Adult respiratory distress syndrome (ARDS) is a complication in many critically ill patients. Rocker and coworkers¹ developed a logistic regression model for predicting ARDS in a patient based on three variables: ● PI Protein accumulation index. O Arterial oxygen in kPa. ● A Age in years. Some of the output from the SPSS calculation for this model is given below. Omnibus Testª Likelihood Ratio Chi- Square 3 Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen/ kPa, Age / years 58.418 Parameter (Intercept) Protein Accumulation Index a. Compares the fitted model against the intercept-only model. df B 6.649 1.554 -.498 -.057 1ª Std. Error 2.2453 4371 Sig. .1631 0257 .000 Lower 2.249 .697 95% Wald Confidence interval Arterial Oxygen/kPa Age / years (Scale) Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years a. Fixed at the displayed value. -.818 -.107 Parameter Estimates Upper Source (Intercept) Protein Accumulation. Index 11.050 2,411 -.179 -.006 Tests of Model Effects Hypothesis Test Wald Chi- Square 8.770 12.643 9.330 4.848 Arterial Oxygen/kPa Age / years Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years df 1 1 Wald Chi- Square 1 1 8.770 12.643 9.330 4.848 Sig. .003 .000 Type III .002 .028 df Exp(B) 772.219 4.731 1 .608 .945 1 1 1 Sig. .003 .000 .002 .028 95% Wald Confidence Interval for Exp(B) Lower 9.474 2.009 .441 .898 Upper 62941.590 11.143 .837 .994
Adult respiratory distress syndrome (ARDS) is a complication in many critically ill patients. Rocker and coworkers¹ developed a logistic regression model for predicting ARDS in a patient based on three variables: ● PI Protein accumulation index. O Arterial oxygen in kPa. ● A Age in years. Some of the output from the SPSS calculation for this model is given below. Omnibus Testª Likelihood Ratio Chi- Square 3 Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen/ kPa, Age / years 58.418 Parameter (Intercept) Protein Accumulation Index a. Compares the fitted model against the intercept-only model. df B 6.649 1.554 -.498 -.057 1ª Std. Error 2.2453 4371 Sig. .1631 0257 .000 Lower 2.249 .697 95% Wald Confidence interval Arterial Oxygen/kPa Age / years (Scale) Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years a. Fixed at the displayed value. -.818 -.107 Parameter Estimates Upper Source (Intercept) Protein Accumulation. Index 11.050 2,411 -.179 -.006 Tests of Model Effects Hypothesis Test Wald Chi- Square 8.770 12.643 9.330 4.848 Arterial Oxygen/kPa Age / years Dependent Variable: ARDS Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years df 1 1 Wald Chi- Square 1 1 8.770 12.643 9.330 4.848 Sig. .003 .000 Type III .002 .028 df Exp(B) 772.219 4.731 1 .608 .945 1 1 1 Sig. .003 .000 .002 .028 95% Wald Confidence Interval for Exp(B) Lower 9.474 2.009 .441 .898 Upper 62941.590 11.143 .837 .994
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
Would someone familiar with SPSS be able to help me with sub-question d please?
Transcribed Image Text:Question 3
Adult respiratory distress syndrome (ARDS) is a complication in many critically ill patients. Rocker and
coworkers¹ developed a logistic regression model for predicting ARDS in a patient based on three variables:
PI Protein accumulation index.
O Arterial oxygen in kPa.
A Age in years.
Some of the output from the SPSS calculation for this model is given below.
Omnibus Testª
●
●
●
Likelihood
Ratio Chi-
Square
58.418
Parameter
(Intercept)
Protein Accumulation
Index
a. Compares the fitted model
against the intercept-only
model.
df
3
Dependent Variable: ARDS
Model: (Intercept), Protein
Accumulation Index, Arterial Oxygen /
kPa, Age / years
B
6.649
1.554
-.498
-.057
1ª
Std. Error
2.2453
.4371
Sig.
.1631
.0257
.000
Lower
2.249
.697
95% Wald Confidence Interval
-.818
-.107
Arterial Oxygen/kPa
Age / years
(Scale)
Dependent Variable: ARDS
Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa, Age / years
a. Fixed at the displayed value.
Parameter Estimates
Upper
Source
(Intercept)
Protein Accumulation
Index
Arterial Oxygen / kPa
Age / years
Dependent Variable: ARDS
11.050
2.411
-.179
-.006
Tests of Model Effects
Hypothesis Test
Wald Chi-
Square
8.770
12.643
9.330
4.848
df
Model: (Intercept), Protein Accumulation Index, Arterial Oxygen / kPa,
Age / years
1
1
1
Wald Chi-
Square
1
8.770
12.643
9.330
4.848
Sig.
.003
.000
Type III
.002
.028
df
Exp (B)
772.219
4.731
1
1
.608
.945
1
1
Sig.
.003
.000
.002
.028
95% Wald Confidence Interval
for Exp(B)
Lower
9.474
2.009
.441
.898
a)
Comment on the overall significance of the model.
b) Comment on whether or not there is there evidence that the Protein Accumulation Index is
associated with ARDS.
Upper
62941.590
11.143
c) By considering the model coefficients, comment on how each of the three variables affects the
probability of a patient having ARDS.
.837
.994
Transcribed Image Text:d) The odds of a patient having ARDS, 2, are related to the model through the following equation:
Р
² (₁²P)
G
-
In Ω = ln
ii)
=
bo + b₁ PI + b₂0 + b3 A
where P is the probability of a patient having ARDS. Using the coefficients from the SPSS output,
determine
i)
The odds, n, that a 65-year-old patient with low arterial oxygen, 6 kPa, and high protein
index, 5.5, has ARDS.
The odds, 2, that a 65-year-old patient with high arterial oxygen, 20 kPa, and low protein
index, 0.2, has ARDS.
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