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Table 4 The parameters calculated via stepwise logistic regression analysis

From: Novel biomarker genes which distinguish between smokers and chronic obstructive pulmonary disease patients with machine learning approach

 

Estimate

Std. Error

Z value

Pr(>|Z|)

(Intercept) NS|SMK

1.6715

0.4229

3.953

7.73E−05

ADM

−2.2568

1.0247

−2.202

0.027641

AREG

2.0152

1.0407

1.936

0.052820

CXCR4

−3.1177

1.4308

− 2.179

0.029336

EFNA1

3.7889

1.9572

1.936

0.052882

EGLN3

−4.0571

1.7627

−2.302

0.021357

FBXO32

−3.8824

2.4113

−1.610

0.107376

HILPDA

3.2193

0.8100

3.974

7.06E−05

IGFBP3

−8.2992

2.3747

−3.495

0.000474

SLC7A11

−3.5355

1.2516

−2.825

0.004730

TXNIP

−5.6745

1.4851

−3.281

1.33E−04

WNT5A

2.7391

0.8231

3.328

8.75E−04

(Intercept) SMK|COPD

−0.8555

0.2144

−3.990

6.61E−05

AREG

−1.3039

0.7058

−1.847

0.06469

DUSP6

1.4688

0.6254

2.349

0.01885

EFNA1

2.3861

0.9058

2.634

0.00843

TXNIP

−0.8847

0.5167

−1.712

8.69E−02