`R/06_calc_myreg_helpers_coef.R`

`theta_hat.Rd`

This function extracts `coef`

from `yreg_fit`

and 3s with zeros appropriately to create a named vector consistently having the following elements:
`(Intercept)`

(a zero element is added for `yreg = "survCox"`

for which no intercept is estimated (the baseline hazard is left unspecified)),
`avar`

,
`mvar`

,
`avar:mvar`

(a zero element is added when `interaction = FALSE`

).
`cvar`

(this part is eliminated when `cvar = NULL`

),
`emm_ac_yreg`

(this part is eliminated when `emm_ac_yreg = NULL`

),
`emm_mc_yreg`

(this part is eliminated when `emm_mc_yreg = NULL`

).

```
theta_hat(
yreg,
yreg_fit,
avar,
mvar,
cvar,
emm_ac_yreg = NULL,
emm_mc_yreg = NULL,
interaction
)
```

- yreg
A character vector of length 1. Outcome regression type:

`"linear"`

,`"logistic"`

,`"loglinear"`

,`"poisson"`

,`"negbin"`

,`"survCox"`

,`"survAFT_exp"`

, or`"survAFT_weibull"`

.- yreg_fit
Model fit object for yreg (outcome model).

- avar
A character vector of length 1. Treatment variable name.

- mvar
A character vector of length 1. Mediator variable name.

- cvar
A character vector of length > 0. Covariate names. Use

`NULL`

if there is no covariate. However, this is a highly suspicious situation. Even if`avar`

is randomized,`mvar`

is not. Thus, there are usually some confounder(s) to account for the common cause structure (confounding) between`mvar`

and`yvar`

.- emm_ac_yreg
A character vector of length > 0. Effect modifiers names. The covariate vector in treatment-covariate product term in the outcome model.

- emm_mc_yreg
A character vector of length > 0. Effect modifiers names. The covariate vector in mediator-covariate product term in outcome model.

- interaction
A logical vector of length 1. The presence of treatment-mediator interaction in the outcome model. Default to TRUE.

A named numeric vector of coefficients.