Cox regression with additive model with interactions for Nested Case-Control NCC study
wrapper_ncc_cox_regression_core_predictive2.RdReturns HRs with treatment effects in the biomarker subgroups and p-value of the interaction term
Usage
wrapper_ncc_cox_regression_core_predictive2(
data,
tte_var,
censor_var,
interaction1_var,
interaction2_var,
covariate_prog_vars = NULL,
covariate_pred_vars = NULL,
ncc_vars,
samplestat_var,
m,
match.var,
match.int,
variable_names = NULL,
caption = NULL,
print_pvalues = TRUE
)Arguments
- data
Data frame preprocessed for the NCC analysis with 'multipleNCC::wpl()'.
- tte_var
Name of the time-to-event variable. This variable must be numeric.
- censor_var
Name of the censor variable. It has to be numeric and encode 1 for event and 0 for censor.
- interaction1_var
Names of the first interaction variable. It would correspond to the biomarker. This variable must be a factor.
- interaction2_var
Name of the second interaction variable. It would correspond to the treatment arm. This variable must be a factor with two levels.
- covariate_prog_vars
Vector with names of prognostic covariates that are included in the formula of the additive model.
- covariate_pred_vars
Vector with names of predictive covariates that are included in the formula of the additive model.
- ncc_vars
Vector of names of covariates that were measured in the NCC.
- samplestat_var
Name of variable indicating samplestat values. See 'multipleNCC::wpl()'.
- m
See 'multipleNCC::wpl()'.
- match.var
See 'multipleNCC::wpl()'. It has to be a matrix of continuous values.
- match.int
See 'multipleNCC::wpl()'.
- variable_names
Named vector with variable names. If not supplied, variable names are created by replacing in column names underscores with spaces.
- caption
Caption for the table with results.
- print_pvalues
Logical. Whether to print p-values.