000). Mixed-effects models in S and S-PLUS. New York : Springer. NB: Available electronically

 

Verbeke, Geert and Geert Molenberghs. (2002). Linear Mixed Models for Longitudinal Data. New York : Springer.  NB: Available electronically.

 

Non-Linear Models

 

Bates, Douglas M. and Donald G. Watts. (1988). Nonlinear Regression Analysis and its Applications. New York : Wiley.

 

Chambers, John M. and Trevor. J Hastie (eds) (1993) Statistical Models in S. London: Chapman and Hall.

 

Seber, G.A.F and C. J. Wild. (1989). Nonlinear Regression. New York : Wiley.

 

Survival Analysis

 

Hosmer, David W. Jr and Stanley Lemeshow. (1999). Applied Survival Analysis : Regression Modeling of Time to Event Data. New York : Wiley.

 

Lawless, J.F. (1982). Statistical Models and Methods for Lifetime Data. New York: Wiley.

 

Kalbfleisch, John D. and Ross L. Prentice. (2002). The Statistical Analysis of Failure Time Data. (2nd Ed). New York: Wiley.

 

Smith, Peter J. (2002) Analysis of Failure and Survival Data. Boca Raton : Chapman & Hall

 

Parmar, Mahesh K.B and David Machin. (1995). Survival Analysis: a Practical Approach. Chichester ; New York: Wiley.

 

Spatial Statistics

 

Cressie, Noel A.C. (1993). Statistics for Spatial Data. New York: Wiley.

 

Kaluzny, Stephen P. et al. (1997). S+SpatialStats : User's Manual for Windows and UNIX. New York : Springer.

 

Ripley, Brian D. (1981). Spatial Statistics. New York: Wiley.