Description Usage Format Details

We created the 'wqs_data' dataset to show how to use this function. These data reflect
59 exposure concentrations simulated from a distribution of 34 PCB exposures and
25 phthalate biomarkers measured in subjects participating in the NHANES study (2001-2002).
Additionally, 8 outcome measures were simulated applying different distributions and fixed
beta coefficients to the predictors. In particular 'y' and 'yLBX' were simulated from
a normal distribution, 'ybin' and 'ybinLBX' from a binomial distribution, 'ymultinom' and
'ymultinomLBX' from a multinomial distribution and 'ycount' and 'ycountLBX' from a Poisson
distribution.
The regression coefficients used to generate the outcomes 'yLBX', 'ybinLBX' and
'ycountLBX' were set to:

LBX105LA = 0.3

LBX138LA = 0.6

LBX157LA = 0.2

LBXD02LA = 0.45

LBXD04LA = 0.15

LBXF06LA = 0.3

LBXF07LA = 0.45

then the following terms were added to generate the variables 'y', 'ybin' and
'ycount':

URXMC1 = 0.15

URXMOH = 0.45

URXP02 = 0.2

URXP10 = 0.3

URXUCR = 0.2

All the remaining coefficients were set to 0.

The coefficients to generate 'ymultinomLBX' were set as below:

level B:

LBX138LA = 0.8

LBXD04LA = 0.2

level C:

LBX105LA = 0.4

LBX157LA = 0.3

LBXD02LA = 0.6

LBXF06LA = 0.4

LBXF07LA = 0.6

and the following terms were added for 'ymultinom':

level B:

URXMC1 = 0.2

URXP02 = 0.3

URXP10 = 0.4

URXUCR = 0.3

level C:

URXMOH = 0.6

The 'sex' variable was also simulated to allow to adjust for a covariate in the model.
This dataset can thus be used to test the 'gWQS' package by analyzing the mixed effect
of the 59 simulated PCBs on the continuous, binary or count outcomes, with adjustments
for covariates.

1 |

A data frame with 500 rows and 68 variables

- y
continuous outcome generated considerig all the predictors

- yLBX
continuous outcome generated considerig only PCBs

- ybin
binary outcome generated considerig all the predictors

- ybinLBX
binary outcome generated considerig only PCBs

- ymultinom
multinomial outcome generated considerig all the predictors

- ymultinomLBX
multinomial outcome generated considerig only PCBs

- ycount
count outcome generated considerig all the predictors

- ycountLBX
count outcome generated considerig only PCBs

- sex
covariate, gender of the subject

- LBX
34 exposure concentrations of PCB

- URX
25 exposure concentrations of phthalates

...

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