Example of running a series of univariate models and multivariate models with the logistic macro

1
Model Variable Value # Outcome = 1/
# subgroup
(% Outcome = 1)
Odds
Ratio
Lower
95% CI
Upper
95% CI
P-Value
Type 3
P-Value
1 age     1.10 1.08 1.12 <.0001 0.0001
age (per 10 units)     2.5 2.2 3.0
Outcome (+)Died Yes=225
Outcome (-)Died No =275
-2 Log L 477.125
H-L Test 10 groups         0.0028

2 age 20-35 18/129 (14.0%) 1.00
age 36-51 22/125 (17.6%) 1.32 0.67 2.6 0.43   <.0001
age 52-66 80/128 (62.5%) 10.3 5.6 19.0 <.0001
age 67-80 105/118 (89.0%) 50 23 107 <.0001

Outcome (+)Died Yes=225
Outcome (-)Died No =275
-2 Log L 471.802
H-L Test 4 groups         1.00
Pink cells indicate effects with p<0.05
Red cells indicate evidence for violations of model assumptions.

 Example of running a series of univariate models and multivariate models with the logistic macro

2
Model Variable Value # Outcome = 1/
# subgroup
(% Outcome = 1)
Odds
Ratio
Lower
95% CI
Upper
95% CI
P-Value
Type 3
P-Value

3 female No 108/235 (46.0%) 1.00
female Yes 117/265 (44.2%) 0.93 0.65 1.32 0.69

Outcome (+)Died Yes=225
Outcome (-)Died No =275
-2 Log L 687.975
H-L Test < 3 groups

4 treatment Placebo 118/250 (47.2%) 1.00
treatment Active 107/250 (42.8%) 0.84 0.59 1.19 0.32

Outcome (+)Died Yes=225
Outcome (-)Died No =275
-2 Log L 687.161
H-L Test < 3 groups

Pink cells indicate effects with p<0.05
Red cells indicate evidence for violations of model assumptions.

 Example of running a series of univariate models and multivariate models with the logistic macro

3
Model Variable Value # Outcome = 1/
# subgroup
(% Outcome = 1)
Odds
Ratio
Lower
95% CI
Upper
95% CI
P-Value
Type 3
P-Value
5 bmi 16.58-24.24 28/125 (22.4%) 1.00
bmi 24.26-27.06 54/126 (42.9%) 2.6 1.50 4.5 0.0007   <.0001
bmi 27.08-29.89 60/124 (48.4%) 3.2 1.88 5.6 <.0001
bmi 29.9-37.06 83/125 (66.4%) 6.8 3.9 12.0 <.0001

Outcome (+)Died Yes=225
Outcome (-)Died No =275
-2 Log L 636.432
H-L Test 4 groups         1.00

6 obese No 144/379 (38.0%) 1.00
obese Yes 81/121 (66.9%) 3.3 2.1 5.1 <.0001

Outcome (+)Died Yes=225
Outcome (-)Died No =275
-2 Log L 656.911
H-L Test < 3 groups
Pink cells indicate effects with p<0.05
Red cells indicate evidence for violations of model assumptions.

 Example of running a series of univariate models and multivariate models with the logistic macro

4
Model Variable Value # Outcome = 1/
# subgroup
(% Outcome = 1)
Odds
Ratio
Lower
95% CI
Upper
95% CI
P-Value
Type 3
P-Value

7 overweight No 162/368 (44.0%) 1.00
overweight Yes 63/132 (47.7%) 1.16 0.78 1.73 0.46

Outcome (+)Died Yes=225
Outcome (-)Died No =275
-2 Log L 687.601
H-L Test < 3 groups

8 age 20-35 18/129 (14.0%) 1.00
age 36-51 22/125 (17.6%) 1.27 0.64 2.5 0.49   <.0001
age 52-66 80/128 (62.5%) 9.6 5.1 18.1 <.0001
age 67-80 105/118 (89.0%) 43 19.8 95 <.0001

treatment Placebo 118/250 (47.2%) 1.00
treatment Active 107/250 (42.8%) 0.97 0.62 1.53 0.90

Pink cells indicate effects with p<0.05
Red cells indicate evidence for violations of model assumptions.

 Example of running a series of univariate models and multivariate models with the logistic macro

5
Model Variable Value # Outcome = 1/
# subgroup
(% Outcome = 1)
Odds
Ratio
Lower
95% CI
Upper
95% CI
P-Value
Type 3
P-Value
female No 108/235 (46.0%) 1.00
female Yes 117/265 (44.2%) 0.91 0.57 1.45 0.69

weightcat Not over 81/247 (32.8%) 1.00
weightcat Overweight 63/132 (47.7%) 0.99 0.57 1.72 0.96   0.19
weightcat Obese 81/121 (66.9%) 1.65 0.91 3.0 0.096

Outcome (+)died Yes=225
Outcome (-)died No =275
-2 Log L 468.149
H-L Test 10 groups         0.58

Pink cells indicate effects with p<0.05
Red cells indicate evidence for violations of model assumptions.