R Under development (unstable) (2025-04-11 r88138 ucrt) -- "Unsuffered Consequences"
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> library(tidyverse) # version: tidyverse_2.0.0
── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.2     ✔ tibble    3.2.1
✔ lubridate 1.9.4     ✔ tidyr     1.3.1
✔ purrr     1.0.4     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
> library(dplyr) #version: dplyr_1.1.4
> library(stats) # version: stats4
> library(fastDummies) # version: fastDummies_1.7.3
> library(reshape2) #version: reshape2_1.4.4

Attaching package: 'reshape2'

The following object is masked from 'package:tidyr':

    smiths

> library(testthat)

Attaching package: 'testthat'

The following object is masked from 'package:dplyr':

    matches

The following object is masked from 'package:purrr':

    is_null

The following objects are masked from 'package:readr':

    edition_get, local_edition

The following object is masked from 'package:tidyr':

    matches

> 
> ## IRT-M estimation:
> #devtools::install_github("dasiegel/IRT-M")
> library(IRTM) #version 1.00
Loading required package: truncnorm
Loading required package: tmvtnorm
Loading required package: mvtnorm
Loading required package: Matrix

Attaching package: 'Matrix'

The following objects are masked from 'package:tidyr':

    expand, pack, unpack

Loading required package: stats4
Loading required package: gmm
Loading required package: sandwich
Loading required package: RcppProgress
Loading required package: RcppDist
> 
> test_check("IRTM")

-- Column specification --------------------------------------------------------
cols()

Sampling...
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
[ FAIL 0 | WARN 1 | SKIP 0 | PASS 2 ]

[ FAIL 0 | WARN 1 | SKIP 0 | PASS 2 ]
> 
> context("Testing IRTM")
> 
> test_that("Test Case One: Normal Use", {
+ 
+   synth_questions <- NULL  # Initialize to avoid R CMD check notes
+ 
+   load("synth_questions.rda")
+   ## Convert numeric ordinal responses to factors
+ 
+   ebdatsub <- lapply(ebdatsynth[,], factor) ## that's a list now
+ 
+   ## converts the list back into a dataframe:
+   Y <- dummy_cols(.data=ebdatsub,
+                   remove_selected_columns=TRUE)
+ 
+   ## remove the .data that dummy_cols adds to the column names
+   colnames(Y) <- gsub(".data.", '', colnames(Y))
+ 
+   ## remove the data objects:
+   rm(ebdatsub)
+   rm(ebdatsynth)
+ 
+   load('mcodes.rda')
+ 
+   ## Only keep M-Codes with loadings or outcomes:
+   MCodes$encoding <- rowSums(abs(MCodes[,4:9]))
+   MCodes <- MCodes[which(MCodes$encoding > 0),]
+ 
+   d <- 6 #number of coded dimensions
+   mcolumns <- c("QMap", "D1-Culture threat",
+                 "D2-ReligionThreat",
+                 "D3-Economic Threat",
+                 "D4-HealthThreat",
+                 "O1-OutcomeSupportImmigration", "O2-OutcomeSupportEU")
+ 
+   combine <- MCodes[,mcolumns] %>% ## question codes and loadings
+     inner_join(
+       Y %>%
+         t() %>%
+         as.data.frame(stringsAsFactors = FALSE) %>%
+         type_convert() %>%
+         rownames_to_column(var = "question"),
+       by = c("QMap" = "question"  )
+     )
+ 
+   M_matrix <- as.data.frame(combine[, 1:(d+1)])
+ 
+   #Reverse the earlier transposition of the observations:
+   Y_in <- combine[, (d+2):ncol(combine)]%>%
+     t() %>%
+     as.data.frame()
+ 
+   Y_in <- as.data.frame(sapply(Y_in, as.numeric))
+ 
+   ## Take the question names and
+   ## convert to column names
+ 
+   question <- combine[,1] %>%
+     as.data.frame()
+   colnames(Y_in) <- question[,1]
+   rm(combine)
+   rm(question)
+ 
+   #Run IRT-M
+   d=6
+   irt <- irt_m(Y_in = Y_in, d = d, M_matrix = M_matrix, nsamp = 100, nburn=100, thin=1)
+ 
+   expect_type(irt, "list")
+   expect_equal(length(irt), 5)
+ }) ## closes the test_that() call
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
── Warning: Test Case One: Normal Use ──────────────────────────────────────────
`type_convert()` only converts columns of type 'character'.
- `df` has no columns of type 'character'
Backtrace:
     ▆
  1. ├─MCodes[, mcolumns] %>% ...
  2. ├─dplyr::inner_join(...)
  3. ├─dplyr:::inner_join.data.frame(...)
  4. │ └─dplyr::auto_copy(x, y, copy = copy)
  5. │   ├─dplyr::same_src(x, y)
  6. │   └─dplyr:::same_src.data.frame(x, y)
  7. │     └─base::is.data.frame(y)
  8. ├─... %>% rownames_to_column(var = "question")
  9. ├─tibble::rownames_to_column(., var = "question")
 10. └─readr::type_convert(.)

> 
> proc.time()
   user  system elapsed 
  66.23    1.32   67.57