Type: Package
Title: Pediatrics Extension Package for ADaM in 'R' Asset Library
Version: 0.2.0
Description: A toolbox for programming Clinical Data Standards Interchange Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, https://www.cdisc.org/standards/foundational/adam). The package is an extension package of the 'admiral' package for pediatric clinical trials.
License: Apache License (≥ 2)
URL: https://pharmaverse.github.io/admiralpeds/, https://github.com/pharmaverse/admiralpeds
Depends: R (≥ 4.1)
Imports: admiral (≥ 1.0.0), admiraldev (≥ 1.0.0), cli (≥ 3.6.2), dplyr (≥ 1.0.5), magrittr (≥ 1.5), purrr (≥ 0.3.3), rlang (≥ 0.4.4), tidyselect (≥ 1.1.0), zoo (≥ 1.8.12)
Suggests: knitr, lubridate (≥ 1.7.4), pharmaversesdtm (≥ 1.1.0), rmarkdown, stringr (≥ 1.4.0), testthat (≥ 3.0.0), tibble
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2025-01-16 17:02:23 UTC; fanny.gautier
Author: Fanny Gautier [aut, cre], Ross Farrugia [aut], Zelos Zhu [aut], Sukalpo Saha [aut], Lina Patil [aut], Samia Kabi [aut], Laura Liao [ctb], Remigiusz Kudlacz [ctb], Pierre Wallet [ctb], Amin Sherzad [ctb], David Freedman [ctb], Mahmoud Hamza [ctb], F. Hoffmann-La Roche AG [cph, fnd], Cytel [cph, fnd], Pfizer Inc. [cph, fnd], Atorus Research [cph, fnd]
Maintainer: Fanny Gautier <fanny.gautier@cytel.com>
Repository: CRAN
Date/Publication: 2025-01-16 17:50:02 UTC

admiralpeds: Pediatrics Extension Package for ADaM in 'R' Asset Library

Description

logo

A toolbox for programming Clinical Data Standards Interchange Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, https://www.cdisc.org/standards/foundational/adam). The package is an extension package of the 'admiral' package for pediatric clinical trials.

Author(s)

Maintainer: Fanny Gautier fanny.gautier@cytel.com

Authors:

Other contributors:

See Also

Useful links:

Other internal: find_closest_bin(), get_bins(), set_bins()

Subject Level Analysis Dataset-pediatrics

Description

An updated ADaM ADSL dataset with pediatric patients

Usage

adsl_peds

Format

An object of class tbl_df (inherits from tbl, data.frame) with 5 rows and 35 columns.

CDC BMI-for-age-chart

Description

BMI-for-age charts, 2 to 20.5 years

Usage

cdc_bmiage

Format

A data frame with 438 rows and 7 variables:

SEX

Sex: 1 = male, 2 = female

AGE

Age in months

L

Box-Cox transformation for normality

M

Median

S

Coefficient of variation

Sigma

Sigma

P95

95th Percentile

Source

https://www.cdc.gov/growthcharts/percentile_data_files.htm

See Also

Metadata cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

CDC Height-for-age-chart

Description

Height-for-age charts, 2 to 20 years

Usage

cdc_htage

Format

A data frame with 436 rows and 5 variables:

SEX

Sex: 1 = male, 2 = female

AGE

Age in months

L

Box-Cox transformation for normality

M

Median

S

Coefficient of variation

Source

https://www.cdc.gov/growthcharts/percentile_data_files.htm

See Also

Metadata cdc_bmiage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

CDC Weight-for-age-chart

Description

Weight-for-age charts, 2 to 20 years

Usage

cdc_wtage

Format

A data frame with 436 rows and 5 variables:

SEX

Sex: 1 = male, 2 = female

AGE

Age in months

L

Box-Cox transformation for normality

M

Median

S

Coefficient of variation

Source

https://www.cdc.gov/growthcharts/percentile_data_files.htm

See Also

Metadata cdc_bmiage, cdc_htage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

Derive interpolated rows for the CDC charts (>=2 yrs old)

Description

Derive a linear interpolation of rows for the CDC charts (>=2 yrs old) by age in days for the following parameters: HEIGHT, WEIGHT and BMI

Usage

derive_interp_records(dataset, by_vars = NULL, parameter)

Arguments

dataset

Input metadataset

The variables AGE, AGEU, SEX, L, M, S are expected to be in the dataset

For BMI the additional variables P95 and Sigma are expected to be in the dataset

Note that AGE must be in days so that AGEU is equal to "DAYS"

by_vars

Grouping variables

The variable from dataset which identifies the group of observations to interpolate separately.

parameter

CDC/WHO metadata parameter

Permitted Values: "WEIGHT", "HEIGHT" or "BMI" only - Must not be NULL e.g. parameter = "WEIGHT", parameter = "HEIGHT", or parameter = "BMI".

Value

The input dataset plus additional interpolated records: a record for each day from the minimum age to the maximum age.

If any variables in addition to the expected ones are in the input dataset, LOCF (Last Observation Carried Forward) is applied to populate them for the new records.

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

Examples

library(dplyr, warn.conflicts = FALSE)
library(rlang, warn.conflicts = FALSE)

cdc_htage <- admiralpeds::cdc_htage %>%
  mutate(
    SEX = case_when(
      SEX == 1 ~ "M",
      SEX == 2 ~ "F",
      TRUE ~ NA_character_
    ),
    # Ensure first that Age unit is "DAYS"
    AGE = round(AGE * 30.4375),
    AGEU = "DAYS"
  )

# Interpolate the AGE by SEX
derive_interp_records(
  dataset = cdc_htage,
  by_vars = exprs(SEX),
  parameter = "HEIGHT"
)

Derive Anthropometric indicators (Z-Scores/Percentiles-for-Age) based on Standard Growth Charts

Description

Derive Anthropometric indicators (Z-Scores/Percentiles-for-Age) based on Standard Growth Charts for Height/Weight/BMI/Head Circumference by Age

Usage

derive_params_growth_age(
  dataset,
  sex,
  age,
  age_unit,
  meta_criteria,
  parameter,
  analysis_var,
  bmi_cdc_correction = FALSE,
  who_correction = FALSE,
  set_values_to_sds = NULL,
  set_values_to_pctl = NULL
)

Arguments

dataset

Input dataset

The variables specified in sex, age, age_unit, parameter, analysis_var are expected to be in the dataset.

sex

Sex

A character vector is expected.

Expected Values: M, F

age

Current Age

A numeric vector is expected. Note that this is the actual age at the current visit.

age_unit

Age Unit A character vector is expected.

Expected values: days, weeks, months

meta_criteria

Metadata dataset

A metadata dataset with the following expected variables: AGE, AGEU, SEX, L, M, S

The dataset can be derived from CDC/WHO or user-defined datasets. The CDC/WHO growth chart metadata datasets are available in the package and will require small modifications.

If the age value from dataset falls between two AGE values in meta_criteria, then the L/M/S values that are chosen/mapped will be the AGE that has the smaller absolute difference to the value in age. e.g. If dataset has a current age of 27.49 months, and the metadata contains records for 27 and 28 months, the L/M/S corresponding to the 27 months record will be used.

  • AGE - Age

  • AGEU - Age Unit

  • SEX - Sex

  • L - Power in the Box-Cox transformation to normality

  • M - Median

  • S - Coefficient of variation

parameter

Anthropometric measurement parameter to calculate z-score or percentile

A condition is expected with the input dataset VSTESTCD/PARAMCD for which we want growth derivations:

e.g. parameter = VSTESTCD == "WEIGHT".

There is CDC/WHO metadata available for Height, Weight, BMI, and Head Circumference available in the admiralpeds package.

analysis_var

Variable containing anthropometric measurement

A numeric vector is expected, e.g. AVAL, VSSTRESN

bmi_cdc_correction

Extended CDC BMI-for-age correction

A logical scalar, e.g. TRUE/FALSE is expected. CDC developed extended percentiles (>95%) to monitor high BMI values, if set to TRUE the CDC's correction is applied.

who_correction

WHO adjustment for weight-based indicators

A logical scalar, e.g. TRUE/FALSE is expected. WHO constructed a restricted application of the LMS method for weight-based indicators. More details on these exact rules applied can be found at the document page 302 of the WHO Child Growth Standards Guidelines. If set to TRUE the WHO correction is applied.

set_values_to_sds

Variables to be set for Z-Scores

The specified variables are set to the specified values for the new observations. For example, set_values_to_sds(exprs(PARAMCD = "BMIASDS", PARAM = "BMI-for-age z-score")) defines the parameter code and parameter.

The formula to calculate the Z-score is as follows:

\frac{((\frac{obs}{M})^L - 1)}{L * S}

where "obs" is the observed value for the respective anthropometric measure being calculated.

Permitted Values: List of variable-value pairs

If left as default value, NULL, then parameter not derived in output dataset

set_values_to_pctl

Variables to be set for Percentile

The specified variables are set to the specified values for the new observations. For example, set_values_to_pctl(exprs(PARAMCD = "BMIAPCTL", PARAM = "BMI-for-age percentile")) defines the parameter code and parameter.

Permitted Values: List of variable-value pair

If left as default value, NULL, then parameter not derived in output dataset

Value

The input dataset additional records with the new parameter added.

See Also

Vital Signs Functions for adding Parameters/Records derive_params_growth_height()

Examples

library(dplyr, warn.conflicts = FALSE)
library(lubridate, warn.conflicts = FALSE)
library(rlang, warn.conflicts = FALSE)
library(admiral, warn.conflicts = FALSE)
library(pharmaversesdtm, warn.conflicts = FALSE)

advs <- pharmaversesdtm::dm_peds %>%
  select(USUBJID, BRTHDTC, SEX) %>%
  right_join(., pharmaversesdtm::vs_peds, by = "USUBJID") %>%
  mutate(
    VSDT = ymd(VSDTC),
    BRTHDT = ymd(BRTHDTC)
  ) %>%
  derive_vars_duration(
    new_var = AGECUR_D,
    new_var_unit = CURU_D,
    start_date = BRTHDT,
    end_date = VSDT,
    out_unit = "days",
    trunc_out = FALSE
  ) %>%
  derive_vars_duration(
    new_var = AGECUR_M,
    new_var_unit = CURU_M,
    start_date = BRTHDT,
    end_date = VSDT,
    out_unit = "months",
    trunc_out = FALSE
  ) %>%
  mutate(
    AGECUR = ifelse(AGECUR_D >= 365.25 * 2, AGECUR_M, AGECUR_D),
    AGECURU = ifelse(AGECUR_D >= 365.25 * 2, CURU_M, CURU_D)
  )

# metadata is in months
cdc_meta_criteria <- admiralpeds::cdc_htage %>%
  mutate(
    age_unit = "months",
    SEX = ifelse(SEX == 1, "M", "F")
  )

# metadata is in days
who_meta_criteria <- bind_rows(
  (admiralpeds::who_lgth_ht_for_age_boys %>%
    mutate(
      SEX = "M",
      age_unit = "days"
    )
  ),
  (admiralpeds::who_lgth_ht_for_age_girls %>%
    mutate(
      SEX = "F",
      age_unit = "days"
    )
  )
) %>%
  rename(AGE = Day)

criteria <- bind_rows(
  cdc_meta_criteria,
  who_meta_criteria
) %>%
  rename(AGEU = age_unit)

derive_params_growth_age(
  advs,
  sex = SEX,
  age = AGECUR,
  age_unit = AGECURU,
  meta_criteria = criteria,
  parameter = VSTESTCD == "HEIGHT",
  analysis_var = VSSTRESN,
  set_values_to_sds = exprs(
    PARAMCD = "HGTSDS",
    PARAM = "Height-for-age z-score"
  ),
  set_values_to_pctl = exprs(
    PARAMCD = "HGTPCTL",
    PARAM = "Height-for-age percentile"
  )
)

Derive Anthropometric indicators (Z-Scores/Percentiles-for-Height/Length) based on Standard Growth Charts

Description

Derive Anthropometric indicators (Z-Scores/Percentiles-for-Height/Length) based on Standard Growth Charts for Weight by Height/Length

Usage

derive_params_growth_height(
  dataset,
  sex,
  height,
  height_unit,
  meta_criteria,
  parameter,
  analysis_var,
  who_correction = FALSE,
  set_values_to_sds = NULL,
  set_values_to_pctl = NULL
)

Arguments

dataset

Input dataset

The variables specified in sex, height, height_unit, parameter, analysis_var are expected to be in the dataset.

sex

Sex

A character vector is expected.

Expected Values: M, F

height

Current Height/length

A numeric vector is expected. Note that this is the actual height/length at the current visit.

height_unit

Height/Length Unit A character vector is expected.

Expected values: cm

meta_criteria

Metadata dataset

A metadata dataset with the following expected variables: HEIGHT_LENGTH, HEIGHT_LENGTHU, SEX, L, M, S

The dataset can be derived from WHO or user-defined datasets. The WHO growth chart metadata datasets are available in the package and will require small modifications.

Datasets who_wt_for_lgth_boys/who_wt_for_lgth_girls are applicable for subject age < 730.5 days.

If the height value from dataset falls between two HEIGHT_LENGTH values in meta_criteria, then the L/M/S values that are chosen/mapped will be the HEIGHT_LENGTH that has the smaller absolute difference to the value in height. e.g. If dataset has a current age of 50.49 cm, and the metadata contains records for 50 and 51 cm, the L/M/S corresponding to the 50 cm record will be used.

  • HEIGHT_LENGTH - Height/Length

  • HEIGHT_LENGTHU - Height/Length Unit

  • SEX - Sex

  • L - Power in the Box-Cox transformation to normality

  • M - Median

  • S - Coefficient of variation

parameter

Anthropometric measurement parameter to calculate z-score or percentile

A condition is expected with the input dataset VSTESTCD/PARAMCD for which we want growth derivations:

e.g. parameter = VSTESTCD == "WEIGHT".

There is WHO metadata available for Weight available in the admiralpeds package. Weight measures are expected to be in the unit "kg".

analysis_var

Variable containing anthropometric measurement

A numeric vector is expected, e.g. AVAL, VSSTRESN

who_correction

WHO adjustment for weight-based indicators

A logical scalar, e.g. TRUE/FALSE is expected. WHO constructed a restricted application of the LMS method for weight-based indicators. More details on these exact rules applied can be found at the document page 302 of the WHO Child Growth Standards Guidelines. If set to TRUE the WHO correction is applied.

set_values_to_sds

Variables to be set for Z-Scores

The specified variables are set to the specified values for the new observations. For example, set_values_to_sds(exprs(PARAMCD = "WGTHSDS", PARAM = "Weight-for-height z-score")) defines the parameter code and parameter.

The formula to calculate the Z-score is as follows:

\frac{((\frac{obs}{M})^L - 1)}{L * S}

where "obs" is the observed value for the respective anthropometric measure being calculated.

Permitted Values: List of variable-value pairs

If left as default value, NULL, then parameter not derived in output dataset

set_values_to_pctl

Variables to be set for Percentile

The specified variables are set to the specified values for the new observations. For example, set_values_to_pctl(exprs(PARAMCD = "WGTHPCTL", PARAM = "Weight-for-height percentile")) defines the parameter code and parameter.

Permitted Values: List of variable-value pair

If left as default value, NULL, then parameter not derived in output dataset

Value

The input dataset additional records with the new parameter added.

See Also

Vital Signs Functions for adding Parameters/Records derive_params_growth_age()

Examples

library(dplyr, warn.conflicts = FALSE)
library(lubridate, warn.conflicts = FALSE)
library(rlang, warn.conflicts = FALSE)
library(admiral, warn.conflicts = FALSE)
library(pharmaversesdtm, warn.conflicts = FALSE)

# derive weight for height/length only for those under 2 years old using WHO
# weight for length reference file
advs <- pharmaversesdtm::dm_peds %>%
  select(USUBJID, BRTHDTC, SEX) %>%
  right_join(., pharmaversesdtm::vs_peds, by = "USUBJID") %>%
  mutate(
    VSDT = ymd(VSDTC),
    BRTHDT = ymd(BRTHDTC)
  ) %>%
  derive_vars_duration(
    new_var = AAGECUR,
    new_var_unit = AAGECURU,
    start_date = BRTHDT,
    end_date = VSDT,
    out_unit = "days"
  )

heights <- pharmaversesdtm::vs_peds %>%
  filter(VSTESTCD == "HEIGHT") %>%
  select(USUBJID, VSSTRESN, VSSTRESU, VSDTC) %>%
  rename(
    HGTTMP = VSSTRESN,
    HGTTMPU = VSSTRESU
  )

advs <- advs %>%
  right_join(., heights, by = c("USUBJID", "VSDTC"))

advs_under2 <- advs %>%
  filter(AAGECUR < 730.5)

who_under2 <- bind_rows(
  (admiralpeds::who_wt_for_lgth_boys %>%
    mutate(
      SEX = "M",
      height_unit = "cm"
    )
  ),
  (admiralpeds::who_wt_for_lgth_girls %>%
    mutate(
      SEX = "F",
      height_unit = "cm"
    )
  )
) %>%
  rename(
    HEIGHT_LENGTH = Length,
    HEIGHT_LENGTHU = height_unit
  )

derive_params_growth_height(
  advs_under2,
  sex = SEX,
  height = HGTTMP,
  height_unit = HGTTMPU,
  meta_criteria = who_under2,
  parameter = VSTESTCD == "WEIGHT",
  analysis_var = VSSTRESN,
  who_correction = TRUE,
  set_values_to_sds = exprs(
    PARAMCD = "WGTHSDS",
    PARAM = "Weight-for-height/length z-score"
  ),
  set_values_to_pctl = exprs(
    PARAMCD = "WGTHPCTL",
    PARAM = "Weight-for-height/length percentile"
  )
)

Find closest bin

Description

Find closest bin

Usage

find_closest_bin(param, breaks, labels)

Arguments

param

Parameter

Vector containing parameter that needs closest bin checking

breaks

Breaks created in get_bins()

labels

Labels created in get_bins()

Value

detects appropriate bin

See Also

Other internal: admiralpeds-package, get_bins(), set_bins()

Get Bins of Metadata

Description

Creates unique age/heights-bins for each record to speed up joining

Usage

get_bins(meta_criteria, param)

Arguments

meta_criteria

Metadata dataset

A metadata dataset that is the same as that in derive_params_growth_age()/derive_params_growth_height()

param

Character vector

Accepted values: "AGE"/"HEIGHT_LENGTH"

Value

list of breaks and labels for age/height bins

See Also

Other internal: admiralpeds-package, find_closest_bin(), set_bins()

Set Age/Height Bins

Description

Adds the unique age/height-bins to each dataframe to have a column for by in join.

Usage

set_bins(param, breaks, labels)

Value

Character vector of unique age/height bins based on metadata

See Also

Other internal: admiralpeds-package, find_closest_bin(), get_bins()

WHO BMI-for-age for boys

Description

WHO BMI-for-age charts for boys from day 0 (birth) to day 1856

Usage

who_bmi_for_age_boys

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/toolkits/child-growth-standards/standards/body-mass-index-for-age-bmi-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO BMI-for-age for girls

Description

WHO BMI-for-age charts for girls from day 0 (birth) to day 1856

Usage

who_bmi_for_age_girls

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/toolkits/child-growth-standards/standards/body-mass-index-for-age-bmi-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO Head circumference-for-age for boys

Description

WHO Head circumference-for-age charts for boys from day 0 (birth) to day 1856

Usage

who_hc_for_age_boys

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/toolkits/child-growth-standards/standards/head-circumference-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO Head circumference-for-age for girls

Description

WHO Head circumference-for-age charts for girls from day 0 (birth) to day 1856

Usage

who_hc_for_age_girls

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/toolkits/child-growth-standards/standards/head-circumference-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO Length/height-for-age for boys

Description

WHO Length/height-for-age charts for boys from day 0 (birth) to day 1856

Usage

who_lgth_ht_for_age_boys

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

integer Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/tools/child-growth-standards/standards/length-height-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO Length/height-for-age for girls

Description

WHO Length/height-for-age charts for girls from day 0 (birth) to day 1856

Usage

who_lgth_ht_for_age_girls

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

integer Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/tools/child-growth-standards/standards/length-height-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO Weight-for-age for boys

Description

WHO Weight-for-age charts for boys from day 0 (birth) to day 1856

Usage

who_wt_for_age_boys

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/tools/child-growth-standards/standards/weight-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_girls, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO Weight-for-age for girls

Description

WHO Weight-for-age charts for girls from day 0 (birth) to day 1856

Usage

who_wt_for_age_girls

Format

A data frame with 1857 rows and 4 variables:

Day

integer Age in days

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/tools/child-growth-standards/standards/weight-for-age

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_lgth_boys, who_wt_for_lgth_girls

WHO Weight-for-length for boys

Description

WHO Weight-for-length charts for boys from 45cm to 110cm

Usage

who_wt_for_lgth_boys

Format

A data frame with 651 rows and 4 variables:

Length

double Length in cm

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/tools/child-growth-standards/standards/weight-for-length-height

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_girls

WHO Weight-for-length for girls

Description

WHO Weight-for-length charts for girls from 45cm to 110cm

Usage

who_wt_for_lgth_girls

Format

A data frame with 651 rows and 4 variables:

Length

double Length in cm

L

double Box-Cox transformation for normality

M

double Median

S

double Coefficient of variation

Source

https://www.who.int/tools/child-growth-standards/standards/weight-for-length-height

See Also

Metadata cdc_bmiage, cdc_htage, cdc_wtage, derive_interp_records(), who_bmi_for_age_boys, who_bmi_for_age_girls, who_hc_for_age_boys, who_hc_for_age_girls, who_lgth_ht_for_age_boys, who_lgth_ht_for_age_girls, who_wt_for_age_boys, who_wt_for_age_girls, who_wt_for_lgth_boys