`gigs` (guidance for international growth standards) package

[simpar1471]

Submitting Author Name: Simon Parker Submitting Author Github Handle: !--author1-->@simpar1471<!--end-author1-- Repository: https://www.github.com/lshtm-gigs/gigs/ Submission type: Pre-submission Language: en

---

• Paste the full DESCRIPTION file inside a code block below:

Type: Package
Package: gigs
Title: Assess Growth in Infants and Newborns
Version: 0.2.4
Authors@R: c(
    person(given = "Simon", family = "Parker",
           email = "simon.parker@lshtm.ac.uk",
           role = c("aut", "cre"), comment = c(ORCID = "0009-0003-8214-4496")),
    person(given = "Eric", family = "Ohuma", role = c("dtc", "rev"),
           comment = c(ORCID = "0000-0002-3116-2593")),
    person(given = "Bill & Melinda Gates Foundation", role = c("fnd", "cph"))
    )
Description: Convert between anthropometric measures and z-scores/percentiles in
    multiple growth standards, and classify infant growth accordingly. With a
    simple interface to growth standards from the World Health Organisation and
    International Fetal and Newborn Growth Consortium for the 21st Century, gigs
    makes growth assessment easy and reproducible for clinicians, researchers
    and policy-makers.
License: GPL (>= 3)
URL: https://github.com/lshtm-gigs/gigs/,
    https://lshtm-gigs.github.io/gigs/
BugReports: https://github.com/lshtm-gigs/gigs/issues
Depends: 
    R (>= 4.1.0)
Imports:
    gamlss.dist,
    stats,
    vctrs
Suggests:
    knitr,
    rmarkdown,
    testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.2.3
Roxygen: list(markdown = TRUE)

Scope

• Please indicate which category or categories from our package fit policies or statistical package categories this package falls under. (Please check an appropriate box below):

  Data Lifecycle Packages

  • [ ] data retrieval

  • [ ] data extraction

  • [ ] data munging

  • [ ] data deposition

  • [ ] data validation and testing

  • [ ] workflow automation

  • [ ] version control

  • [ ] citation management and bibliometrics

  • [ ] scientific software wrappers

  • [ ] field and lab reproducibility tools

  • [ ] database software bindings

  • [ ] geospatial data

  • [ ] text analysis

    Statistical Packages

  • [ ] Bayesian and Monte Carlo Routines

  • [ ] Dimensionality Reduction, Clustering, and Unsupervised Learning

  • [ ] Machine Learning

  • [ ] Regression and Supervised Learning

  • [x] Exploratory Data Analysis (EDA) and Summary Statistics

  • [ ] Spatial Analyses

  • [ ] Time Series Analyses

• Explain how and why the package falls under these categories (briefly, 1-2 sentences). Please note any areas you are unsure of:

The package is used to convert measurements, for example a baby's weight at a given age, into summary statistics such as z-scores (i.e. number of standard deviations away from mean) and percentiles (i.e. number of percentage points above/below the median, expressed as a decimal). It can also be used to classify these z-scores and percentiles into specific categories for specific facets of growth.

• If submitting a statistical package, have you already incorporated documentation of standards into your code via the srr package?

We have started this process, and will have it done by the next version of gigs released onto GitHub.

• Who is the target audience and what are scientific applications of this package?

The target audience for this package is researchers, clinicians, and policy-makers interested in nutrition and newborn and child health. Scientific applications of this package would include using our functions to generate statistical measures of growth in individuals or populations across time or pre/post a healthcare intervention, and then to perform further downstream analysis on these measures.

• Are there other R packages that accomplish the same thing? If so, how does yours differ or meet our criteria for best-in-category?

Several R packages which implement child growth charts already exist, but they differ in the range of growth charts offered, their flexibility in conversion, and in what data they make available to users.

1. anthro converts measurements into z-scores in the WHO Child Growth Standards, but lacks any INTERGROWTH-21^st standards and outputs tabular data. We provide an interface which takes vectors in and gives vectors out, so is more flexible (e.g. with dplyr pipelines). This package is available on CRAN.
2. childsds can convert measurements to z-scores or percentiles, but cannot convert z-scores/percentiles to expected measurements. Additionally, childsds does not contain the newborn/postnatal INTERGROWTH-21^st growth standards, which we implement. Though childsds does include more growth references, growth references are not within the scope of the GIGS project. We can discuss the reasons for this if necessary. This package is available on CRAN.
3. growthstandards contains functions for converting between values and z-scores/percentiles, as in gigs. It includes the INTERGROWTH-21^st fetal standards, but not the newborn or postnatal standards we implement. This package makes coefficients available to end-users, but not reference growth curves. This package is not available on CRAN, and was last updated in 2021.
4. intergrowth provides more fetal growth standards than gigs, but cannot convert between z-scores/percentiles in the lacks the INTERGROWTH-21^st newborn or postnatal growth standards, which we have implemented in gigs. This package also does not make coefficients for the growth standards available to end-users, though it it does provide growth curve data to end-users. This package is not available on CRAN, and was last updated in January 2023.
5. gigs provides a simple interface for working with the growth standards it implements, which can be easily included in dplyr-like data wrangling pipelines. Reference growth curves and model coefficients are available wherever possible, and we intend to update the package with extra functionality (e.g. the full suite of fetal/maternal INTERGROWTH-21^st standards) by June of next year. We are ready to submit to CRAN, but are waiting to see how you respond to this presubmission inquiry.

In terms of performance/scaling from 1 to 10000 inputs, anthro performs/scales the worst (28 ms to 234 ms), then gigs (921.8 microseconds to 41 ms), then growthstandards (4.7497 ms to 23 ms), then childsds (2 ms to 17 ms). We will look to these implementations to see how we can make gigs faster, if required.

• (If applicable) Does your package comply with our guidance around Ethics, Data Privacy and Human Subjects Research?

Not applicable.

• Any other questions or issues we should be aware of?

None.

[noamross]

Thank you for this pre-submission, @simpar1471! This is an interesting package. I note it somewhat straddles the line between the standard category of "data munging," which has traditionally include software that implements field-specific standard conversions and deterministic descriptive calculations on data, and the the still less-defined EDA statistical category, which we had envisioned as tools to enable things like exploring the distributions and correlations within data. I'm going to pose this to some of the other editors and follow up, as this will change the way you submit, and whether you need to use srr, standards.

[simpar1471]

Hi @noamross, just wondering if you managed to get an answer from the other editors?

[noamross]

Thank you for following up @simpar1471! My apologies, I did get some feedback and didn't post it back here. For edge cases like these, we ask that things be submitted as statistical packages if 50% or more of the standards can be applied. I think that this applies to the EDA standards and General standards in this case, so we would be happy to accept full a submission of the package under the EDA statistical category.

[simpar1471]

Ah, thank you @noamross! I'll open a new issue in due course once the package is updated.