editor_options: markdown: wrap: 72
warning("Reference XX for key YY not found."
into warning("Reference XX for key YY not found. Using default."
preliminary_standards
from key gsed2406
in the above case.Inf
values in daz()
into NA
valuesNaN
values in SEM into NA
valuesget_mu()
below -1/12 into NA
valuesdscore()
and dscore_posterior()
now accept a matrix as inputNA
s in D-score, SEM and DAZprior_mean_NA
and prior_sd_NA
to NA
(was 50 and 20). This is a safer option to handle missing ages. The user can still emulate the previous automatic behavior (introduced in dscore 1.9.2) by including the prior_mean_NA = 50
and prior_sd_NA = 20
arguments to the dscore()
function.count_mu()
as function get_mu()
to extract the prior mean from a reference table. Deprecates count_mu()
.testthat/test-prior.R
dscore()
data-raw/data/keys/items_gs1_gl1.txt
that was accidentally removed in a previous releasepreliminary_standards
with a larger sample from Bangladeshmutate()
. In argument: daz = daz(...)
' key
column compulsory in the itembank
argument, and adds a check on proper column namespopulation
and key
argumentsThis is a major update of the dscore
package featuring:
"preliminary_standards"
BREAKING CHANGE: On May 31, 2024 we detected a long-time error in the calculation of the D-score resulting from an incorrect scale factor that led us to believe that item characteristic curves are steeper than the actually are. The impact of the error on the result is as follows: 1) There is no effect on the difficulty estimates of the Rasch models, 2) The D-score estimates are slightly altered but changes are small, 3) The references are largely unaffected and need not to be redone, 4) The estimates of the SEMs can differ substantially, so inferences based on the SEMs should be re-evaluated, 5) When there were changes in the analyses, the results in the newer method look smoother and are preferred. The correction appeared in the development version dscore 1.8.8
, and is now incorporated into release dscore 1.9.0
. For backward compatibility to dscore 1.8.7
and earlier, use the argument algorithm = "1.8.7"
in calls to the dscore()
function.
BREAKING CHANGE: dscore_posterior()
now returns a data.frame
with column names that indicate the quadrature point. This was an unnamed matrix
. Code that expects a matrix
as the return of dscore_posterior()
may need to be adapted.
NEW DEFAULT KEY: Adds a new reference "preliminary_standards"
calculated from selected subsample of the GSED Phase 1 data, and makes these the default in this release. The reference is a temporary stand-in for a future norm-based standard for normal early child development. This reference replaces the temporary reference "phase1_healthy"
that was introduced in dscore 1.8.7
. Compared to the "phase1"
reference, the "preliminary_standards"
reference has the following differences: 1) D-score estimation uses the new model 20240601 with correct scale factor, 2) Calculates the D-score for SF and LF separately (not combined), 3) Tunes the GAMSLSS model to fit the healthy subsample. The "phase1_healthy"
object is removed.
"dutch"
calculated using the "gsed2212"
key."gsed2406"
to accomodate for the changed prior mean because of the adoption of the new reference "preliminary_standards"
as the base population. The key "gsed2406"
is identical to "gsed2212"
, and is the default key in this release.builtin_keys
table that contains proper defaults for the base reference, transformation and quadrature points per keykey
and population
. Previously the index was based on only population
. This change allows for multiple references per key, and for references created for the same population under different keys. The key
field is now mandatory in the reference table.verbose
option to dscore()
, dscore_posterior()
, get_age_equivalent()
, get_reference()
, get_tau()
, daz()
and zad()
to print progress messages to the console on the values of key
, population
, transform
, qp
and algorithm
. This is useful for debugging and for understanding the behavior of the functions.builtin_keys
table. This makes the code more readable and maintainable.sf2206
, lf2206
, 294_0
, gsed2206
, gsed2208
and removes from the builtin_itembank
.dscore()
and dscore_posterior()
can now copy variables from the input data
into the output through the prepend
argument. (#46)init_key()
and set_default_xxx()
functions to regulate values for key
, population
, transform
and qp
argumentsdata-raw/data/keys
to more consistent names, adapts data-raw/R/save_builtin_itembank.R
to reflect model history, and rebuilds builtin_itembank
tibble
and tidyselect
, and replaces the dependency on stringr
by the lighter stringi
reference
to reference_table
in daz()
and zad()
to avoid confusion with the references
argument in get_reference()
magrittr
pipe %>%
by base pipe |>
styler
Specified C++11: please drop specification unless essential
), removes a C++11 specificationpBCT()
daz()
and zad()
using the BCT transformation for positive values names
attribute from the return value of daz()
and zad()
pBCT()
when is.na(nu)
is TRUE
bibtex
packagedata-raw/data/keys
folder and renamed them to improve readabilitygh1
(GSED-HF, JAN 2023) to builtin_itemtable
and builtin_itembank
as part of key gsed2212
sample_sf
, sample_lf
and sample_hf
gl1
instruments as: aa --> gm, bb --> lg, cc --> fmgl1aad001
--> gl1gmd001
, and so onselect()
and pivot_longer()
to conform to tidyselect 1.2.0
grammargsed2206
and gsed2208
, as well as analyses that rely on correct LF item labels. Version 1.7.0 corrects these problems.LF1
, corrected using RedCAP comparisons from
Phase_1_master_data_dictionary_V1.0_29_11_2022.xlsx
;LF2
, from
GSED LF Item Guide_October22_FINAL_clean_27Nov22.docx
and
manually matched to LF1
.gsed2212
gs1
(GSED SF V1.0) and gl1
(GSED LF V1.0)gto
labels with correct ordergsed2212
. This key repairs problems in gsed2206
and gsed2208
. get_labels()
now returns the labels in the same order as items
gsed2212
with 18 ECDI items using Phase 1 validation databuiltin_itemtable
and builtin_itembank
with correct LF
item orderdscore::count_mu_phase1(t)
when t
is a
vector containing NA
sgsample
with 10 cases with SF and LF scoresorder
argument to get_itemnames()
sort_itemnames()
exampledscore.cpp
sirt
packagegsed2208
and 293_0
) using the Phase 1
validation data for the GSED SF and GSED LF.293_0
as the GSED core model and extended it to include
the 818 items that fitted the previous model ("gsed2206").phase1
), based on LF and SF data from
cohorts GSED-BGD, GSED-PAK and GSED-TZA studies.gsed2208
and default population
to "phase1".**. If you want the old behavior, specify
key =
"gsed1912"or
key =
"gsed2206"to functions that accept the
keyargument (
dscore(),
dscore_posterior(),
get_age_equivalent(),
get_tau()`).get_age_equivalent()
and get_tau()
consistent
with dscore()
phase1
reference to get_reference()
zad()
and daz()
count_mean_phase1()
for setting prior mean equal to the GSED
Phase 1 referencecount_mean_phase1()
dscore()
prior_mean functionality to deal with the
to-be-implemented new reference as "phase1"count_mean_phase1()
functiongsed2206
and 294_0
population
when key is 294_0
.294_0
to the builtin_itembank
.relevance
argument to dscore()
and dscore_posterior()
to restrict calculation of D-scores to those items that have their
tau
within this relevance interval around the dynamic EAP
estimate.builtin_itembank
that inherits old (gsed1912) tau's
into new key (gsed2206) for instruments gto
and gpa
. As a
consequence, D-score were incorrectly calculated when gto
and
gpa
item names were used.get_age_equivalent()
that resulted in age
interval estimates that were too narrow on the D-score scale.gsed2206
, lf2206
and sf2206
) that
incorporate Phase 1 validation data for the GSED SF, GSED LF and
BSID.gsed2206
. If you want the old
behavior, specify key = "gsed1912"
to functions that accept the
key
argument (dscore()
, dscore_posterior()
,
get_age_equivalent()
, get_tau()
).builtin_itemtable
with names and labels for gpa
(SF),
gto
(LF) and gsd
(novel SF) items.metric = "logit"
and transform
parameters specified.
The D-scores calculated under different transforms are now linear
transformations of each other.D-score/dscore
for
increased visibilitydata-raw/data/bds)edited.csv
ddata
package to
builtin_itemtable
itemtable_20200424.txt
with minimal item definitionsddata
packagebuiltin_itemtable
get_itemtable()
function gets a new argument decompose
for
adding info from decomposed item namesget_itemtable()
when itemtable
argument is
specifieddrop = TRUE
to account for new behavior in
tibble 3.0.0
get_itemtable()
.dscore
and clopus
packages. The dscore
package now first
rounds the D-score and then calculate DAZ.dscore()
function now automatically select the
prior_mean = ".dutch"
option when the user specifies
key == "dutch"
. This change repair an error in the D-score
calculation that occurs when only key == "dutch"
was given.dscore()
function now silently handles warnings that may
result from taking the log of negative ages.dscore 1.0.0
! For the development history, see
https://github.com/D-score/dscoreNEWS.md
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