Patients who have ever smoked and carry the TGFB1+868 TC genotype, compared with all remaining patients. Forward stepwise selection was used to ...
Lipsitz, Laird and Harrington, 1991; Carey and Zeger, 1993). ... 2001), and mixed discrete and continuous (Dunson, 2000; Dunson, Chen and Harry, 2003).
As in univariate logistic regression, let π(x) represent the probability of an ... So,
the form is identical to univariate logistic regression, but now with more than one.
Hospital; PNUH, Pusan National University Hospital; SNUBH, Seoul National University. Bundang Hospital; IUHPH, Inje University Haeundae Paik Hospital.
Table 3. Multivariate logistic regression analysis: Factors associated with the depressive emotion among the informal caregivers of disabled elders (N=444).
Supplementary Table 2a: Multivariate Regression Results (Expanded Variable Set). Variable. Odds Ratio of Long. Recovery. Lower (95% CI) Upper (95% CI) p ...
Regression Parameters Derived from Stepwise Regression Analysis of Variables for Combination of Cardiovascular Diseases, Cancers and. COPD for Five ...
Regression Parameters Derived from Stepwise Regression Analysis of Variables for COPD for Five Population Density Groups. Variable. Lowest Density ...
S9 Table. Regression Parameters Derived from Stepwise Regression Analysis of Variables for Life Expectancy for Five Population Density Groups. Variable.
model that on one hand has usually too many variables ... improving the model selection process by taking into ..... Hos
Aug 23, 2014 - A Hybrid Approach of Stepwise Regression,. Logistic Regression, Support Vector Machine, and Decision. Tree for Forecasting Fraudulent ...
Chapter 12. Logistic Regression. 12.1 Modeling Conditional Probabilities. So far,
we either looked at estimating the conditional expectations of continuous.
6.2 Logistic Regression and Generalised Linear Models. 6.3 Analysis Using R. 6.3.1 ESR and Plasma Proteins. We can now fit a logistic regression model to the ...
This note follow Business Research Methods and Statistics using SPSS by ... http
://www.uk.sagepub.com/burns/website%20material/Chapter%2024%20-.
Slide 1. Logistic Regression – 14 Oct 2009. Logistic Regression. Essential
Medical Statistics. Applied Logisitic Regression Analysis. Kirkwood and Sterne.
Nov 28, 2006 - were detected by Colilert and Enterolert Quanti-Tray/2000 (IDEXX Laborato- ries Inc., Westbrook, ME) ...... A neural network ... culture and viral assay procedures for monitoring viruses in the environment. Appl. Environ.
Summary of linear stepwise regression analysis for seven variables of objective complexity predicting subjective complexity ratings of representational paintings ...
Model coefficients and odds ratios for logistic models reduced to significant parameters. pAF vs. SR logistic model with 10 variables coefficient. (95% CI).
XiEIG*Lambda*inv(XiEIG) ...... alpha (here « denotes the power used in data preprocessing: Ь. ¼ = Ь «¡Ь. Note that the ...... [theta,lambda] = ica(X,alpha). [theta ...
Summary of linear stepwise regression analysis for seven variables of objective complexity predicting subjective complexity ratings of IAPS pictures (N = 72).
Table S2. Multivariate stepwise logistic regression analysis of variables associated with ischaemic heart disease and myocardial infarction in patients with ...
Table S2. Multivariate stepwise logistic regression analysis of variables associated with ischaemic heart disease and myocardial infarction in patients with established RA after inclusion of smoking+VEGFA-2578A interaction term Ischaemic Heart Disease (model 1b) Variable
Regression
OR (95% CI)
Myocardial Infarction (model 2c) p value
Variable
coefficient a
Regression
OR (95% CI)
p value
coefficient
Smoking+VEGFA-2578 A
0.870
2.39 (1.31 – 4.36)
0.005
Hypercholesterolaemia
1.182
3.26 (1.72 – 6.20)
CRP ≥ 10 mg/l
1.036
d
a
Smoking+VEGFA-2578 A
1.344
3.83 (1.69 – 8.69)
0.001
0.0003
Hypercholesterolaemia
1.376
3.95 (1.90 – 8.24)
0.0002
2.82 (1.57 – 5.06)
0.0005
Hypertension
0.927
2.52 (1.25 – 5.12)
0.010
1.214
3.37 (1.36 – 8.34)
0.009
CRP ≥ 10 mg/l
0.920
2.51 (1.23 – 5.10)
0.011
Male
0.636
1.89 (1.08 – 3.31)
0.026
Male
0.769
2.16 (1.10 – 4.23)
0.025
e
Smoking+TGFB1+868 TC
0.797
2.22 (1.26 – 3.92)
0.006
e
0.734
2.08 (1.06 – 4.11)
0.034
Age, per year
0.028
1.03 (1.01 – 1.06)
0.049
Diabetes
a
Smoking+TGFB1+868 TC
Patients who have ever smoked and carry the VEGFA-2578 A allele, compared with all remaining patients; bPatients with IHD vs. without IHD; cPatients
with MI vs. all non-MI patients; dType I or type II diabetes; ePatients who have ever smoked and carry the TGFB1+868 TC genotype, compared with all remaining patients. Forward stepwise selection was used to determine the variables most strongly associated with IHD and MI. Variables excluded by the stepwise procedure for IHD were disease duration, hypertension, ESR, RF, anti-CCP, body mass index (BMI), methotrexate treatment, steroid treatment, erosive disease and nodular disease. Variables excluded by the stepwise procdure for MI were age, disease duration, ESR, RF, anti-CCP, BMI, diabetes, methotrexate treatment, steroid treatment, erosive disease and nodular disease.
