correlations: Correlation, p-value and t-statistic associated with the...
In rakheon/d2wlasso: Structured variable selection with weighted lasso

Correlation, p-value and t-statistic associated with the regression between response y and a covariate x after potential adjustment for a covariate z.

correlations(
  factor.z,
  x,
  z,
  response,
  partial = FALSE,
  ttest.pvalue = FALSE,
  regression.type
)

`factor.z`	logical. If TRUE, the fixed variable z is a factor variable.
`x`	(n by m) matrix of main covariates where m is the number of covariates and n is the sample size.
`z`	(n by 1) matrix of additional fixed covariate affecting response variable. Can be NULL.
`response`	a list containing: yy and delta. yy is an (n by 1) matrix corresponding to the response variable. If `regression.type` is "cox", `y` contains the observed event times. delta is an (n by 1) matrix that denotes censoring when `regression.type` is "cox" (1 denotes survival event is observed, 0 denotes the survival event is censored). Can be NULL.
`partial`	logical indicator. If TRUE, the partial correlation is computed between the response and each covariate in x after adjustment for z. If FALSE, the correlation is computed between the response and each covariate in x.
`ttest.pvalue`	logical indicator. If TRUE, p-value for each covariate is computed from univariate linear/cox regression of the response on each covariate. If FALSE, the p-value is computed from correlation coefficients between the response and each covariate. Default is FALSE.
`regression.type`	a character indicator that is either "linear" for linear regression or "cox" for Cox proportional hazards regression. Default is "linear".

pvalues:p-values for each x_k in the regression of y on x_k when partial=FALSE. Otherwise, p-values for each x_k in the regression of y on x_k and z when partial=TRUE.
estimate:Correlation between x_k and y when partial=FALSE. Otherwise, estimate is the partial correlation between x_k and y after adjustment for z when partial is TRUE.
tvalues:t-statistic with testing the significance of x_k in the regression of y on x_k and z when partial is TRUE. Otherwise it is the t-statistic when testing the significance of x_k in the regression of y on x_k when partial is FALSE.