Deciding how many subjects to include in a study is key decision.
One investigation of studies in a certain area found that only
half of them had enough subjects to meet usual power criteria.
Learn how to design studies so that you don’t end up with
inconclusive results after much expense and effort.  Thomas Ryan
will present his online course, “Sample Size and Power,”
November 26 – December 31 at statistics.com.

Upcoming Courses:
Oct 29:  Safety Monitoring Committees in Clinical Trials
Nov 12:  Introduction to Structural Equation Modeling
Nov 12:  Categorical Data – Applied Modeling
Nov 12:  Advanced Survival Analysis
Nov 26:  Sample Size and Power Determination (more below)
Dec  3:  Meta Analysis

"Sample Size and Power Determination" covers how to plan the
appropriate sample size for a study, striking the optimal balance
of feasible sample size, reasonable assumptions, and acceptable
power. The power of a study (the study's ability to prove a
treatment effect exists) is determined by such factors as the
magnitude of the treatment effect, the sample size, alpha (the
level of statistical significance required), and (for survival
studies) the study duration.

Since some of these factors are under the researcher's control
while others are not, the goal of power analysis is to balance
them as a series of "What if's." For example "What sample size
would we need if the treatment reduces the risk of death by 10%,
and what sample size would we need if the treatment reduces the
risk of death by 20%?" Or, "How would power be affected if the
study followed patients for two years rather than three?" This
process of finding a balance among factors is done most
effectively with graphs that allow the researcher to grasp
(and communicate) a range of options in a single picture,
and find the one that strikes the optimal balance of feasible
sample size, reasonable assumptions, and acceptable power.
Illustrations include examples from means, proportions,
correlations, and survival analysis, and possibly from
other procedures as well.

Dr. Thomas P. Ryan is the author of “Modern Engineering
Statistics,” “Modern Experimental Design,” “Modern Regression
Methods and Statistical Methods for Quality Improvement,” all
from Wiley, plus numerous papers in peer-reviewed journals. He
is an elected Fellow of the American Statistical Association,
American Society for Quality, and Royal Statistical Society, and
has been listed in Marquis Who's Who in America. He served on
the Editorial Review Board of the Journal of Quality Technology
from 1990 through 2006 and was the Book Review Editor of that
journal from 2003 through 2006. Participants can ask questions
and exchange comments with Dr. Ryan via a private discussion
board throughout the period of the course.

Details:
http://www.statistics.com/ourcourses/samplesize/

The course takes place online at staistics.com in a series of 4
weekly lessons and assignments, and requires about 15 hours per
week.  Participate at your own convenience; there are no set
times when you are required to be online.

Hope to see you "online"!

Janet Dobbins

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