Package: bspam 1.2.6

Kuo Wang

bspam: Speed-Accuracy Psychometric Modeling for Binomial Count Outcome Data

Provides functions to fit speed-accuracy psychometric models for binomial count outcome data. The models jointly represent accuracy and response time and can be used for model-based calibration and scoring of oral reading fluency (ORF) assessment data. The methods are based on Potgieter, Kamata and Kara (2017) <doi:10.48550/arXiv.1705.10446> and Kara, Kamata, Potgieter and Nese (2020) <doi:10.1177/0013164419900208>.

Authors:Kuo Wang [aut, cre], Akihito Kamata [aut, ctb], Cornelis J. Potgieter [aut], Joseph F. T. Nese [aut], Yusuf Kara [aut], Sarunya Somsong [aut], Xin Qiao [aut]

bspam_1.2.6.tar.gz
bspam_1.2.6.zip(r-4.7-any)bspam_1.2.6.zip(r-4.6-any)
bspam_1.2.6.tar.gz(r-4.7-any)bspam_1.2.6.tar.gz(r-4.6-any)
bspam_1.2.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
bspam/json (API)

# Install 'bspam' in R:

install.packages('bspam', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/kamataak/bspam/issues

Pkgdown/docs site:https://kamataak.github.io

Datasets:

passage.calib.bayes - Task calibration example output object by Bayes
passage.calib.mcem - Task calibration example output object by MCEM
passage2 - Passage-level Oral Reading Fluency assessment data set
sentence.cens.high - Sentence-level data set with high censoring
sentence.cens.low - Sentence-level data set with low censoring
sentence.level.data - Sentence-level Oral Reading Fluency assessment data set

On CRAN:

2.85 score 14 scripts 13 exports 127 dependencies

Last updated from:604b63793d. Checks:6 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	167
source / vignettes	OK	293
linux-release	OK	173
windows-devel	OK	257
windows-release	OK	234
wasm-release	OK	153

Exports:%>%agg.word desc.data fit.model fit.model.testlet get.cases plot.information plot.person plot.task plot.wcpm prep run.mcem scoring

Dependencies:askpass backports base64enc bit bit64 blob broom bslib cachem callr cellranger cli clipr codetools conflicted cpp11 crayon crosstalk curl data.table DBI dbplyr digest doParallel dplyr dtplyr evaluate farver fastmap fontawesome forcats foreach formatR fs futile.logger futile.options gargle generics ggplot2 glue googledrive googlesheets4 GPArotation gtable haven highr hms htmltools htmlwidgets httr ids isoband iterators jquerylib jsonlite knitr labeling lambda.r later lattice lazyeval lifecycle lubridate magrittr Matrix memoise mime miscTools mnormt modelr mvtnorm nleqslv nlme openssl otel pillar pkgconfig plotly prettyunits processx progress promises ps psych purrr R6 ragg rappdirs RColorBrewer Rcpp readr readxl rematch rematch2 reprex rlang rmarkdown rootSolve rstudioapi rvest S7 sass scales selectr statmod stringi stringr sys systemfonts textshaping tibble tidyr tidyselect tidyverse timechange tinytex tryCatchLog tzdb utf8 uuid vctrs viridisLite vroom withr xfun xml2 yaml

bspam: Passage-level Calibration & Scoring for ORF Data 1

Rendered frombasic_01.Rmdusingknitr::rmarkdown

Last update: 2026-11-12
Started: 2026-11-12

Help page	Topics
Aggregate word-level ORF data	agg.word
Summarize response data	desc.data
Fit the speed-accuracy psychometric model	fit.model
Fit the speed-accuracy testlet model	fit.model.testlet
Create person-by-occasion case identifiers	get.cases
Task calibration example output object by Bayes	passage.calib.bayes
Task calibration example output object by MCEM	passage.calib.mcem
Passage-level Oral Reading Fluency assessment data set	passage2
Plot model-based WCPM information	plot.information
Plot estimated person scores	plot.person
Plot calibrated task parameters	plot.task
Plot observed versus model-based WCPM	plot.wcpm
Prepare response data for bspam analyses	prep
Fit the speed-accuracy model by Monte Carlo EM	run.mcem
Estimate person scores by likelihood-based methods	run.scoring
Estimate person scores from a calibrated speed-accuracy model	scoring
Sentence-level data set with high censoring	sentence.cens.high
Sentence-level data set with low censoring	sentence.cens.low
Sentence-level Oral Reading Fluency assessment data set	sentence.level.data
Summarize bootstrap scoring results	summary.bootstrap
Summarize a fitted bspam model	summary.fit.model
Summarize a fitted testlet model	summary.fit.model.testlet
Summarize bspam scoring results	summary.scoring

Package: bspam 1.2.6

bspam: Speed-Accuracy Psychometric Modeling for Binomial Count Outcome Data

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)