Advanced Studies in Biostatistics

 

INSTRUCTOR:           Steven Juliano                        OFFICE:          335 FSA         

E-MAIL:                      sajulian@ilstu.edu                     PHONE:          82642

HOURS (tentative):      WTh 9:30 - 10:30 AM           LECTURE:      TTh 1:00 - 2:30 PM, SLB 121

 

Course content:  This version of Advanced Studies is designed to give graduate students the opportunity to learn some of the advanced statistical techniques now used by biologists, primarily in the fields of ecology, behavior, physiology, and evolutionary biology.  The prerequisite for this course is BSC 490/420.27 (Biostatistics and Biostatistics Laboratory), or an equivalent graduate level course in applied statistics.  If you have had a course that you think is the equivalent, you should discuss this with me immediately.  A working knowledge of the statistical package SAS 9 or higher is desirable.  You should be able to operate IBM compatible computers in Windows, and to use Excel.

 

I intend to be flexible in my approach to the breadth and depth of the material covered.  The emphasis of the course is on statistical applications - that is how to apply particular procedures to specific problems.  We will only cover statistical theory to the extent necessary to understanding the applications.  I plan to offer lectures describing the particular problems and situations for which the advanced techniques described can be used, and to explain the interpretation of results from these advanced techniques.  Much of the actual learning of the techniques will occur when you use them in problems that I will assign.  How much you learn depends primarily on you, and on the effort you are willing to give.

 

Required Text:           Scheiner, S. M. & Gurevitch, J. (eds.)  2001.  Design and Analysis of

                                                Ecological Experiments, 2nd edition.  Oxford University Press, Oxford

 

This text includes 18 chapters on various advanced techniques used primarily in the field of ecology, and primarily in experimental (as opposed to observational) analysis.  Although the text emphasizes ecological applications, all of the techniques described are applicable to other subdisciplines of biology, and in fact to disciplines beyond biology.  I plan to cover most of the chapters in the book, though the detail with which they are covered will vary.

 

This book includes supplementary material (data sets, SAS code) as html files on Oxford University Press web site.  We will make use of this material, so you should bookmark the site:

 

http://www.oup-usa.org/sc/0195131886/index.html

 

These files can also be downloaded as zipped files

 

Supplemental assignments on randomization methods will come from another book (not required): 

 

Manly, B. F. J. 1991.  Randomization and Monte Carlo Methods in Biology.  Chapman & Hall, New York. 

 

Grade:  There will be no exams.  Your grade in this course will be based on graded assignments, which will consist of statistical problems for you to analyze.  For each problem, you will apply the techniques described, and write a report on the results.  The reports will be graded based on correct execution and interpretation of the procedures, and clear presentation of the results.  Reports will not be accepted late.   For each problem, I will include a set of questions that will help you in the writing of the report.  Reports must be typed, and should include publication-quality graphics and tables.  Relevant statistical input and output should be included as an appendix. 

 

Topic Outline

(Instructor reserves the right to modify this outline any time he feels like it)

Topic                                                                                       Reading Assignment

 

PART 1:  Introduction

 

Using statistics in science ...............................…………….      Scheiner & Gurevitch Ch. 1

Graphical presentations & Exploratory data analysis ………     Scheiner & Gurevitch Ch. 3

 

PART 2:  ANOVA & MANOVA

 

Experimental design ………………………………………..   Supplementary readings

Laboratory experiments ............................................…......Scheiner & Gurevitch Ch. 4

Field experiments .............................................................. Scheiner & Gurevitch Ch. 5

Multivariate Analysis of Variance ...........................….......       Scheiner & Gurevitch Ch. 6, 8

Power analysis …………………………………………..…   Scheiner & Gurevitch Ch. 2

 

PART 3:   Regression & Correlation

 

Nonlinear regression .......................................................... Scheiner & Gurevitch Ch. 10

Path analysis .....................................................................Scheiner & Gurevitch Ch. 12

Time series analysis ........................................................... Scheiner & Gurevitch Ch. 9

Logistic regression ...........................................….............. Scheiner & Gurevitch Ch. 11

 

PART 4.  Randomization Tests

 

Basic concepts ...................................................................Manly Ch. 1, 2, 3

Bootstrap & Jackknife .......................................................Scheiner & Gurevitch Ch. 14

Randomization ANOVA & ANCOVA .........................…..     Scheiner & Gurevitch Ch. 7,

                                                                                                Manly Ch. 5

PART 5.   Miscellaneous Tests

 

Failure time analysis ...........................................................Scheiner & Gurevitch Ch. 13

Spatial analysis:  Mantel’s test ………………………..……    Scheiner & Gurevitch Ch. 16

Meta-analysis .....................................................................Scheiner & Gurevitch Ch. 18