vif_adj_cont_0: VIF for logistic regression with adjustments (continuous var;...
In cheungngo/PrevCorr: Statistical methods for prevalence and correlate studies
Description
Usage
Arguments
Value
Description
VIF for logistic regression with adjustments (continuous var; including zero cont vars)
Usage
1
vif_adj_cont_0(datay, datax, j, i, adj)
Arguments
datay
: dataframe that contains the first variable, e.g. disease diagnosis status
datax
: dataframe that contains the second variable
j
: column number with respect to datay
i
: column number with respect to datax
adj
: column numbers for adjustments
Value
VIF for each variables
cheungngo/PrevCorr documentation built on Feb. 27, 2021, 9:10 p.m.
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Description Usage Arguments Value
Description
VIF for logistic regression with adjustments (continuous var; including zero cont vars)
Usage
1 | vif_adj_cont_0(datay, datax, j, i, adj)
|
Arguments
datay |
: dataframe that contains the first variable, e.g. disease diagnosis status |
datax |
: dataframe that contains the second variable |
j |
: column number with respect to datay |
i |
: column number with respect to datax |
adj |
: column numbers for adjustments |
Value
VIF for each variables
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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