Assigned Reading
 Association networks
Read
 Introduction to chisquare test Read►
 Statistical test of independence in 2 variables Slides►
 Statistical test of independence in 3 variables Slides►
 Independence test through Poisson regression
Slides►
 Jee Vang's lecture on independence test through Mutual Information Slides►
Assignment
Question 1:
For this assignment you can use any statistical package including SQL or Excel. Work can be done in group's of two students but you cannot
work with a student that you have previously teamed up with.
A. For the following data:
MD 
RN 
Complaint 
Observed 
George 
Jim 
Yes 
53 
George 
Jim 
No 
424 
George 
Jill 
Yes 
11 
George 
Jill 
No 
37 
Smith 
Jim 
Yes 
0 
Smith 
Jim 
No 
16 
Smith 
Jill 
Yes 
4 
Smith 
Jill 
No 
139 
 Estimate chisquare for complete independence, 3 joint independence models,
and 3 homogenous models
 Which model best fits the data and why?
Shruti's response►
Aryan & Saeed's SQL►
Question 2: In the following data, test which pair of variables
are independent and which pairs are associated. First calculate
the goodness of fit of a homogenous model (all main effects and all
pair wise associations). Then progressively remove one of the pairs from the
model until you can find a set of associations that fit the data. R code► Slides►
Center for Medicare Services reimburses hip fracture treatment based on
one price for the hospital, physician or post acute care. Each
group continues to bill for their service as usual but at end of the
year the hospitals that have above average bundled costs are penalized
and hospitals that have below average bundled costs receive a financial
incentive. The hospital manager is interested to understand which
component of the operations contributes most to above average cost. The
data shows the number of hip fracture patients with above and below
average cost when cared for by various teams of clinicians. There
are five dimensions in the contingency table: orthopedic surgeon
(O), use of rehabilitation services (R), use of one of two skilled
nursing facilities (N), severity of patients' illness (S), and whether
the cost of the patient exceeded average bundled cost (A). You are
asked to fit a model that includes all pairwise interactions, including
OR, ON, OS, OA, RN, RS, RA, NS, NA, and SA. Calculate the fit of
the model to the data using chisquare. Then remove one of the
pairwise terms to see if it affects model performance significantly.
Continue to do so until you obtain a parsimonious model that describes
the relationships in the data and whose fit to the data cannot be
rejected. Verify that the associations shown in the
following Figure fits the result of your analysis. For every
associated pair in the model (significant or not significant), there
should be a link in the Figure. Identify which arc should not be
there and which arc should be there but is not there.

N: Skilled Nursing
Facility A 
Skilled Nursing Facility B 
S: High Severity 
Low
Severity 
High
Severity 
Low
Severity 
O: Orthopedic Surgeon 
R: Rehab Services 
A: > Bundle Cost 
< Bundle Cost 
> Bundle Cost 
< Bundle Cost 
> Bundle Cost 
< Bundle Cost 
> Bundle Cost 
< Bundle Cost 
Joe 
Yes 
405 
268 
453 
228 
23 
23 
30 
19 
Joe 
No 
13 
218 
28 
201 
2 
19 
1 
18 
Jim 
Yes 
1 
17 
1 
17 
0 
1 
1 
8 
Jim 
No 
1 
117 
1 
133 
0 
12 
0 
17 
Data adapted from Agresti A. Categorical Data Analysis, 3rd Edition, Wiley InterScience,
2013, page 381 
Question 3. Select 3 variables from the STAR*D data and analyze the
independence relationship among the variables.
 Read about the STAR*D study protocol. Protocol►
 Download data. Use instructor's last name as password. Must enter password twice.
Data 2010►
Data 2003►
 Select 3 variables
 Test 1 complete independence, 3 joint independence, and 3 homogenous associations.
 Identify the most parsimonious model whose fit to the data cannot be rejected
 Describe the meaning of your insight.
Arpitha and Shruti's Response►
Sheri Moinamin's Teach One
Video►
R Code►
Data►
More
For additional information (not part of the required reading), please see the following links:
 Independence and Bayesian networks Video►
 Introduction to probability models Read► Slide►
 Event time stratification Read►
 Bayes rule & independence
Video►
 Estimating effects of nursing in clinical teams Read►
 Breaking nominal variables into binary variables Read►
 The relationship between chisquare statistics from matched and unmatched analyses Read►
 Jeff Lin's analysis of independence of 3 variables Read►
 Decomposable (independent) subgraphs in 5 variable models
Read►
 Visualizing conditional probability
See►
This page is part of the course on Comparative Effectiveness Home► Emailâ–º
