✔ Set "updated_2025.06" as default for regression method on <DIGBACLS>
✔ Set "updated_2025.06" as default for regression method on <MINTTOTS>
✔ Set "nacc_legacy" as default for regression method on <NACCMMSE>
✔ Set "updated_2025.06" as default for regression method on <OTRLBRR>
✔ Set "updated_2025.06" as default for regression method on <UDSVERTN>
✔ Set "nacc_legacy" as default for regression method on <BOSTON>
✔ Set "updated_2025.06" as default for regression method on <DIGBACCT>
✔ Set "updated_2025.06" as default for regression method on <CRAFTDVR>
✔ Set "updated_2025.06" as default for regression method on <OTRLARR>
✔ Set "updated_2025.06" as default for regression method on <UDSVERFC>
✔ Set "ravlt_trials" as default for norms method on <REYDREC>
✔ Set "ravlt_trials" as default for norms method on <REY6REC>
✔ Set "updated_2025.06" as default for regression method on <MOCATOTS>
✔ Set "updated_2025.06" as default for regression method on <ANIMALS>
✔ Set "nacc_legacy" as default for regression method on <MEMUNITS>
✔ Set "updated_2025.06" as default for regression method on <CRAFTURS>
✔ Set "updated_2025.06" as default for regression method on <DIGFORCT>
✔ Set "updated_2025.06" as default for regression method on <VEG>
✔ Set "updated_2025.06" as default for regression method on <UDSBENTD>
✔ Set "nacc_legacy" as default for regression method on <DIGIB>
✔ Set "updated_2025.06" as default for regression method on <CRAFTDRE>
✔ Set "updated_2025.06" as default for regression method on <TRAILB>
✔ Set "updated_2025.06" as default for regression method on <UDSVERLC>
✔ Set "nacc_legacy" as default for regression method on <DIGIFLEN>
✔ Set "updated_2025.06" as default for regression method on <OTRAILB>
✔ Set "updated_2025.06" as default for regression method on <UDSBENTC>
✔ Set "updated_2025.06" as default for regression method on <TRAILA>
✔ Set "nacc_legacy" as default for regression method on <LOGIMEM>
✔ Set "nacc_legacy" as default for regression method on <DIGIBLEN>
✔ Set "updated_2025.06" as default for regression method on <OTRAILA>
✔ Set "nacc_legacy" as default for regression method on <DIGIF>
✔ Set "updated_2025.06" as default for regression method on <CRAFTVRS>
✔ Set "updated_2025.06" as default for regression method on <DIGFORSL>Overview
ntrs provides an S7-based interface for standardizing neuropsychological test scores. The typical workflow is:
- Create score objects using factory functions (e.g.,
MOCATOTS(),ANIMALS()) - Standardize scores with
std()or batch-standardize a data frame withstd_data()
When loading the package, messages are printed for all the defaults being set. These can be suppressed with suppressPackageStartupMessages().
Creating score objects
Each neuropsychological test has a dedicated factory function that wraps raw numeric scores with metadata (valid range, error codes, etc.):
<ntrs::MOCATOTS> num [1:3] 25 28 30
@ label : chr "MoCA"
@ domain : chr "General Cognition"
@ short_descriptor: chr "MoCA Total Raw Score - uncorrected"
@ range : num [1:2] 0 30
@ codes : Named num [1:2] -4 88
.. - attr(*, "names")= chr [1:2] "Not available: UDS form submitted did not collect data in this way, or a skip pattern precludes response to this question" "Item(s) or whole test not administered"To see all available tests:
[1] "ANIMALS" "BOSTON" "CDRGLOB" "CDRSUM" "CRAFTDRE" "CRAFTDVR"
[7] "CRAFTURS" "CRAFTVRS" "DIGBACCT" "DIGBACLS" "DIGFORCT" "DIGFORSL"
[13] "DIGIB" "DIGIBLEN" "DIGIF" "DIGIFLEN" "LOGIMEM" "MEMUNITS"
[19] "MINTTOTS" "MOCACLOCK" "MOCATOTS" "MOCBTOTS" "NACCGDS" "NACCMMSE"
[25] "OTRAILA" "OTRAILB" "OTRLARR" "OTRLBRR" "REY1REC" "REY2REC"
[31] "REY3REC" "REY4REC" "REY5REC" "REY6REC" "REYAREC" "REYDLIST"
[37] "REYDREC" "REYFPOS" "REYTCOR" "REYTOTAL" "TRAILA" "TRAILALI"
[43] "TRAILARR" "TRAILB" "TRAILBLI" "TRAILBRR" "UDSBENRS" "UDSBENTC"
[49] "UDSBENTD" "UDSVERFC" "UDSVERLC" "UDSVERTN" "VEG" "WAIS" Discovering standardization options
Before standardizing, you can check which methods and versions are available for a given test:
list_std_methods(moca)[1] "norms" "regression"
list_method_versions(moca, "norms")[1] "nacc" "updated"
list_method_versions(moca, "regression")[1] "nacc" "updated_2024.06" "updated_2025.06"Each test has registered defaults so you don’t need to specify a method every time:
get_std_defaults(moca)$method
[1] "regression"
$version
[1] "updated_2025.06"These can be changed globally with set_std_defaults():
set_std_defaults(
moca,
method = "norms",
version = "nacc",
overwrite = TRUE
)ℹ Default method and version for "MOCATOTS" was previously set to "regression"
and "updated_2025.06".
ℹ Will be overwritten.
✔ Set "nacc" as default for norms method on <MOCATOTS>
get_std_defaults(moca)$method
[1] "norms"
$version
[1] "nacc"Do note that changes to the default will not be saved from session to session, so you may want to set them in your .Rprofile if you want them to persist.
Standardizing a single score vector
Use std() to convert raw scores to z-scores. Covariates (age, sex, education, etc.) are passed as named arguments:
z <- std(moca, age = 72, sex = 1, educ = 16)
z<ntrs::std_npsych_scores> num [1:3] -0.417 0.833 1.667
@ scores_subclass: chr "MOCATOTS"
@ description : chr "Standardized using norms, version nacc. Adjusted for covariates age, educ, sex."
@ method : chr "norms"
@ version : chr "nacc"The result is an std_npsych_scores object. You can inspect the standardization metadata via S7 properties:
z@method[1] "norms"
z@version[1] "nacc"
z@description[1] "Standardized using norms, version nacc. Adjusted for covariates age, educ, sex."
set_std_defaults(
moca,
method = "regression",
version = "updated_2025.06",
overwrite = TRUE
)ℹ Default method and version for "MOCATOTS" was previously set to "norms" and
"nacc".
ℹ Will be overwritten.
✔ Set "updated_2025.06" as default for regression method on <MOCATOTS>
z_reg <- std(moca, age = 72, sex = 1, educ = 16, race = 1)
z_reg<ntrs::std_npsych_scores> num [1:3] -0.363 0.891 1.727
@ scores_subclass: chr "MOCATOTS"
@ description : chr "Standardized using regression, version updated_2025.06. Adjusted for covariates age, sex, educ, race."
@ method : chr "regression"
@ version : chr "updated_2025.06"To override the default method or version, specify them explicitly:
z_norms <- std(
moca,
method = "norms",
version = "updated",
age = 72,
sex = 1,
educ = 16
)
z_norms<ntrs::std_npsych_scores> num [1:3] -0.353 0.831 1.621
@ scores_subclass: chr "MOCATOTS"
@ description : chr "Standardized using norms, version updated. Adjusted for covariates sex, age, educ."
@ method : chr "norms"
@ version : chr "updated"Batch standardization with std_data()
When you have a data frame with multiple test score columns, std_data() standardizes all of them at once:
df <- data.frame(
age = c(72, 75, 68),
sex = c(1, 2, 1),
educ = c(16, 14, 12),
race = c(1, 2, 1),
moca = MOCATOTS(c(25, 28, 22)),
animals = ANIMALS(c(18, 20, 16))
)
result <- std_data(
df,
age = age,
sex = sex,
educ = educ,
race = race
)
result age sex educ race moca animals z_moca z_animals
1 72 1 16 1 25 18 -0.3628727 -0.6295726
2 75 2 14 2 28 20 1.6463434 0.5252069
3 68 1 12 1 22 16 -1.1015874 -0.7205741Each standardized column is an std_npsych_scores object carrying @method, @version, and @description properties. Use methods_from_std_data() to extract them conveniently:
attr(result, "prefix_std")[1] "z_"
methods_from_std_data(result)$moca
method version
"regression" "updated_2025.06"
$animals
method version
"regression" "updated_2025.06" You can override the method/version per test class:
result2 <- std_data(
df,
methods = list(
MOCATOTS = list(method = "norms", version = "nacc")
),
age = age,
sex = sex,
educ = educ,
race = race
)Warning: `race` is not needed to standardize using "norms" when version is "nacc" and
will be ignored.
result2 age sex educ race moca animals z_moca z_animals
1 72 1 16 1 25 18 -0.4166667 -0.6295726
2 75 2 14 2 28 20 0.8928571 0.5252069
3 68 1 12 1 22 16 -1.0303030 -0.7205741