|Statistician Works to
Develop Method to Deal With Missing Data
Incomplete or missing data is a pervasive
problem in most research. Associate professor is developing,
advancing and applying statistical methods of analysis to resolve
March 10, 2005 :: No. 147
What’s a scientist to do when
some individuals under study for depression are so depressed
they don’t participate?
Those missing study participants mean missing
data, which could result in faulty analysis.
Jamshidian, associate professor of mathematics
at Cal State Fullerton, the search for a way to resolve that
dilemma is an ideal project for math students.
“Incomplete or missing data is a pervasive
problem in almost all areas of research,” says Jamshidian.
“When someone drops out of a research study randomly,
if they move out of state or have an accident on the way to
the test site, that is seen as data missing ‘randomly.’
But in the case of those dropping out of a study because their
condition is so severe, or because they don’t have the
condition at all, that is considered ‘non-random.’
That type of missing data, if ignored, can lead to biased
conclusions in a study,” notes the researcher.
Thanks to a three-year, $168,541 National Science
Foundation grant, Jamshidian —working with a graduate
student and two undergraduates — is developing, advancing
and applying statistical methods for analysis of social and
behavioral sciences data that are missing “not at random.”
“We’re working in two parts. The
first part is fairly theoretical — development of statistical
methods, using a lot of mathematics and statistics. The next
stage is implementing the methods and programming our methodology
to test our theoretical developments,” Jamshidian says.
Another phase is using these statistical methods
on real data. To do that, Jamshidian is working with Ke-Hai
Yuan, University of Notre Dame associate professor of psychology,
and applying the Cal State Fullerton methods on data from
Notre Dame’s Adolescent Parenting Project, an ongoing
longitudinal study of teen parenting. An additional $168,459
National Science Foundation grant was awarded to Notre Dame
for this phase of the project, according to Jamshidian.
“One thing we do know is that there won’t
be a single method that will resolve all missing data problems
in social and behavioral sciences. Our hope is that we find
a series of methodologies that, depending on the type of missing
data, will be of help to researchers.”
Jamshidian joined Cal State Fullerton in 2002,
after teaching at the University of Central Florida in Orlando
and Isfahan University of Technology in Iran. He also has
served as a statistician with BMDP Statistical Software in
Los Angeles. The Anaheim Hills resident earned his doctorate
in applied mathematics from UCLA.
||Mortaza (Mori) Jamshidian, associate
professor of mathematics, at 657-278-2398 or firstname.lastname@example.org
Pamela McLaren of Public Affairs, at
657-278-4852 or email@example.com
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