Updating for pkgdown

.github/workflows/pkgdown.yaml

@@ -0,0 +1,50 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+  release:
+    types: [published]
+  workflow_dispatch:
+
+name: pkgdown
+
+permissions: read-all
+
+jobs:
+  pkgdown:
+    runs-on: ubuntu-latest
+    # Only restrict concurrency for non-PR jobs
+    concurrency:
+      group: pkgdown-${{ github.event_name != 'pull_request' || github.run_id }}
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    permissions:
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::pkgdown, local::.
+          needs: website
+
+      - name: Build site
+        run: pkgdown::build_site_github_pages(new_process = FALSE, install = FALSE)
+        shell: Rscript {0}
+
+      - name: Deploy to GitHub pages 🚀
+        if: github.event_name != 'pull_request'
+        uses: JamesIves/[email protected]
+        with:
+          clean: false
+          branch: gh-pages
+          folder: docs

DESCRIPTION

@@ -40,4 +40,4 @@ Remotes:
 LinkingTo: Rcpp, RcppArmadillo, RcppDist, Rfast
 NeedsCompilation: yes
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2.9000

R/padj_sim_fns.R

@@ -64,6 +64,7 @@ padj_test_fn <- function(idat, bdat, blockid, trtid = "trt", fmla = Y ~ trtF | b
     bdatnew <- bdatnew[newcovb]
   }
 
+  ## Create potential outcome to treatment using a tau_fn and tau_size etc.
   datnew$y1new <- create_effects(
     idat = datnew, ybase = ybase, blockid = blockid,
     tau_fn = tau_fn, tau_size = tau_size,
@@ -136,7 +137,8 @@ padj_test_fn <- function(idat, bdat, blockid, trtid = "trt", fmla = Y ~ trtF | b
 #' @export
 reveal_po_and_test <- function(idat, bdat, blockid, trtid, fmla = NULL, ybase, y1var,
                                prop_blocks_0, tau_fn, tau_size, pfn, p_adj_method = "fdr",
-                               afn = NULL, splitfn = NULL, splitby = NULL, thealpha = .05, copydts = FALSE, stop_splitby_constant = FALSE, ncores = 1, return_details = FALSE) {
+                               afn = NULL, splitfn = NULL, splitby = NULL, thealpha = .05, copydts = FALSE,
+                               stop_splitby_constant = FALSE, ncores = 1, return_details = FALSE) {
   stopifnot(is.null(splitfn) | splitfn == "NULL")
   # make no effects within block by shuffling treatment, this is the engine of variability in the sim
   idat[, newZ := sample(get(trtid)), by = blockid]
@@ -383,11 +385,11 @@ calc_errs <- function(testobj,
 
   # This is calculated at the level of blocks not nodes.
   deterrs <- detobj[, .(
-    nreject = sum(hitb),
+    nreject = sum(hitb), # number of rejected blocks
     naccept = sum(1 - hitb),
     prop_reject = mean(hitb),
     prop_accept = mean(1 - hitb),
-    tot_true0 = sum(true0),
+    tot_true0 = sum(true0), # number of true 0 blocks.
     tot_truenot0 = sum(truenot0),
     tot_reject_true0 = sum(hitb * true0),
     tot_not_reject_true0 = sum((1 - hitb) * true0),
@@ -397,9 +399,12 @@ calc_errs <- function(testobj,
     # Proportion of the total blocks that have an effect where we detect that effect:
     correct_pos_effect_prop = sum(hitb * truenot0) / max(1, sum(truenot0)),
     correct_pos_nulls_prop = sum(hitb * true0) / max(1, sum(true0)),
+    ## if hitb=1 (reject) and truenot0=1 then this is a correct rejection. Use in power calculations.
     true_pos_prop = mean(hitb * truenot0),
     ## Proportion of rejections of a true null out of the total number of tests
-    false_pos_prop = mean(hitb * true0),
+    ##   if hitb=1 (meaning rejection) and true0=1 (meaning no true effect, true effect = 0) then a false positive
+    false_pos_prop = mean(hitb * true0), # number blocks rejected when truly 0 / total number of blocks.
+    # also sum(hitb*true0)/nrow(detobj)
     # If we do not reject and all blocks are truly null, then we have no error.
     prop_not_reject_true0 = mean((1 - hitb) * true0),
     # If we do not reject/detect and at least one of the blocks actually has an effect, we have

R/simulation_functions.R

@@ -142,7 +142,10 @@ tau_norm_outliers <- function(ybase, tau_sds, covariate) {
     rnorm(n, mean = tau_sds * sd(ybase), sd = sd(ybase) / 2)
   } else {
     # 2 large outliers
-    c(rnorm(n - num_outliers, mean = sd(ybase) * tau_sds, sd = sd(ybase) / 2), rnorm(num_outliers, mean = sd(ybase) * tau_sds * 4, sd = sd(ybase) * 4))
+    c(
+      rnorm(n - num_outliers, mean = sd(ybase) * tau_sds, sd = sd(ybase) / 2),
+      rnorm(num_outliers, mean = sd(ybase) * tau_sds * 4, sd = sd(ybase) * 4)
+    )
   }
 }
 

_pkgdown.yml

@@ -0,0 +1,4 @@
+url: ~
+template:
+  bootstrap: 5
+