Medical statistics courses presented by the Medical and Pharmaceutical 
Statistics Research Unit, University of Reading:

  8-9 March Sample Size Determination in Clinical Trials
        Presenters: Anne Whitehead and Patrick Kelly 

  10-12 March Statistical Methods for Ordered Categorical Data
        Presenters: Kim Bolland and John Whitehead 

full details are given below or see http://www.reading.ac.uk/mps

                            


                 Sample Size Determination in Clinical Trials
 
                 Presenters: Anne Whitehead and Patrick Kelly 

                              8-9 March 2004
                              
       Standard fee: £600 (discounts available for early booking and 
  academic or public sector participants - see http://www.reading.ac.uk/mps)


At the planning stage of a clinical trial a key question is "How many patients 
do we need?" For a superiority trial the main objective is to provide evidence 
of superior efficacy for the new therapy relative to the control.  This 
requires a sample size that ensures sufficient statistical power to detect a 
clinically relevant improvement. Equivalence or non-inferiority trials require 
sample sizes that establish with sufficient confidence that the new therapy is 
respectively equivalent to or no worse than the control.

This course provides a framework for sample size determination in superiority, 
non-inferiority and equivalence trials. It considers a general parametric 
approach applicable to binary, ordinal, time to event or normally distributed 
patient responses. Comparisons are made with other commonly used approximate 
and exact methods.  Extension to more than two treatments, including a 
factorial design, is considered. Practical aspects such as allowance for 
drop-outs, protocol violations and mid-trial sample size reviews are 
addressed.  The course includes practical sessions involving the use of hand 
calculators and training in software packages such as nQuery Advisor and 
PASS.  Use of other packages is discussed.

Programme

* A general parametric approach to sample size calculations
* Binary, ordinal, time to event and normally distributed data
* A unified approach to superiority, equivalence and 
	non-inferiority trials
* Parallel group and cross-over designs
* Designs with more than two treatments
* Practical and ethical considerations
* Software



              Statistical Methods for Ordered Categorical Data
  
                Presenters: Kim Bolland and John Whitehead 

                           10-12 March 2004

       Standard fee: £900 (discounts available for early booking and 
  academic or public sector participants - see http://www.reading.ac.uk/mps)

Ordered categorical data arise from many clinical trials and epidemiological 
studies.  Commonly used scales include the Glasgow Outcome Scale in head 
injury, where the five response categories are Good Recovery, Moderate 
Disability, Severe Disability, Vegetative State and Death; the Barthel Index 
and modified Rankin score in stroke; the Expanded Disability Status scale in 
multiple sclerosis as well as various measures of quality of life.  This 
course examines the design and analysis of studies in which the primary 
response is of this form.

Binary data are a special case of ordered categorical data and the course 
first reviews the statistical methodology for binary data, with an emphasis 
on logistic regression analysis.  The generalisation from binary to ordinal 
data is based on the assumption of proportional odds, and for a simple 
comparison of two homogenous groups the method leads to the Mann-Whitney 
test.  Linear modelling and model checking are given prominence.  Calculation 
and review of sample sizes are examined, together with other design issues.  
Methods for the analysis of repeated ordinal data based on the marginal model 
and on the subject-specific model are presented and compared. 

The course is extensively illustrated using examples drawn from the 
presenters' consultancy experience.  Many practical sessions are included, 
most of which involve using SAS.

Programme

* Review of binary data analysis
* The proportional odds model
* Fitting linear models using PROC LOGISTIC
* Model checking
* Alternative models
* Ordinal data and clinical trials
* Sample size and power
* Repeated ordinal data

For further information and to book a place on either course, please visit 
http://www.reading.ac.uk/mps