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Supplement to Multilevel Regression Chapter
Presentations
Assignment
Question 1: The
following simulated data show the survival of patients in two tertiary
medical centers and 3 community hospitals. Should ambulances take
trauma victims to tertiary medical centers, by passing community
hospitals? Data►
-
Predict patient survival rates using patient-level variables: (a)
Presence of severe burns, (b) Head injury, (c) More than 65+ years
old, (d) Male gender. Identify the intercept for each hospital
-
Regress unexplained variation in survival probability on features of
the hospital, including whether it is a tertiary medical center
(Yes=1, No=0), or has a dedicated burn unit (Yes=1, No=0),.
|
Hospital |
Tertiary Center |
Has Burn Unit |
|
A |
1 |
0 |
|
B |
1 |
1 |
|
C |
0 |
0 |
|
D |
0 |
0 |
|
E |
0 |
0 |
-
Report the meaning of these two related regressions.
Question 2: In this problem, we approach multi-level
modeling through SQL. In particular, we address question 1 but
this time we use SQL instead of regression. In particular, for
each 2 medical centers follow these steps:
-
Select the data for the medical center.
- Use
SQL for Level 1 model:
-
In temporary table #Cancer, calculate the probability of
mortality for patients with cancer at different combination of
comorbidities (called strata). Call the probability
"Probability of Strata + Cancer". You can accomplish this by
selecting the probability where lung cancer =1 and grouping by
concatenation of all comorbidities. To concatenate string
variables you can use the + sign.
-
In temporary table #NoCancer, calculate the probability of
mortality for patients without cancer at different strata. Call
the probability "Probability of Strata + No Cancer".
-
Join the tables #Cancer and #NoCancer on Strata.
- Use
Regression for Level 2 model:
-
Regress the "Probability of Strata + Cancer" on "Probability of
Strata + No Cancer".
- Use
the intercept as the impact of cancer in the Medical Center.
-
Examine mortality rates at the center as a function of center's
distance to referral source and satisfaction of the patients in the
center.
|
Medical Center |
Distance |
% Satisfied |
|
Center1 |
50 |
79 |
|
Center2 |
80 |
82 |
|
Center3 |
70 |
80 |
|
Center4 |
70 |
79 |
|
Center5 |
80 |
79 |
|
Center6 |
70 |
83 |
|
Center7 |
80 |
81 |
Use the instructor's last name as the password for the data. Data► Shukri's
Video Part 1► Shukri's
Video Part 2► Shukri's
SQL Code► Answer
by Jehanzeb► Answer
by Shukri & Lavanya►
Question 3: Using multi-level modeling, calculate
the expected length of stay for the clinician and peer group, after
removing the effects of previous Myocardial Infarction (MI) and
Congestive Heart Failure (CHF). Compare the performance of the
clincian to the peer provider using the intercepts estimated for each
group. Answer
by Jehanzeb► Answer
by Shukri & Lavanya►
|
Clinician's Patients
|
Peer Provider's Patients
|
|
Case
|
Previous MI
|
CHF
|
Length of stay
|
Case
|
Previous MI
|
CHF
|
Length of stay
|
|
1
|
MI
|
CHF
|
6
|
1
|
MI
|
CHF
|
5
|
|
2
|
MI
|
No CHF
|
5
|
2
|
MI
|
CHF
|
5
|
|
3
|
MI
|
CHF
|
6
|
3
|
No MI
|
CHF
|
4
|
|
4
|
MI
|
CHF
|
6
|
4
|
No MI
|
No CHF
|
3
|
|
5
|
MI
|
CHF
|
6
|
5
|
No MI
|
CHF
|
4
|
|
6
|
MI
|
No CHF
|
5
|
6
|
No MI
|
CHF
|
4
|
|
7
|
MI
|
CHF
|
6
|
7
|
MI
|
CHF
|
5
|
|
8
|
MI
|
No CHF
|
5
|
8
|
MI
|
CHF
|
5
|
|
9
|
MI
|
CHF
|
6
|
9
|
MI
|
CHF
|
5
|
|
10
|
MI
|
No CHF
|
5
|
10
|
MI
|
CHF
|
5
|
|
11
|
MI
|
CHF
|
6
|
11
|
MI
|
CHF
|
5
|
|
12
|
No MI
|
CHF
|
4
|
12
|
No MI
|
No CHF
|
3
|
|
13
|
No MI
|
CHF
|
4
|
13
|
No MI
|
CHF
|
4
|
|
14
|
No MI
|
CHF
|
4
|
14
|
No MI
|
CHF
|
4
|
|
15
|
MI
|
CHF
|
6
|
15
|
No MI
|
CHF
|
4
|
|
16
|
MI
|
CHF
|
6
|
16
|
No MI
|
CHF
|
4
|
|
17
|
MI
|
CHF
|
6
|
17
|
No MI
|
CHF
|
4
|
|
18
|
MI
|
No CHF
|
5
|
18
|
No MI
|
No CHF
|
3
|
|
19
|
MI
|
No CHF
|
5
|
19
|
MI
|
No CHF
|
4
|
|
20
|
MI
|
CHF
|
6
|
20
|
MI
|
CHF
|
5
|
|
|
|
|
|
21
|
MI
|
CHF
|
5
|
|
|
|
|
|
22
|
MI
|
CHF
|
5
|
|
|
|
|
|
23
|
MI
|
No CHF
|
4
|
|
|
|
|
|
24
|
No MI
|
CHF
|
4
|
More
For additional information (not part of the required reading), please
see the following links:
- A
practical guide to multi-level modeling PubMed►
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