Cardiovascular risk factors

Description

Data from a study to investigate assocation between uric acid and various cardiovascular risk factors in developing countries (Heritier et. al. 2009). There are 474 men and 524 women aged 25-64.

Usage

data(CardioRiskFactors)

Format

A data frame with 998 observations on the following 14 variables.

age

Age of subject

bmi

Body Mass Index

waisthip

waist/hip ratio(?)

smok

indicator for regular smoker

choles

total cholesterol

trig

triglycerides level in body fat

hdl

high-density lipoprotien(?)

ldl

low-density lipoprotein

sys

systolic blood pressure

dia

diastolic blood pressure(?)

Uric

serum uric

sex

indicator for male

alco

alcohol intake (mL/day)

apoa

apoprotein A

Details

Data set and description taken from Heritier et. al. (2009) (c.f. Conen et. al. 2004). Some not discussed (in Section 3.5) of the text and their persummed meaning is listed followed by (?).

Source

Heritier, S., Cantoni, E., Copt, S., and Victoria-Feser, M. (2009), Robust Methods in Biostatistics, New York: John Wiley & Sons.

Conen, D., Wietlisbach, V., Bovet, P., Shamlaye, C., Riesen, W., Paccaud, F., and Burnier, M. (2004), Prevalence of hyperuricemia and relation of serum uric acid with cardiovascular risk factors in a developing country. BMC Public Health, http://www.biomedcentral.com/1471-2458/4/9.

Examples

data(CardioRiskFactors)
fitF<-rfit(Uric~bmi+sys+choles+ldl+sex+smok+alco+apoa+trig+age,data=CardioRiskFactors)
fitR<-rfit(Uric~bmi+sys+choles+ldl+sex,data=CardioRiskFactors)
drop.test(fitF,fitR)
summary(fitR)

Results

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> library(Rfit)
Loading required package: quantreg
Loading required package: SparseM

Attaching package: 'SparseM'

The following object is masked from 'package:base':

    backsolve

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Rfit/CardioRiskFactors.Rd_%03d_medium.png", width=480, height=480)
> ### Name: CardioRiskFactors
> ### Title: Cardiovascular risk factors
> ### Aliases: CardioRiskFactors
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(CardioRiskFactors)
> fitF<-rfit(Uric~bmi+sys+choles+ldl+sex+smok+alco+apoa+trig+age,data=CardioRiskFactors)
> fitR<-rfit(Uric~bmi+sys+choles+ldl+sex,data=CardioRiskFactors)
> drop.test(fitF,fitR)

Drop in Dispersion Test
F-Statistic     p-value 
     82.089       0.000 
> summary(fitR)
Call:
rfit.default(formula = Uric ~ bmi + sys + choles + ldl + sex, 
    data = CardioRiskFactors)

Coefficients:
              Estimate Std. Error t.value   p.value    
(Intercept) -122.60425   19.11525 -6.4140 2.191e-10 ***
bmi            5.16658    0.49163 10.5091 < 2.2e-16 ***
sys            0.67090    0.10485  6.3988 2.410e-10 ***
choles        60.39106    5.10978 11.8187 < 2.2e-16 ***
ldl          -53.32794    5.33347 -9.9987 < 2.2e-16 ***
sex          128.75255    5.00422 25.7288 < 2.2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Multiple R-squared (Robust): 0.4687287 
Reduction in Dispersion Test: 175.0439 p-value: 0 

> 
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> dev.off()
null device 
          1 
>