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Andreas Gammelgaard Damsbo 2025-04-09 12:31:08 +02:00
commit 347490605f
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20 changed files with 573 additions and 538 deletions
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90
R/regression_model.R
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@ -97,7 +97,7 @@ regression_model <- function(data,
if (is.null(fun)) auto.mode <- TRUE
if (auto.mode) {
if (isTRUE(auto.mode)) {
if (is.numeric(data[[outcome.str]])) {
fun <- "stats::lm"
} else if (is.factor(data[[outcome.str]])) {
@ -318,7 +318,7 @@ supported_functions <- function() {
design = "cross-sectional",
out.type = "dichotomous",
fun = "stats::glm",
args.list = list(family = stats::binomial(link = "logit")),
args.list = list(family = "binomial"),
formula.str = "{outcome.str}~{paste(vars,collapse='+')}",
table.fun = "gtsummary::tbl_regression",
table.args.list = list()
@ -326,7 +326,7 @@ supported_functions <- function() {
polr = list(
descr = "Ordinal logistic regression model",
design = "cross-sectional",
out.type = c("ordinal","categorical"),
out.type = c("ordinal", "categorical"),
fun = "MASS::polr",
args.list = list(
Hess = TRUE,
@ -449,6 +449,7 @@ get_fun_options <- function(data) {
#' )
#' ls <- regression_model_list(data = default_parsing(mtcars), outcome.str = "cyl", fun.descr = "Ordinal logistic regression model")
#' summary(ls$model)
#' ls <- regression_model_list(data = default_parsing(mtcars), outcome.str = "mpg", fun.descr = "Linear regression model")
#'
#' ls <- regression_model_list(data = default_parsing(gtsummary::trial), outcome.str = "trt", fun.descr = "Logistic regression model")
#' tbl <- gtsummary::tbl_regression(ls$model, exponentiate = TRUE)
@ -458,7 +459,7 @@ get_fun_options <- function(data) {
#' outcome.str = "trt",
#' fun = "stats::glm",
#' formula.str = "{outcome.str}~.",
#' args.list = list(family = stats::binomial(link = "logit"))
#' args.list = list(family = "binomial")
#' )
#' tbl2 <- gtsummary::tbl_regression(m, exponentiate = TRUE)
#' broom::tidy(ls$model)
@ -509,20 +510,27 @@ regression_model_list <- function(data,
}
}
parameters <- list(
outcome.str = outcome.str,
fun = fun.c,
formula.str = formula.str.c,
args.list = args.list.c
)
model <- do.call(
regression_model,
list(
data = data,
outcome.str = outcome.str,
fun = fun.c,
formula.str = formula.str.c,
args.list = args.list.c
append_list(parameters,
data = data, "data"
)
)
code <- glue::glue(
"{fun.c}({paste(Filter(length,list(glue::glue(formula.str.c),'data = data',list2str(args.list.c))),collapse=', ')})"
)
parameters_print <- list2str(Filter(length,
modifyList(parameters, list(
formula.str = glue::glue(formula.str.c),
args.list = NULL
))))
code <- glue::glue("FreesearchR::regression_model(data,{parameters_print}, args.list=list({list2str(args.list.c)}))",.null = "NULL")
list(
options = options,
@ -566,6 +574,7 @@ list2str <- function(data) {
#' lapply(broom::tidy) |>
#' dplyr::bind_rows()
#' ms <- regression_model_uv_list(data = default_parsing(mtcars), outcome.str = "mpg", fun.descr = "Linear regression model")
#' ms$code
#' lapply(ms$model, broom::tidy) |> dplyr::bind_rows()
#' }
regression_model_uv_list <- function(data,
@ -628,28 +637,43 @@ regression_model_uv_list <- function(data,
# )
# )
model <- vars |>
lapply(\(.var){
do.call(
regression_model,
list(
data = data[c(outcome.str, .var)],
outcome.str = outcome.str,
fun = fun.c,
formula.str = formula.str.c,
args.list = args.list.c
)
)
})
vars <- "."
code_raw <- glue::glue(
"{fun.c}({paste(Filter(length,list(glue::glue(formula.str.c),'data = .d',list2str(args.list.c))),collapse=', ')})"
parameters <- list(
outcome.str = outcome.str,
fun = fun.c,
formula.str = formula.str.c,
args.list = args.list.c
)
code <- glue::glue("lapply(data,function(.d){code_raw})")
model <- vars |>
lapply(\(.var){
out <- do.call(
regression_model,
append_list(parameters,
data = data[c(outcome.str, .var)], "data"
)
)
## This is the very long version
## Handles deeply nested glue string
code <- glue::glue("dplyr::select(data,{paste0(paste(names(data[c(outcome.str, .var)]),collapse=','))})|>\nFreesearchR::regression_model({list2str(modifyList(parameters,list(formula.str = glue::glue(gsub('vars','.var',formula.str.c)))))})")
REDCapCAST::set_attr(out, code, "code")
})
# vars <- "."
#
# code_raw <- glue::glue(
# "{fun.c}({paste(Filter(length,list(glue::glue(formula.str.c),'data = .d',list2str(args.list.c))),collapse=', ')})"
# )
# browser()
# code <- glue::glue("lapply(data,function(.d){code_raw})")
code <- model |>
lapply(\(.x)REDCapCAST::get_attr(.x, "code")) |>
purrr::reduce(c) |>
(\(.x){
paste0("list(\n", paste(.x, collapse = ",\n"), ")")
})()
list(
options = options,