Present: Abby
Crocker, Kairn Kelley (by phone), Amanda Kennedy, Rodger Kessler, Ben
Littenberg, Connie van Eeghen
1.
Theme: Ben: prediction is not necessarily about
regression. There are many alternatives,
each with strengths and weaknesses. Good
to have many tools in the toolkit to choose from.
2.
Presentation: Abby
– “How we picked the predictive model for the NAS article.” NOTE: this is an excerpt; complete notes can
be obtained from the presenter.
a. Alternative
methods of predictive modeling:
i.
Logistic: widely used, doesn’t have to be explained,
but its limitations are not well understood, i.e. predictive power
ii.
Clinical Heuristic
iii.
Neural Net
iv.
Bayesian Net
v.
Recursive Partitioning – not well known but easy to
explain
b. Board
example of recursive partitioning:
i.
796 babies, of whom 253 with NAS and 531 without, the
remainder missing data; total is 784 babies
ii.
No babies are “grey” – they either have been treated
for NAS or not
iii.
Each predictor will be applied to the 784 population,
e.g. sex (f/m), maternal smoking (y/n), … and evaluate the strength of each
predictor.
iv.
The strongest predictor (for example, maternal
substance abuse) is used to determine new probabilities
1. The
entire group of 784 has a 33% chance of NAS
a. 700
are positive for SA and 71% are NAS
i.
The next strongest predictor (for example gestational
age)
1. Older
babies have a 65% of NAS
a. Smokers
have a 68% of NAS
b. Non-smokers
have a 15% of NAS
2. Younger
babies have an 89% of NAS
b. 84
are negative for SA and 14% are NAS
i.
The next strongest predictor (for example maternal age)
1. Younger
moms have a 16% of NAS
2. Older
moms have a 2% (no further analysis needed down this branch)
v.
This model looks for the best fit and is highly
dependent on how the variables are categorized
1. Cannot
go below some minimum number of subjects in a branch
2. Can
be forced into meaningful clinical variables, and tested that way (not by
ranking the variables)
c. Summary:
there are three reasons to build a model.
i.
Describe the world as it is, and reduce it to something
that might be important. Some of these
are called exploratory studies. No
single model preferred.
ii.
Predict a true relationship, even if it does not
describe what is true in the world completely. Try recursive partitioning.
iii.
Hypothesize the relationship between a predictor and a
variable, using a t test of
Chi-square (if there are only 2 variables).
Logistic modeling might be best.
3.
Workshop
Goals for 2012:
a. Journal
club: identify UVM guests and articles; invite to CROW ahead of time
b. Research
updates: share work-in-process
a.
Aug 9, 16, 23, 30: remaining Thursdays in August will
be cancelled. Everyone is encourage to
attend Book Club on all August Fridays at noon.
Contact Connie if you need the source document we are reviewing jointly. New schedule for fall to be set up by Doodle
poll later in August.
b. Future
agenda to consider:
i.
Kairn – review of draft article on IRR (no Abby)
ii.
Ben: budgeting exercise for grant applications
iii.
Journal Club: “Methods and metrics challenges of
delivery-system research,” Alexander and Hearld, March 2012 (for later in the
year?). UVM authors who have published
interesting design articles (Kim, Osler)
iv.
Rodger: Mixed methods article; article on Behavior’s
Influence on Medical Conditions (unpublished); drug company funding. Also: discuss design for PCBH clinical and
cost research.
v.
Amanda: presentation and interpretation of data in
articles
vi.
Sharon Henry: article by Cleland, Thoracic Spine
Manipulation, Physical Therapy 2007
Recorder: Connie van Eeghen
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