`dm_Rdate_FPR`

creates design matrices for false positive rate regressions;
can also be used to standardize dates.

## Arguments

- Rdate
a vector of dates of R format

- Y
binary case/control status; 1 for case; 0 for controls

- effect
The design matrix for "random" or "fixed" effect; Default is "fixed". When specified as "fixed", it produces standardized R-format dates using control's mean and standard deviation; When specified as "random", it produces

`num_knots_FPR`

columns of design matrix for thin-plate regression splines (TPRS) fitting. One needs both "fixed" and "random" in a FPR regression formula in`model_options`

to enable TPRS fitting. For example,`model_options$likelihood$FPR_formula`

can be`~ AGECAT+HIV+dm_Rdate_FPR(ENRLDATE,Y,"fixed")+dm_Rdate_FPR(ENRLDATE,Y,"random",10)`

means FPR regression with intercept, main effects for 'AGECAT' and 'HIV', and TPRS bases for 'ENRLDATE' using 10 knots placed at 10 equal-probability-spaced sample quantiles.- num_knots_FPR
number of knots for FPR regression; default is

`NULL`

to accommodate fixed effect specification.

## Value

Design matrix for FPR regression:

`Z_FPR_ctrl`

transformed design matrix for FPR regression for controls`Z_FPR_case`

transformed design matrix for borrowing FPR regression from controls to cases. It is obtained using control-standardization, and square-root the following matrix (\(\Omega\)]) with (\(j_1\),\(j_2\)) element being $$\Omega_{j_1j_2}=\|knots_{j_1}-knots_{j_2}\|^3$$.