Chapter 1
1.
y NA 
s NA 
6.84  9.29  3.83  5.95  5.77 31.68

 6.336
5
5
(6.84  6.336) 2  (9.29  6.336) 2  (3.83  6.336) 2  (5.95  6.336) 2  (5.77  6.336) 2

5 1
 1.98 
cv NA  
100%  31.25%
 6.336 
15.73
 1.98
4
y A  6.24
s A  2.12
cv A  33.95%
Very similar levels
2.
^
1 
^
171
153
 0.9607  2 
 0.8596
178
178
3.
1273
 0.1153
11036
1293
b) P(C | B ) 
 0.1172
11035
c) No, very similar risks
a ) P(C | B) 
4.
a) P(C )  .009418
407
3702
 .002375 P(C | L) 
 .013974
171363
264913
c) 94.18, 23.75, 139.74
b) P(C | L) 
5.
Sensitivity: 45/50 = 0.90 (90%)
Specificity: 24/63 = 0.38 (38%)
PV+ : 45/84 = 0.54 (54%) PV- : 24/29 = 0.83 (83%)
Accuracy: (45+24)/113 = 0.61 (61%)
6.
Sensitivity: 116/140 = 0.83 (83%)
Specificity: 211/215 = 0.98 (98%)
+
PV : 116/120 = 0.97 (97%) PV : 211/235 = 0.90 (90%)
Accuracy: (116+211)/355 = 0.92 (92%)
7.
a)
b)
c)
d)
Cross-sectional
Cohort study
Randomized clinical trial
Historical controls
8.
a) Dependents: Ability to obtain erection (ordinal), EDITS (Numeric)
Independent: Dose (Numeric)
b) Approx. 41
c) Validity: It is accurately measuring patient satisfaction.
Reliability: Reproducability of responses within subjects
d) Yes
Chapter 2
9.
72  67.9


a ) P (Y  72)  P Z 
 1.46   .0721
2.8


60  63.3


b) P (Y  60)  P Z 
 1.27   .1020
2.6


d ) P ( Z  1.28)  .10  P(Y  143  1.28(15.5)  162.8)  .10
e) P( Z  1.645)  .05  P(Y  123  1.645(14.3)  99.5)  .05
f ) P (   1.96  Y    1.96 )  .95  219  1.96(39.2)  219  77  (142,296)
g ) P ( Z  2.33)  .01  P(Y  74  2.33(12.2)  45.6)  .99 for men
45.6  40


for women : P (Y  45.6)  P Z 
 0.77   .2206
7 .3


10.

a ) N   Y


b) N   Y


c) N   Y


d ) N   Y


 0.56 
25


1.3
 33.9 ,  Y 
 0.22 
35


3.0
 69.9 ,  Y 
 1.00 
9


14.3
 123 ,  Y 
 2.02 
50

 67.9 ,  Y 
2.8
11.
70  67.9


a) P(Y  70)  P Z 
 3.75   P( Z  3.09)  .0010
0.56


32  33.9


b) P(Y  32)  P Z 
 8.64   0
0.22


71  69.9 
 69  69.9
c) P(69  Y  71)  P
Z
  P(0.9  Z  1.1)  1  .1357  .1841  .6802
1
1


125  123


d ) P(Y  125)  P Z 
 0.99   .1611
2.02


Chapter 3
12.
H 0 : 1   2  0 H A : 1   2  0
TS : z obs 
RR : | z obs
30.6  38.6
(7.54) 2 (12.43) 2

37
36
|  z.05 / 2  z.025  1.96

 8.0
 3.33
2.4
P : 2 P( Z | 3.33 | 3.33)  2(.0010)  .002
Conclusion :Reject the null hypothesis , difference s exist
13.
H 0 : 1   2  0 H A :  1   2  0
TS : t obs 
RR : | t obs
40.31  44.89
2
2

 4.58
 1.43
3.21
(5.07)
(8.67)

13
9
|   t.05,139 2  t.05, 20  1.725
P : P(t  1.43)  .10 and  .05
Conclusion :Fail to Reject the null hypothesis , don' t conclude fluoxetine reduces POMS
14.
H Rank
PT Rank
Healthy MAT
Pre-Tran MAT
14
5
5.36
2.64
11
13
4.35
4.84
4
2.5
2.61
2.42
10
7
3.78
2.92
6
8
2.78
2.94
12
2.5
4.51
2.42
9
16
3.43
15.08
1
15
1.66
11.04
67
69
Since both T1 (67) and T2 (69) are above 49, do not conclude population means (or
medians) differ.
15.
9.3
 10.73
2.6 / 9 0.87
 t.05,8  1.860
TS : t obs 
RR : t obs
9.3

P : P(t  10.73)  0
16.
a.
Extensive : t obs 
3.7
 3.30
Poor : t obs 
1.8
 1.99 RR : t obs  t.05, 4  2.132
2.51 / 5
2.02 / 5
Since extensive metabolizers are significant, may be evidence that codeine is cause
b.
664  558
Codeine : TS : t obs 
Morphine : TS : t obs 
(95) 2 (114) 2

5
5
13.9  0.68

106
 1.60 RR :| t obs | t.05 / 2,552  t.025,8  2.306
66.4
(10.5) 2 (0.15) 2

5
5

13.22
 2.82 RR :| t obs | t.05 / 2,55 2  t.025,8  2.306
4.70
Codeine not significantly different. Morphine is significantly different
17.
a.
T + = 1+2+4+5+3+7+9 = 31
T - = 11+8+12+10+6 = 47 Fail to reject H0 (47>17)
b.
TS : t obs 
 0.053

0.285 / 20
 0.053
 0.83 RR : t obs  t.05,19  1.729
0.064
c.
No evidence that Orlistat increases levels of leutenizing hormones.
18.
H0: D = 0 (No placebo effect) HA: D > 0 (Placebo effect)
TS : z obs 
8.2
9.0 / 169

8.2
 11.8
0.69
RR : z obs  z.05  1.645 P  P( Z  11.8)  0
Strong evidence of placebo effect
19.
For each test, conclude decrease if tobs < -t.05, 6-1 = -2.015
High Fat : t obs 
443
854.6 / 6
 1.27 Mixed : t obs 
313
851.7 / 6
 0.90 No Fat : t obs 
 760
859.0 / 6
 2.17
20.
di
|di|
-0.1
2.8
-5.2
0.35
-2.55
-5.25
0.55
5.85
-1.5
-2.4
2.05
5.85
1.88
-1.85
-4.2
0.1
2.8
5.2
0.35
2.55
5.25
0.55
5.85
1.5
2.4
2.05
5.85
1.88
1.85
4.2
rank(|di|) T1
10
12
2
9
13
3
14.5
4
8
7
14.5
6
5
11
T+
1
10
12
2
9
13
3
14.5
4
8
7
14.5
6
5
11
63
57
Since 63 and 57 > 25, Don’t conclude differences exist in maximum concentrations by
fasting and fed states.
21.
a) Within regimen: Paired t-test, Signed Rank test (Before/After)
b) Across regimens: Independent sample t-test, Rank Sum test (Compare Mean
Before/After changes for dosing regimens)
Chapter 4
22.
95%CI for Problem 12:
(30.6  38.6)  1.96
(7.54) 2 (12.43) 2

 8.0  (1.96)( 2.41)  8.0  4.73  (12.73,3.27)
37
36
23.
95%CI for Problem 13:
(40.31  44.89)  2.086
(5.07) 2 (8.67) 2

 4.58  (2.086)(3.21)  4.58  6.70  (11.28,2.12)
13
9
24.
95%CI for Problem 15:
 2.6 
9.3  2.306
  9.3  2.306(0.87)  9.3  2.0  (7.3 , 11.3)
 9
Chapter 5
23. (Bad automated numbering)
a), b) , c)
^
E 
^
4
16
.0156
 0.0156  E 
 0.0615 RR 
 0.2537
257
260
.0615
d)
v
1  .0156 1  .0615

 0.2461  0.0587  0.3048
4
16

CI : 0.2537e 1.96
0.3048
,0.2537e1.96
0.3048
  (0.2357(0.5502),0.2357(1.8174))  (0.1297,0..4284)
Entire interval < 1, conclude antiplatelet trt reduces risk of primary cardiac event
e)
(RR-1)100% = (0.2357-1)100% = -76.43% , Reduction of 76% due to antiplatelet trt
24.
Trt \ Outcome
Xenical
Placebo
Total
^
^
 X  0.57
95%CI :
>5% Reduction
1140
620
1760
1.96(.0386)
Total
2000
2000
4000
0.57
1  0.57 1  0.31
 1.84
v

 .0015
0.31
1140
620
, 1.84e1.96(.0386)  (1.84(0.93) , 1.84(1.08))  (1.71 , 1.99)
 P  0.31
1.84e
<5% Reduction
860
1380
2240
RR 

Entire CI > 1, Conclude that Xenical increases likelihood of >5% Reduction in body
weight.
25.
OR 
80(395) 31600
1
1
1
1

 1.62 v 



 0.0311
230(85) 19550
80 230 85 395
95%CI :
1.62e
1.96(.1765)
v  0.1765

, 1.62e1.96(.1765)  (1.62(0.71) , 1.62(1.41))  (1.15 , 2.29)
Entire CI > 1, conclude odds of MI is higher for patients on CC Blockers. Cannot
conclude causation.
26.
^
174
248
0.0527
 0.0527  PLAC 
 0.0753 RR 
 0.70
3302
3293
0.0753
1  .0527 1  .0753
v

 0.0039
v  0.0621
174
248
95%CI : 0.70e 1.96(.0621) , 0.70e1.96(.0621)  (0.70(0.89) , 0.70(1.13))  (0.62 , 0.79)
^
 PRAV 


Entire CI < 1, conclude Pravastatin reduces risk of cardiac events.
v  .0386
27.
Death
Antisep
Control
Total
Survive
1
6
7
Total
Death
11
6
17
12
12
24
Antisep
Control
Total
Survive
0
7
7
Total
12
5
17
28.
McNemar’s Test:
TS : z obs 
19  10
19  10

9
 1.67
5.39
RR : | z obs |  1.96
Don’t conclude detection rates differ.
29.
Scandinavian/Cancer: Expected = 134(195)/410 = 63.7
2 = (63-63.7)2/63.7 = 0.008
Scandinavian/No Cancer: Expected = 134(215)/410 = 70.3
2 = (71-70.3)2/70.3 = 0.007
TS: 2obs =
.017+.015+.360+.325+.533+.484+.211+.191+.006+.006+.133+.123+.008+.007=2.419
RR: 2obs  2.05,(7-1)(2-1) = 2.05,6 = 12.592
among cancer rates
Don’t conclude ethnic differences exist
30.
Note: Column marginal totals are reversed, should be 74 and 75, respectively.
Experience
<=15
<=15
>=16
>=16
OTC Switch
No
Yes
No
Yes
obs
exp
28
50
46
25
38.7
39.3
35.3
35.7
obs-exp
-10.7
10.7
10.7
-10.7
chi-square
2.958398
2.913232
3.243343
3.207003
12.32198
Test Statistic: 2obs = 12.32
RR: 2obs  2.05,(2-1)(2-1) = 2.05,1 = 3.841
Conclude that attitudes toward switch differ by experience.
12
12
24
31.
22550  32565  10015

 0.1817
22550  32565
55115
 0.1817
b) TS : z obs 
 1.91 RR : | z obs |  z.025  1.96 Don' t reject, but P  0.05
0.095
c)  0.049  1.96(0.025)   0.049  0.049)  (0.098 , 0)
^
a)  
Borderline significan t negative associatio n
32.
a)
C=33(58+73+37+82)+18(58+73)+86(58+37)+82(58) = 8250+2358+8170+4756 = 23534
D=18(5+73+18+82)+86(5+18)+37(5+73)+82(5) = 3204+1978+2886+410 = 8478
^
b)  
23534  8478 15056

 0.47
23534  8478 32012
RR: zobs  z.05 = 1.645 Yes, Positive association
c) TS: zobs = 0.47/0.059 = 7.97
d ) n 2   ni2.  410 2  136 2  137 2  137 2   168100  56034  112066
n 2   n.2j  410 2  113 2  244 2  56 2   168100  75441  92659
^
B 
15056
0.5 (112066)(92659)

15056
 0.296
50951
e) 0.296  1.96(0.039)  0.296  0.076   (0.220 , 0.372) Conclude Positive assoc.
33.
T1 = 23(16)+98(102)+98(249.5)+58(369.5)+40(436.5)+10(471)+7(486.5) = 81821.5
T2 = 8(16)+43(102)+56(249.5)+28(369.5)+8(436.5)+11(471)+3(486.5) = 38964.5
 (81821.5) 2 (38964.5) 2
12

TS : H 

491(492) 
334
157

  3(492)  1476.1  1476  0.1

RR : H   .205,( 21)( 7 1)   .205, 6  12.592
Absolutely no evidence of fatigue differences among two drugs.
34.
Under independence, expect the following proportion of agreements (by chance):
p11  (.301)(.390)  .117
p 22  (.154)(.260)  .040
p33  (.545)(.350)  .191
p11  p 22  p33  .117  .040  .191  .348
Observed agrreement: .179+.057+.228 = .457

.457  .348 .109

 .167 Fairly low level of agreement between the reviewers.
1  .348
.652
Chapter 6
35.
305.9
 6.29
RR : Fobs  F.05,3, 43  2.84 Conclude means not all equal
48.6
b) PCA has lower means than others (all CI’s completely negative)
c) Tukey’s method gives narrower intervals (but Bonferroni is applicable to more
situations)
a) TS : Fobs 
36.
a)
Drug (i)
n_i
Buproprion(1)
Fluoxetine(2)
Paroxetine(3)
Sertraline(4)
Total
22
37
21
27
107
ybar_i
s_i
0.46
-0.49
-0.90
-0.49
0.80
0.97
0.73
1.25
n_i(ybar_i-ybar)^2 (n_i-1)s_i^2
15.5232
13.44
0.4477
33.8724
5.6784
10.658
0.3267
40.625
21.976
98.5954
SST
SSE
b)
Source
Trt (Drugs)
Err (Subjects)
df
4-1=3
107-4=103
SS
21.98
98.60
MS
21.98/3=7.33
98.6/103=0.96
F
7.33/0.96=7.64
107-1=106
Total
120.58
c)
TS: Fobs =7.64 RR: Fobs  F.05.3.103  2.70
exist)
Conclude means not all equal (Drug effects
d)
Trts (i,j)
(1,2)
(1,3)
(1,4)
(2,3)
(2.4)
(3,4)
ybar_i-ybar_j
0.46-(-0.49)=0.95
0.46-(-0.90)=1.36
0.46-(-0.49)=0.95
(-0.49-(-0.90))=0.41
(-0.49-(-0.49))=0
(-0.90-(-0.49))=-0.41
CV
0.624
0.708
0.666
0.634
0.587
0.675
Conclude
1 > 2
1 > 3
1 > 4
NSD*
NSD*
NSD*
NSD* = Not significantly different
e) Bupropion has higher mean than all others
37.
i
n_i
1
2
3
ybar_i
185
185
169
s_i
11.0
12.0
8.2
10.1
10.1
9.0
Sum
ybar=
10.46531
z.05/2(3) = z.0083 = 2.40
n_i(ybar_i-ybar)^2
52.8910454
435.7277801
867.242399
1355.861224
SST=1355.86
dfT=3-1=2
MST=677.93
F_obs=7.10
F(.05,2,536)=3.0
(n_i-1)s_i^2
18769.84
18769.84
13608
51147.68
SSE=51147.68
dfE=539-3=536
MSE=95.42
1 
 1
1v 2 : (11.0  12.0)  2.40 95.42

   1.0  2.40(1.02)   1.0  2.44  (3.44 ,  1.44)
 185 185 
1 
 1
1v3 : (11.0  8.2)  2.40 95.42

  2.8  2.40(1.04)  2.8  2.50  (0.30 , 5.30)
 185 169 
1 
 1
1v3 : (12.0  8.2)  2.40 95.42

  3.8  2.40(1.04)  3.8  2.50  (1.30 , 6.30)
 185 169 
38.
a.
T .S : H 
12
(2166.0  1700.2  682.7  73.5)  3(25)  92.448  75  17.448
24(25)
RR : H   .205, 41  7.815
Conclude Means are not all equal.
b.
Conclude: Placebo > 0.5, Placebo > 2.5 0.2 > 2.5 0.5 > 2.5
2.5
0.5
0.2 Placebo
Treatments connected by a line are not significantly different.
39.
TS : Fobs 
1.38
 0.19
7.17
RR : Fobs  F.05, 4, 28  2.71
No evidence of formulation differences
Much more variation in subjects
40.
Note that the rank for form 5 is incorrect for subject 4 in table in notes.
Subject
Rank1
1
2
3
4
5
6
7
8
Rank2
2
4
2
1
1
3
2
2
17
Total
Rank3
4
5
4
5
3
4
5
3
33
Rank4
5
1
5
3
4
5
4
4
31
Rank5
3
3
3
4
5
2
3
5
28
1
2
1
2
2
1
1
1
11
b=8 Subjects (blocks) k=5 Formulations (Treatments)
12
TS : Fr 
(17) 2  (33) 2  (31) 2  (28) 2  (11) 2  3(8)6  162.2  144  18.2
8(5)(6)


RR : Fr   .205,51  9.488
Conclude formulations are not all equal.
Conclude: 1<2, 2>5, 3>5, 4>5
5
1
4
3
No others are significantly different.
2
41.
a.
TS : Fobs 
44.70
 2.73
16.40
RR : Fobs  F.05, 2,92  3.10
Do not conclude interactio n exists
b.
Zidovudine :
77.71
 4.74
16.40
52.76

 3.22
16.40
TS : Fobs 
Disease State : TS : Fobs
RR : Fobs  F.05,1,92  3.95
AZT effect exists
RR : Fobs  F.05, 2,92  3.10 Disease state effects exist
42.
TS : Fobs 
0.0867
 2.44
0.0356
RR : Fobs  F.05,1, 22  4.30 No evidence of formulatio n difference s
43.
TS : Fobs 
64872.1
 24.21
2680.1
RR : Fobs  F.05,5, 24  2.62 Dose effects not all equal.
Chapter 7
44.
a.
^
1 
2.79
 0.3233
8.63
^
y  0.0536  0.3233 x
^
0 
14.682
 41.27 
 0.3233
  0.5873  0.5337  0.0536
25
 25 
s2 
(2.79) 2
8.63  0.42  0.018
25  2
23
1.32 
s  0.018  0.134
b.
0.134
 0.046
t.05 / 2, 25 2  t.025, 23  2.069
2.94
8.63
95%CI : 0.3233  2.069(0.046)  0.3233  0.0952  (.2281, .4185)
^
 
^
0.134
1

Entire CI is positive, conclude positive association.
c.
S yy  1.32 SSE  0.42 SSR  1.32  0.42  0.90
Source
Model
Error
Total
df
1
23
24
SS
0.90
0.42
1.32
MS
0.90
0.0183
---
F
49.29
d.
r
2.79
(8.63)(1.32)

2.79
 0.8266
3.375
r2 
0.90
 0.6818
1.32
45.
a.
r
 202.48
(22.47)( 2078.19)

 202.48
 0.94
216.095
b.
^
1 
 202.48
 9.01
22.47
c.
Yes
46.
z.025 = 1.96. Note that low Y values mean higher severity. The conclusions are
associations, not necessarily causes.
Variable
Body Temp
Sex (Male)
Prev Stroke
Atrial Fib
Leucocytosis
Infections
Est
S.E.
-3.70
4.68
-4.56
-5.07
-1.21
-10.74
t=Est/SE Conclusion
1.40 -2.64286 Severity increases with temp
1.66 2.819277 Males have lower severity
1.91 -2.38743 Previous stroke increases sev
2.05 -2.47317 Atrial Fib increases sev
0.28 -4.32143 Leucocytosis increases sev
2.43 -4.41975 Infections increase sev
47.
a.
^
y  1.2619  0.5623(3.25)  0.3896(1)  1.2619  1.8275  0.3896  3.4790
b.
0.3896
c.
0.2804
d.
SSR = 0.2804(12.4146) = 3.4811
Source
Model
Error
Total
SSE = 12.4146-3.4811 = 8.9335
SS
3.4811
8.9335
12.4146
df
2
112
114
MS
1.7406
0.0798
F
21.81
Chapter 8
48.
a.
2
TS : X
2
obs
 0.0694 

  15.20
 0.0178 
2
RR : X obs
  .205,1  3.841 Positive association
b.
e0.0694 = 1.072 (7.2% increase in odds of seizure per unit increase in dose)
c.
 4.0733  0.0694 ED50  0  ED50 
4.0733
 58.7
0.0694
49.
a.
^
y 3.8307 
93.9809(3.8307)
 46.99
3.8307  3.8307
^
y 10  67.95
^
y 50  87.29
^
y 100  90.51
b.
3.8307  1.96(0.2038)  3.8307  0.3994  (3.43 , 4.23)
c.
Not good: The curve is very flat at top...small range of %ACE inhib covers a wide range
of Enalaprilat concentrations
50.
a.
^
y 50  6.115 
27.620(50)
 6.115  7.907  14.022
124.656  50
^
y 100  18.409
b.
Large amount of subject-to-subject variation.
Chapter 9
51.
a.
Methylcholanthrene
i
t(i)
1
2
3
4
5
6
7
8
9
10
11
12
ni
14
15
16
17
18
19
20
21
22
23
28
31
di
46
45
43
37
33
28
18
15
9
8
7
6
1
2
6
4
5
10
3
6
1
1
1
1
lhat_i
0.021739
0.044444
0.139535
0.108108
0.151515
0.357143
0.166667
0.4
0.111111
0.125
0.142857
0.166667
S(t(i))
0.978261
0.934783
0.804348
0.717391
0.608696
0.391304
0.326087
0.195652
0.173913
0.152174
0.130435
0.108696
^
y 200  23.130
^
y 400  27.173
Dibenzanthracene
i
t(i)
ni
1
2
3
4
5
6
7
8
9
10
11
21
23
24
25
26
28
29
31
32
33
38
di
26
25
22
20
18
17
16
15
11
9
8
1
3
2
2
1
1
1
4
2
1
4
lhat_i
0.038462
0.12
0.090909
0.1
0.055556
0.058824
0.0625
0.266667
0.181818
0.111111
0.5
S(t(i))
0.961538
0.846154
0.769231
0.692308
0.653846
0.615385
0.576923
0.423077
0.346154
0.307692
0.153846
n2i
e1i
0.638889
1.267606
3.73913
2.349206
2.79661
5.185185
1.227273
2.560976
0.264706
0.969697
0.482759
0.518519
0.28
0.583333
0.272727
1.428571
0.625
0.357143
1.538462
27.08579
b.
squares= M
circles=D
c.
time (i)
14(1)
15(2)
16(3)
17(4)
18(5)
19(6)
20(7)
21(8)
22(9)
23(10)
24(11)
25(12)
26(13)
28(14)
29(15)
31(16)
32(17)
33(18)
38(19)
Sum
d1i
n1i
1
2
6
4
5
10
3
6
1
1
0
0
0
1
0
1
0
0
0
41
O1-E1 = 41-27.09 = 13.91
TS : TMH 
groups.
13.91
12.74

d2i
46
45
43
37
33
28
18
15
9
8
7
7
7
7
6
6
5
5
5
0
0
0
0
0
0
0
1
0
3
2
2
1
1
1
4
2
1
4
26
26
26
26
26
26
26
26
25
25
22
20
18
17
16
15
11
9
8
v1i
0.23071
0.457562
1.305349
0.922602
1.147411
2.072625
0.691476
1.380428
0.194637
0.665748
0.353151
0.369315
0.2016
0.395229
0.198347
0.816327
0.401042
0.229592
0.710059
12.74321
V1 = 12.74
13.91
 3.90
3.57
RR : | TMH | z.025  1.96 Conclude differences in
52.
a.
Bottom of Continuous Table:
ni
7
5
5
2
i
2/7=.2857
0
3/5=.6000
0
di
2
0
3
0
S(t(i))
.2114(1-.2857)=.1510
.1510
.1510(1-.6)=.0604
.0604
b.
circles=Intermittent
squares=Continuous
c.
Similar to t=8, then better survival for Continuous
53.
a.
Increased age leads to higher risk of death (CI for RR > 1)
Presence of Nausea/Vomiting leads to higher risk of death
Presence of Biliary disease not associated with risk of death (CI contains 1)
Low CD4 count associated with higher risk of death
b.
4.1 times higher (Point estimate)
1.72 to 9.76 times higher (Interval estimate)
c.
No
54.
a.
age<35, Male, IDU behavior, date=1984-1987, Infection=PCP, CD4<50, No ZDV, No
PCP Prophylaxis
b.
Age>35, Male, IDU behavior, Date=1984-1987, infection=CMV, CD4<50, Yes ZDV,
Yes PCP prophylaxis
c.
Age<35, Female, Ex-IDU behavior, Date=1988-1990, infection=KS, CD4>100, No
ZDV, No PCP prophylaxis
d.
CI for RR (0.87,1.22) contains 1, no association after controlling for other factors
e.
Same conclusion as d. (0.80,1.29)
f.
b : e 0.231000.53100.0300.058  e 0.85  2.34
c : e 00.0830.1510.2230.1390.69300  e 1.289  0.28