moved some helper functions to internal

NAMESPACE

@@ -7,9 +7,6 @@ S3method(IPD_stats,maic)
 S3method(IPD_stats,stc)
 export(ALD_stats)
 export(IPD_stats)
-export(gcomp_ml.boot)
-export(gcomp_ml_log_odds_ratio)
-export(gcomp_stan)
 export(marginal_treatment_effect)
 export(marginal_variance)
 export(mimR)

R/marginal_stats.R → R/ALD_stats.R

@@ -1,4 +1,19 @@
 
+#' Aggregate-level data mean and variance statistics
+#'
+#' @param ald Aggregate-level trial data
+#' @param treatments Treatment labels list; default `B`, `C`
+#'
+#' @return List of marginal treatment effect mean and variance
+#' @seealso [marginal_treatment_effect()], [marginal_variance()]
+#' @export
+#'
+ALD_stats <- function(ald, treatments = list("B", "C")) {
+  list(mean = marginal_treatment_effect(ald, treatments),
+       var = marginal_variance(ald, treatments))
+}
+
+
 #' Marginal effect variance using the delta method
 #' 
 #' Calculate
@@ -67,19 +82,3 @@ trial_treatment_effect <- function(ald, tid) {
   var_string <- glue::glue("log(ald$y.{tid}.sum*(ald$N.{tid} - ald$y.{tid}.sum))")
   eval(parse(text = var_string))
 }
-
-
-#' Aggregate-level data mean and variance statistics
-#'
-#' @param ald Aggregate-level trial data
-#' @param treatments Treatment labels list; default `B`, `C`
-#'
-#' @return List of marginal treatment effect mean and variance
-#' @seealso [marginal_treatment_effect()], [marginal_variance()]
-#' @export
-#'
-ALD_stats <- function(ald, treatments = list("B", "C")) {
-  list(mean = marginal_treatment_effect(ald, treatments),
-       var = marginal_variance(ald, treatments))
-}
-

R/gcomp_ml.R

@@ -9,7 +9,7 @@
 #'
 #' @return Mean difference in expected log-odds
 #' @seealso [strategy_gcomp_ml()], [gcomp_ml_log_odds_ratio()]
-#' @export
+#' @keywords internal
 #' 
 gcomp_ml.boot <- function(data, indices,
                           formula = as.formula("y ~ X3 + X4 + trt*X1 + trt*X2")) {
@@ -31,7 +31,7 @@ gcomp_ml.boot <- function(data, indices,
 #' @return Difference of log-odds 
 #' @seealso [strategy_gcomp_ml()], [gcomp_ml.boot()]
 #' @importFrom copula normalCopula mvdc rMvdc
-#' @export
+#' @keywords internal
 #'
 gcomp_ml_log_odds_ratio <- function(formula, dat) {
   browser()  ## what is type of data?...

R/gcomp_stan.R

@@ -11,7 +11,7 @@
 #' @return A list of \eqn{y^*_A} and \eqn{y^*_C} posterior predictions
 #' @importFrom copula normalCopula mvdc rMvdc
 #' @importFrom rstanarm stan_glm posterior_predict
-#' @export
+#' @keywords internal
 #'
 gcomp_stan <- function(formula = as.formula("y ~ X3 + X4 + trt*X1 + trt*X2"),
                        ipd, ald) {

R/maic.R

@@ -10,6 +10,7 @@
 #' 
 #' @references
 #' \insertRef{Signorovitch2010}{mimR}
+#' @keywords internal
 #' 
 maic_weights <- function(X_EM) {
   X_EM <- as.matrix(X_EM)
@@ -43,6 +44,7 @@ maic_weights <- function(X_EM) {
 #' @template args-ald
 #' @return Fitted treatment coefficient is marginal effect for _A_ vs _C_
 #' @seealso [IPD_stats.maic()]
+#' @keywords internal
 #' 
 maic.boot <- function(ipd, indices, formula, ald) {
 

R/summary.R

@@ -0,0 +1,8 @@
+
+#
+summary.mimR <- function(object, ...) {
+
+  ans <- NULL
+  class(ans) <- "summary.mimR"
+  ans
+} 

_pkgdown.yml

@@ -16,23 +16,18 @@ navbar:
 
 reference:
 - title: "Main"
-  desc: "Main functions"
+  desc: "Main analysis functions."
   contents:
   # - mimR-package
   - starts_with("mimR")
-- title: "Helpers"
-  desc: "Helper functions"
+  - strategy
+- title: "Constituent statistics"
+  desc: "Helper functions used by the main functions."
   contents:
   - ALD_stats
-  - gcomp_ml.boot
-  - gcomp_ml_log_odds_ratio
-  - gcomp_stan
   - IPD_stats
-  - maic.boot
-  - maic_weights
   - marginal_treatment_effect
   - marginal_variance
-  - strategy_maic
   - trial_treatment_effect
   - trial_variance