| Title: | Data and Methods Around Reference Values in Pediatrics |
|---|---|
| Description: | Calculation of standard deviation scores and percentiles adduced from different standards (WHO, UK, Germany, Italy, China, etc). Also, references for laboratory values in children and adults are available, e.g., serum lipids, iron-related blood parameters, IGF, liver enzymes. See package documentation for full list. |
| Authors: | Mandy Vogel [aut, cre] |
| Maintainer: | Mandy Vogel <[email protected]> |
| License: | GPL-3 |
| Version: | 0.9.11 |
| Built: | 2025-03-26 17:53:43 UTC |
| Source: | https://github.com/cran/childsds |
change saturation and brightness of given colors
adjust_colors(colors, saturation_factor = 1, brightness_factor = 1)adjust_colors(colors, saturation_factor = 1, brightness_factor = 1)
colors |
vector of hex colors |
saturation_factor |
factor |
brightness_factor |
factor |
vector of adjusted colors
Mandy Vogel
Parameters from recommendations of the German Adiposity Association (2015, AGA)
aga_15.refaga_15.ref
"Kromeyer-Hauschild K, Moss A, Wabitsch M. Referenzwerte fuer den Body-Mass-Index fuer Kinder, Jugendliche und Erwachsene in Deutschland. Adipositas - Ursachen, Folgeerkrankungen, Therapie. 2015;09(3):123-7."
aggregate lms parameters
aggregate_lms(lms.list)aggregate_lms(lms.list)
lms.list |
list of parameter tables as returned by do_iterations() |
function takes the lms part of the result from the do_iterations() function and returns the mean parameters
list of dataframes containing the aggregated parameters, each for every level of sex
Mandy Vogel
Parameters derived from Flandern population
belgium.refbelgium.ref
Roelants M, Hauspie R, Hoppenbrouwers K. References for growth and pubertal development from birth to 21 years in Flanders, Belgium. Annals of Human Biology. 2009 Dezember;36(6):680-94.
Parameters for different bone parameters
bone.refbone.ref
Geserick M, Vogel M, Eckelt F, et al. Children and adolescents with obesity have reduced serum bone turnover markers and 25-hydroxyvitamin D but increased parathyroid hormone concentrations – Results derived from new pediatric reference ranges. Bone 2020;132:115124 and Eberle et al. unpublishedfor VitD binding protein
Parameters from Wuehl et al. blood pressure reference values Germany according to age, from version 0.7.3 unplausible values are replaced by interpolated ones. For the original values check out earlier versions
bp_wuehl_age.refbp_wuehl_age.ref
"Wuehl E, Witte K, Soergel M, Mehls O, Schaefer F, Hypertension for the GWG on P. Distribution of 24-h ambulatory blood pressure in children: normalized reference values and role of body dimensions. Journal of Hypertension. 2002 Oct;20(10):1995.", implausible values were replaced by interpolated ones from package version 0.7.4
Parameters from Wuehl et al. blood pressure reference values Germany according to height from version 0.7.3 unplausible values are replaced by interpolated ones. For the original values check out earlier versions
bp_wuehl_height.refbp_wuehl_height.ref
"Wuehl E, Witte K, Soergel M, Mehls O, Schaefer F, Hypertension for the GWG on P. Distribution of 24-h ambulatory blood pressure in children: normalized reference values and role of body dimensions. Journal of Hypertension. 2002 Oct;20(10):1995.", implausible values were replaced by interpolated ones from package version 0.7.4
Calculate confidence intervals
calc_confints( lms.list, perc = c(2.5, 5, 50, 95, 97.5), level = 0.95, type = c("point") )calc_confints( lms.list, perc = c(2.5, 5, 50, 95, 97.5), level = 0.95, type = c("point") )
lms.list |
lms part of the returned list of |
perc |
percentiles for which the confidence bands are calculated |
level |
confidence level |
type |
for now only point is a valid value |
The function takes a lms list as returned by do_iterations and
calculates the confidence bands for a given set of percentiles using
envelope from the boot package
list containing the respective confidence envelopes
mandy
Calculate percentage relative to a given base percentile
calc_percent_excess( bmi = NULL, age = NULL, sex = NULL, ref.perc = 50, ref, item = "bmi", rownr = NULL )calc_percent_excess( bmi = NULL, age = NULL, sex = NULL, ref.perc = 50, ref, item = "bmi", rownr = NULL )
bmi |
vector of bmi |
age |
vector of age |
sex |
vector of sex (coding "male" and "female") is assumend |
ref.perc |
single value: reference percentile (0,100) |
ref |
RefGroup object |
item |
item within ref |
rownr |
indicator of order |
The function calculates the percentage of a given bmi value relative to a specific percentile
vector containing values between 0 and 1
Mandy Vogel
LMS Parameters for the Centers for Disease Control and Prevention 2000 Growth Charts, contains bmi, height, head cirumference, weight, weight for length,
cdc.refcdc.ref
National health statitics reports 63.
Parameters for height of normal weight and obese children from the CrescNet database dependent on height
cn.refcn.ref
"Kempf et al. In progress"
Parameters for bmi from Cole and Lobstein, 2012
cole_lobstein.refcole_lobstein.ref
Cole TJ, Lobstein T. Extended international (IOTF) body mass index cut-offs for thinness, overweight and obesity. Pediatric Obesity 2012;7(4):284–94.
Parameters of skinfold measures derived from Colombian population
colombia_sf.refcolombia_sf.ref
Ramirez-Velez, R. et al. Triceps and Subscapular Skinfold Thickness Percentiles and Cut-Offs for Overweight and Obesity in a Population-Based Sample of Schoolchildren and Adolescents in Bogota, Colombia. Nutrients 8, (2016).
Do lms iterations
do_iterations( data.list, n = 10, max.it = 1000, method = "gamlss", prop.fam = 0.75, prop.subject = 1, age.min = 0, age.max = 18, age.int = 1/12, x2.min = 25, x2.max = 42, x2.int = 1/12, keep.models = F, dist = "BCCGo", mu.df = 4, sigma.df = 3, nu.df = 2, tau.df = 2, verbose = F, formula = NULL, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, method.pb = "ML", trans.x = F, lim.trans = c(0, 1.5) )do_iterations( data.list, n = 10, max.it = 1000, method = "gamlss", prop.fam = 0.75, prop.subject = 1, age.min = 0, age.max = 18, age.int = 1/12, x2.min = 25, x2.max = 42, x2.int = 1/12, keep.models = F, dist = "BCCGo", mu.df = 4, sigma.df = 3, nu.df = 2, tau.df = 2, verbose = F, formula = NULL, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, method.pb = "ML", trans.x = F, lim.trans = c(0, 1.5) )
data.list |
list of dataframes as returned by prepare_data |
n |
number of desired fits |
max.it |
maximum number of iterations that will be run |
method |
use vgam or gamlss |
prop.fam |
proportion of families to be sampled |
prop.subject |
proportion of subject to be sampled |
age.min |
lower bound of age |
age.max |
upper bound of age |
age.int |
stepwidth of the age variable |
x2.min |
minimum limit for the second predictor |
x2.max |
maximum limit for the second predictor |
x2.int |
interval length between knots saved |
keep.models |
indicator whether or not models in each iteration should be kept |
dist |
distribution used for the fitting process, has to be one of BCCGo, BCPEo, BCTo as they are accepted by lms() |
mu.df |
degree of freedem location parameter |
sigma.df |
degree of freedem spread parameter |
nu.df |
degree of freedem skewness parameter |
tau.df |
degree of freedem kurtosis parameter |
verbose |
whether or not information about sampling will be printed during while iterate |
formula |
formula for the location parameter |
sigma.formula |
formula for the sigma parameter |
nu.formula |
formula for the nu parameter |
tau.formula |
formula for the tau parameter |
method.pb |
GAIC or ML |
trans.x |
indicator wether age should be transformed or not |
lim.trans |
limits for the exponent of transformation of age |
function samples families, samples measurements (and subjects), fits the model for a given number of iterations
list of lists for models and fitted parameters
Mandy Vogel
Parameters for different carotid artery intima-media thickness and distensibility dependent on age
doyon_age.refdoyon_age.ref
"Doyon A, Kracht D, Bayazit AK, et al. Carotid artery intima-media thickness and distensibility in children and adolescents: reference values and role of body dimensions. Hypertension 2013;62(3):550-6"
Parameters for different carotid artery intima-media thickness and distensibility dependent on height
doyon_height.refdoyon_height.ref
"Doyon A, Kracht D, Bayazit AK, et al. Carotid artery intima-media thickness and distensibility in children and adolescents: reference values and role of body dimensions. Hypertension 2013;62(3):550-6"
dummy function to call a function of the gamlss.dist package
dummy.refs(ref, item)dummy.refs(ref, item)
ref |
reference object |
item |
item name specifiying the reference |
dummy function to call a function of the gamlss.dist package
dummy output
Mandy Vogel
Parameters for bodyfat ( for Whites, Blacks, and Mexican-Americans
duran_bf.refduran_bf.ref
"Duran I, Martakis K, Rehberg M, Stark C, Schafmeyer L, Schoenau E. Reference Centiles for the Evaluation of Nutritional Status in Children using Body Fat Percentage, Fat Mass and Lean Body Mass Index. Journal of Clinical Densitometry [Internet] 2019 [cited 2019 Mar 19];Available from: https://linkinghub.elsevier.com/retrieve/pii/S1094695018302622"
Parameters derived Ethiopian children
ethiop.refethiop.ref
Amare, E. B. et al. Reference Ranges for Head Circumference in Ethiopian Children 0–2 Years of Age. World Neurosurgery 84, 1566–1571.e2 (2015).
fit gamlss
fit_gamlss( data, age.min = 0.25, age.max = 18, age.int = 1/12, keep.models = F, dist = "BCCGo", mu.df = 4, sigma.df = 3, nu.df = 2, tau.df = 2, trans.x = F, lim.trans = c(0, 1.5), value, tmpdata )fit_gamlss( data, age.min = 0.25, age.max = 18, age.int = 1/12, keep.models = F, dist = "BCCGo", mu.df = 4, sigma.df = 3, nu.df = 2, tau.df = 2, trans.x = F, lim.trans = c(0, 1.5), value, tmpdata )
data |
dataframe as return by select_meas() |
age.min |
lower bound of age |
age.max |
upper bound of age |
age.int |
stepwidth of the age variable |
keep.models |
indicator whether or not models in each iteration should be kept |
dist |
distribution used for the fitting process, has to be one of BCCGo, BCPEo, BCTo as they are accepted by lms() |
mu.df |
degree of freedem location parameter |
sigma.df |
degree of freedem spread parameter |
nu.df |
degree of freedem skewness parameter |
tau.df |
degree of freedem kurtosis parameter |
trans.x |
indicator wether age should be transformed or not |
lim.trans |
limits for the exponent of transformation of age |
value |
names of the value variable (character) if different from value, ignored |
tmpdata |
ignored |
wrapper around the lms function in the gamlss package
returns the fitted lms-parameter at given age points
the function is called inside do_iterations and may not called directly
list containing a dataframe of the fitted lms parameter at the given age points and the fitted model
Mandy Vogel
fit_gamlss 2dim
fit_gamlss_2d( data, age.min = 0, age.max = 80, age.int = 1/12, x2.min = 25, x2.max = 42, x2.int = 1, keep.models = F, dist = "BCCGo", formula = NULL, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, method.pb = "ML" )fit_gamlss_2d( data, age.min = 0, age.max = 80, age.int = 1/12, x2.min = 25, x2.max = 42, x2.int = 1, keep.models = F, dist = "BCCGo", formula = NULL, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, method.pb = "ML" )
data |
dataframe as return by select_meas() |
age.min |
lower bound of age |
age.max |
upper bound of age |
age.int |
stepwidth of the age variable |
x2.min |
minimum limit for the second predictor |
x2.max |
maximum limit for the second predictor |
x2.int |
interval length between knots saved |
keep.models |
indicator whether or not models in each iteration should be kept |
dist |
distribution used for the fitting process, has to be one of BCCGo, BCPEo, BCTo as they are accepted by lms() |
formula |
formula for the location parameter |
sigma.formula |
formula for the sigma parameter |
nu.formula |
formula for the nu parameter |
tau.formula |
formula for the tau parameter |
method.pb |
GAIC or ML |
wrapper around the gamlss function from the gamlss package
returns the fitted lms-parameter at given age points
the function is called inside do_iterations and may not be called directly
list containing a dataframe of the fitted lms parameter at the given age points and the fitted model
Mandy Vogel
fit_gamlss1
fit_gamlss1( data, age.min = 0, age.max = 80, age.int = 1/12, keep.models = F, dist = "BCCGo", formula = NULL, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, method.pb = "ML" )fit_gamlss1( data, age.min = 0, age.max = 80, age.int = 1/12, keep.models = F, dist = "BCCGo", formula = NULL, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, method.pb = "ML" )
data |
dataframe as return by select_meas() |
age.min |
lower bound of age |
age.max |
upper bound of age |
age.int |
stepwidth of the age variable |
keep.models |
indicator whether or not models in each iteration should be kept |
dist |
distribution used for the fitting process, has to be one of BCCGo, BCPEo, BCTo as they are accepted by lms() |
formula |
formula for the location parameter |
sigma.formula |
formula for the sigma parameter |
nu.formula |
formula for the nu parameter |
tau.formula |
formula for the tau parameter |
method.pb |
GAIC or ML |
wrapper around the gamlss function from the gamlss package
returns the fitted lms-parameter at given age points
the function is called inside do_iterations and may not be called directly
list containing a dataframe of the fitted lms parameter at the given age points and the fitted model
Mandy Vogel
fit vgam
fit_vgam( data, age.min = 0.25, age.max = 18, age.int = 1/12, keep.models = F, dist = "BCN", mu.df = 4, sigma.df = 3, nu.df = 2, value )fit_vgam( data, age.min = 0.25, age.max = 18, age.int = 1/12, keep.models = F, dist = "BCN", mu.df = 4, sigma.df = 3, nu.df = 2, value )
data |
dataframe as return by select_meas() |
age.min |
lower bound of age |
age.max |
upper bound of age |
age.int |
stepwidth of the age variable |
keep.models |
indicator whether or not models in each iteration should be kept |
dist |
distribution used for the fitting process, has to be one of BCCGo, BCPEo, BCTo as they are accepted by lms() |
mu.df |
degree of freedem location parameter |
sigma.df |
degree of freedem spread parameter |
nu.df |
degree of freedem skewness parameter |
value |
names of the value variable (character) if different from value, ignored |
wrapper around the vgam function in the VGAM package
returns the fitted lms-parameter at given age points
the function is called inside do_iterations and may not called directly
list containing a dataframe of the fitted lms parameter at the given age points and the fitted model
mandy
Parameters derived from Dutch children (additional to nl4.ref)
fredriks05.reffredriks05.ref
Fredriks, A. M. et al. Nationwide age references for sitting height, leg length, and sitting height/height ratio, and their diagnostic value for disproportionate growth disorders. Archives of Disease in Childhood 90, 807–812 (2005)
Parameters for height, weight, sitting height, etc from Ghouili, 2021
ghouili_anthro.refghouili_anthro.ref
Ghouili H, Ouerghi N, Boughalmi A, Dridi A, Rhibi F, Bouassida A. First growth reference curves for Tunisian children and adolescents. Archives de Pediatrie 2021;28(5):381–91
Parameters for BMI and TMI from Gomez, 2021
gomez_bmitmi.refgomez_bmitmi.ref
Gomez-Campos R, Vidal-Espinoza R, Marques de Moraes A, et al. Comparison of Anthropometric Indicators That Assess Nutritional Status From Infancy to Old Age and Proposal of Percentiles for a Regional Sample of Chile. Frontiers in Nutrition 2021 [cited 2022 May 28];8. Available from: https://www.frontiersin.org/article/10.3389/fnut.2021.657491
International Laboratory Parameters Tables
international_lab.refinternational_lab.ref
Bidlingmaier, M., Friedrich, N., Emeny, R.T., Spranger, J., Wolthers, O.D., Roswall, J., Koerner, A., Obermayer-Pietsch, B., Huebener, C., Dahlgren, J., others, 2014. Reference intervals for insulin-like growth factor-1 (IGF-I) from birth to senescence: results from a multicenter study using a new automated chemiluminescence IGF-I immunoassay conforming to recent international recommendations. The Journal of Clinical Endocrinology & Metabolism 99, 1712-1721.
Friedrich, N., Wolthers, O.D., Arafat, A.M., Emeny, R.T., Spranger, J., Roswall, J., Kratzsch, J., Grabe, H.J., Huebener, C., Pfeiffer, A.F.H., Doering, A., Bielohuby, M., Dahlgren, J., Frystyk, J., Wallaschofski, H., Bidlingmaier, M., 2014. Age- and Sex-Specific Reference Intervals Across Life Span for Insulin-Like Growth Factor Binding Protein 3 (IGFBP-3) and the IGF-I to IGFBP-3 Ratio Measured by New Automated Chemiluminescence Assays. The Journal of Clinical Endocrinology & Metabolism 99, 1675-1686. doi:10.1210/jc.2013-3060
Parameters for iron-related blood parameters in children
iron.refiron.ref
Rieger, K. et al. Reference intervals for iron-related blood parameters: results from a population-based cohort study (LIFE Child). LaboratoriumsMedizin 40, (2016).
Parameters derived from Italian children
italian.refitalian.ref
Cacciari E, Milani S, Balsamo A, Spada E, Bona G, Cavallo L, et al. Italian cross-sectional growth charts for height, weight and BMI (2 to 20 yr). J Endocrinol Invest. 2006 Jul 1;29(7):581–93.
Parameters of serum insulin-like growth factor-I (IGF-I)
japan_lab.refjapan_lab.ref
Isojima, T., Shimatsu, A., Yokoya, S., Chihara, K., Tanaka, T., Hizuka, N., Teramoto, A., Tatsumi, K., Tachibana, K., Katsumata, N., Horikawa, R., 2012. Standardized centile curves and reference intervals of serum insulin-like growth factor-I (IGF-I) levels in a normal Japanese population using the LMS method. Endocrine Journal 59, 771-780. doi:10.1507/endocrj.EJ12-0110
Parameters derived from Japanese children
japanese.refjapanese.ref
Inokuchi, M., Matsuo, N., Anzo, M., Takayama, J. I. & Hasegawa, T. Age-dependent percentile for waist circumference for Japanese children based on the 1992–1994 cross-sectional national survey data. Eur J Pediatr 166, 655–661 (2007)
Parameters for Cardiovascular Magnetic Resonance
kawel_boehm.refkawel_boehm.ref
Kawel-Boehm N, Hetzel SJ, Ambale-Venkatesh B, et al. Reference ranges (normal values) for cardiovascular magnetic resonance (CMR) in adults and children: 2020 update. Journal of Cardiovascular Magnetic Resonance 2020;22(1):87.
Parameters derived from the German KiGGS cohort
kiggs_bp.refkiggs_bp.ref
contains 2-dimensional reference grid. Do not use with sds but sds_2d
Neuhauser, H. K., Thamm, M., Ellert, U., Hense, H. W. & Rosario, A. S. Blood Pressure Percentiles by Age and Height from Nonoverweight Children and Adolescents in Germany. Pediatrics peds.2010-1290 (2011). doi:10.1542/peds.2010-1290.
Parameters regarding lightness and height-to-mass ratio
kiggs_lightness.refkiggs_lightness.ref
Kliegl et al. in preparation
LMS Parameters for German reference data (KiGGS, 2003-2006) for height, weight, bmi, hip, whr, whtr, bodyfat, skinfold sum, triceps skinfold, subscapular skinfold, and waist circumference
kiggs.refkiggs.ref
Referenzperzentile fuer anthropometrische Masszahlen und Blutdruck aus KiGGS 2003-2006, Robert Koch Institut, Germany
Parameters for fat and lean mass from Kirk, 2021
kirk_bf.refkirk_bf.ref
Kirk B, Bani Hassan E, Brennan-Olsen S, et al. Body composition reference ranges in community-dwelling adults using dual-energy X-ray absorptiometry: the Australian Body Composition (ABC) Study. Journal of Cachexia, Sarcopenia and Muscle 2021;12(4):880–90.
LMS Parameters for German reference data (Kromeyer Hauschild, 2001) for height, weight, bmi, and waist circumference, including preterm correction (Voigt) and census data for ages 18+ to 92 years
kro.refkro.ref
Perzentile fuer den Body-mass-Index fuer das Kindes- und Jugendalter unter Heranziehung verschiedener deutscher Stichproben, Monatsschrift Kinderheilkunde August 2001, Volume 149, Issue 8, pp 807-818; Fruehgeborenenkorrektur nach Voigt
LMS Parameters for German reference data (Kromeyer Hauschild, 2015) for height, weight, bmi, and waist circumference, including preterm correction (Voigt) and Kromyer-Hausschild 2015
kro.ref15kro.ref15
Perzentile fuer den Body-mass-Index fuer das Kindes- und Jugendalter unter Heranziehung verschiedener deutscher Stichproben, Monatsschrift Kinderheilkunde August 2001, Volume 149, Issue 8, pp 807-818; preterm adjustment Voigt; Adults: Kromeyer-Hauschild K, Moss A, Wabitsch M. Referenzwerte für den Body-Mass-Index für Kinder, Jugendliche und Erwachsene in Deutschland. Adipositas - Ursachen, Folgeerkrankungen, Therapie. 2015;09(3):123-127. doi:10.1055/s-0037-1618928
Parameters for leptin dependent on age/puberty and bmi
leptin.refleptin.ref
Brandt-Hedunemann et al. In preparation
Parameters for IGF-1 from Liao, 2016
liao_igf1.refliao_igf1.ref
Liao ZH, Yin QQ, Wan JX, He W, Ji W, Zhang LY, et al. Serum Insulin-like growth factor-1 levels of healthy adults in southern China. Endocr J. 2016 Dec 30;63(12):1081–6.
Parameters for alkaline phosphatase
life_ap.reflife_ap.ref
Strauch, J.-M., Vogel, M., Meigen, C., Ceglarek, U., Kratzsch, J., Willenberg, A., Kiess, W., 2023. Pediatric reference values of alkaline phosphatase: Analysis from a German population-based cohort and influence of anthropometric and blood parameters. Bone 174, 116809. https://doi.org/10.1016/j.bone.2023.116809
Parameters for complete blood count
life_cbc.reflife_cbc.ref
Sommer et al. In preparation
Parameters for different circumferences and whr and whtr
life_circ.reflife_circ.ref
"Roennecke E, Vogel M, Bussler S, Grafe N, Jurkutat A, Schlingmann M, Koerner A, Kiess W. Age- and sex-related percentiles of skinfold thickness, waist and hip circumference, Waist-to- Hip Ratio and Waist-to-Height Ratio: Results from a population-based paediatric cohort in Germany (LIFE Child). Obesity Facts. 2019."
Parameters for creatine kinase
life_ck.reflife_ck.ref
Publication in Preparation
Parameters for different metabolom parameters from the LIFE Child cohort
life_cysc.reflife_cysc.ref
"Ziegelasch N, Vogel M, Müller E, et al. Cystatin C Serum Levels in Healthy Children Are Related to Age, Gender, and Pubertal Stage. Pediatr Nephrol 2019; 34: 449–57."
Parameters for fibroscan from the LIFE Child cohort
life_fibroscan.reflife_fibroscan.ref
Brunnert, L., Puasa, I.D., Garten, A., Penke, M., Gaul, S., Grafe, N., Karlas, T., Kiess, W., Flemming, G., Vogel, M., 2022. Pediatric percentiles for transient elastography measurements - effects of age, sex, weight status and pubertal stage. Front Endocrinol (Lausanne) 13, 1030809. https://doi.org/10.3389/fendo.2022.1030809
Parameters regarding folate and cobalamine
life_folb12.reflife_folb12.ref
Kreusler, P., Vogel, M., Willenberg, A., Baber, R., Dietz, Y., Körner, A., Ceglarek, U., Kiess, W., 2021. Folate and Cobalamin Serum Levels in Healthy Children and Adolescents and Their Association with Age, Sex, Bmi and Socioeconomic Status. Nutrients 13. https://doi.org/10.3390/nu13020546
Parameters for hba1c based on a child cohort a) including overweight and b) excluding overweight children
Parameters regarding HbA1c
life_hba1c.ref life_hba1c.reflife_hba1c.ref life_hba1c.ref
"Hovestadt, I., Kiess, W., Lewien, C., Willenberg, A., Poulain, T., Meigen, C., Körner, A., Vogel, M., 2022. HbA1c Percentiles and the Association between BMI, Age, Gender, Puberty and HbA1c Levels in Healthy German Children and Adolescents. Pediatr Diabetes 23, 194–202. https://doi.org/10.1111/pedi.13297"
Hovestadt, I., Kiess, W., Lewien, C., Willenberg, A., Poulain, T., Meigen, C., Körner, A., Vogel, M., 2022. HbA1c Percentiles and the Association between BMI, Age, Gender, Puberty and HbA1c Levels in Healthy German Children and Adolescents. Pediatr Diabetes 23, 194–202. https://doi.org/10.1111/pedi.13297
hs-Troponin T and NT-proBNP from the LIFE Child cohort
Parameters for heart markers
life_heart.ref life_heart.reflife_heart.ref life_heart.ref
Kiess A, Green J, Willenberg A, et al. Age-dependent reference values for hs-Troponin T and NT-proBNP and determining factors in a cohort of healthy children (The LIFE child study). Pediatric Cardiology 2022.
Kiess, A., Green, J., Willenberg, A., Ceglarek, U., Dähnert, I., Jurkutat, A., Körner, A., Hiemisch, A., Kiess, W., Vogel, M., 2022. Age-Dependent Reference Values for Hs-Troponin T and Nt-Probnp and Determining Factors in a Cohort of Healthy Children (the Life Child Study). Pediatr Cardiol 43, 1071–1083. https://doi.org/10.1007/s00246-022-02827-x
IGF-I and IGF-BP3 from the LIFE Child cohort
life_igf.reflife_igf.ref
Hoerenz C, Vogel M, Wirkner K. BMI and contraceptives affect new age-, sex-, and puberty-adjusted IGF-I and IGFBP-3 reference ranges across life span. JCEM 2022 (in (minor) revision).
Parameters for serum liver enzymes
life_liver.reflife_liver.ref
Bussler et al, New pediatric percentiles of liver enzyme serum levels (ALT, AST, GGT): effects of age, sex, BMI and pubertal stage, Hepatology 2017
Parameters for oxyandrogenes
life_oxyandrogene.reflife_oxyandrogene.ref
Zeidler R, Wagner F, et al. in preparation
Parameters for shbg and testosterone-shbg-ratio
life_shbg.reflife_shbg.ref
Duergen P. et al. in preparation
Parameters for different skinfolds
life_skinfold.reflife_skinfold.ref
"Roennecke E, Vogel M, Bussler S, Grafe N, Jurkutat A, Schlingmann M, Koerner A, Kiess W. Age- and sex-related percentiles of skinfold thickness, waist and hip circumference, Waist-to- Hip Ratio and Waist-to-Height Ratio: Results from a population-based paediatric cohort in Germany (LIFE Child). Obesity Facts. 2019."
Parameters for steroid hormones
life_steroide.reflife_steroide.ref
Bae, Y.J., Zeidler, R., Baber, R., Vogel, M., Wirkner, K., Loeffler, M., Ceglarek, U., Kiess, W., Koerner, A., Thiery, J., Kratzsch, J., 2019. Reference intervals of nine steroid hormones over the life-span analyzed by LC-MS/MS: Effect of age, gender, puberty, and oral contraceptives. J. Steroid Biochem. Mol. Biol. 193, 105409. https://doi.org/10.1016/j.jsbmb.2019.105409
Parameters regarding soluble transferrin receptor
life_stfr.reflife_stfr.ref
Prenzel et al. In Preparation.
Parameters for TSH, FT3, FT4 from the LIFE Child cohort
life_thyr.reflife_thyr.ref
"Surup H., Vogel M., Koerner A., Hiemisch A., Oelkers L., Willenberg A., Kiess W., Kratzsch J. (2021). BMI and puberty have to be included into the interpretation of TSH, FT3 and FT4 measurements by new pediatric reference intervals. THYROID."
Parameters for vegf-d
life_vegf.reflife_vegf.ref
Arelin M. et al. in preparation
Parameters for cobalamin and folate (awkward)
life_vit.reflife_vit.ref
Kreusler, P., Vogel, M., Willenberg, A., Baber, R., Dietz, Y., Körner, A., Ceglarek, U., Kiess, W., 2021. Folate and Cobalamin Serum Levels in Healthy Children and Adolescents and Their Association with Age, Sex, Bmi and Socioeconomic Status. Nutrients 13. https://doi.org/10.3390/nu13020546
Parameters for left artrial volumne Linden et al,
linden_heart.reflinden_heart.ref
Linden, K. et al. (2019) Left Atrial Volumes and Phasic Function in Healthy Children: Reference Values Using Real-Time Three-Dimensional Echocardiography, Journal of the American Society of Echocardiography, 32(8), pp. 1036-1045.e9. doi:10.1016/j.echo.2019.03.018.
Parameters for serum lipids in children
lipids.reflipids.ref
Dathan-Stumpf, A. et al. Pediatric reference data of serum lipids and prevalence of dyslipidemia: Results from a population-based cohort in Germany. Clinical Biochemistry 49, 740–749 (2016). In addition non-hdl references are provided. Publication in progress (Maidowski et al).
Calculate raw values for percentile curve
make_percentile_tab( ref, item, perc = c(2.5, 5, 50, 95, 97.5), stack = F, age = NULL, include.pars = T, digits = 4, sex )make_percentile_tab( ref, item, perc = c(2.5, 5, 50, 95, 97.5), stack = F, age = NULL, include.pars = T, digits = 4, sex )
ref |
Refgroup object |
item |
name of the measurement item |
perc |
vector of percentiles to be calculated |
stack |
wether or not the data should be stacked, stacked data would most possibly be used in ggplot2 |
age |
desired values of age |
include.pars |
indicator whether or not parameters should be included |
digits |
specification of number of decimal places |
sex |
name of the sex variable (character) if different from sex, not functional in this version and therefore ignored |
calculates quantile values for given RefGroup and given percentiles
data frame either with the different percentiles as columns or, if stacked, as data frame with four columns: age, sex, variable, value
Mandy Vogel
ptab <- make_percentile_tab(ref = kro.ref, item = "height", perc = c(2.5,10,50,90,97.5), stack = TRUE) ggplot2::ggplot(ptab, ggplot2::aes(x = age, y = value, colour = variable)) + ggplot2::geom_line() + ggplot2::facet_wrap(~ sex, nrow = 2)ptab <- make_percentile_tab(ref = kro.ref, item = "height", perc = c(2.5,10,50,90,97.5), stack = TRUE) ggplot2::ggplot(ptab, ggplot2::aes(x = age, y = value, colour = variable)) + ggplot2::geom_line() + ggplot2::facet_wrap(~ sex, nrow = 2)
Calculate raw values for percentile curve
make_percentile_tab2d( ref, item, perc = c(2.5, 5, 50, 95, 97.5), stack = F, age = NULL, x2 = NULL, include.pars = T, digits = 4, sex )make_percentile_tab2d( ref, item, perc = c(2.5, 5, 50, 95, 97.5), stack = F, age = NULL, x2 = NULL, include.pars = T, digits = 4, sex )
ref |
Refgroup object |
item |
name of the measurement item |
perc |
vector of percentiles to be calculated |
stack |
wether or not the data should be stacked, stacked data would most possibly be used in ggplot2 |
age |
desired values of age |
x2 |
desired values of second covariate |
include.pars |
indicator whether or not parameters should be included |
digits |
specification of number of decimal places |
sex |
name of the sex variable (character) if different from sex, not functional in this version and therefore ignored |
calculates quantile values for given RefGroup and given percentiles
data frame either with the different percentiles as columns or, if stacked, as data frame with four columns: age, sex, variable, value
Mandy Vogel
ptab <- make_percentile_tab(ref = kro.ref, item = "height", perc = c(2.5,10,50,90,97.5), stack = TRUE) ggplot2::ggplot(ptab, ggplot2::aes(x = age, y = value, colour = variable)) + ggplot2::geom_line() + ggplot2::facet_wrap(~ sex, nrow = 2)ptab <- make_percentile_tab(ref = kro.ref, item = "height", perc = c(2.5,10,50,90,97.5), stack = TRUE) ggplot2::ggplot(ptab, ggplot2::aes(x = age, y = value, colour = variable)) + ggplot2::geom_line() + ggplot2::facet_wrap(~ sex, nrow = 2)
mean ridits for vectors of paired observations
mean_ridits(v, w, maxrank = max(v), minrank = NULL)mean_ridits(v, w, maxrank = max(v), minrank = NULL)
v |
vector 1 |
w |
vector 2 |
maxrank |
max possible rank |
minrank |
min possible rank |
2-element named vector
Mandy Vogel
Parameters for different metabolom parameters from the LIFE Child cohort
metabolom.refmetabolom.ref
"Hirschel, J., Vogel, M., Baber, R., Garten, A., Beuchel, C., Dietz, Y., Dittrich, J., Körner, A., Kiess, W., & Ceglarek, U. (2020). Relation of Whole Blood Amino Acid and Acylcarnitine Metabolome to Age, Sex, BMI, Puberty, and Metabolic Markers in Children and Adolescents. Metabolites, 10(4), 149. https://doi.org/10.3390/metabo10040149"
calculate mid mean ranks
mid.mean.ranks( v1, v2, maxrank = max(c(v2, v1)), minrank = NULL, conf.level = 0.05 )mid.mean.ranks( v1, v2, maxrank = max(c(v2, v1)), minrank = NULL, conf.level = 0.05 )
v1 |
vector of ranks |
v2 |
vector of ranks |
maxrank |
max possible rank |
minrank |
min possible rank |
conf.level |
confidence level alpha |
list of marginal mean ranks and mid ranks
Mandy Vogel
mock values for a given reference
mock_df(ref, item, n = 1000)mock_df(ref, item, n = 1000)
ref |
a valid RefGroup object |
item |
a valid imte present in ref |
n |
how many values should be created |
mock values for a given reference
data frame containing a age, sex, and value column
mandy
mock a value for a given reference
mock_value(ref, item, sex = c("male", "female"), age)mock_value(ref, item, sex = c("male", "female"), age)
ref |
a valid RefGroup object |
item |
a valid item present in ref |
sex |
character male or female |
age |
numeric age value |
the function creates a random value for a given age and sex value and a given reference
a random value from the conditional distribution (conditionally on age and sex)
mandy
mock values for a given reference, given age and given sex
mock_values(df, sex, age, ref, item)mock_values(df, sex, age, ref, item)
df |
data frame containing the age and sex |
sex |
name of the sex variable |
age |
name of the age variable |
ref |
a valid RefGroup object |
item |
a valid imte present in ref |
the function creates random values for given age and sex values and a given reference
data frame containing the additional column with random numbers
mandy
Parameters for the German MoMo study (sports test)
momo.refmomo.ref
"Niessner C, Utesch T, Oriwol D, et al. Representative Percentile Curves of Physical Fitness From Early Childhood to Early Adulthood: The MoMo Study. Front Public Health 2020;8. Available from: https://www.frontiersin.org/articles/10.3389/fpubh.2020.00458/full?report=reader"
Parameters for 5 subtests of the KiGGS Motorik Module
motor.refmotor.ref
"Sobek et al. In progress"
Parameters of skinfold measures derived from Colombian population
nl3.refnl3.ref
Fredriks, A. M. et al. Continuing positive secular growth change in The Netherlands 1955-1997. Pediatric research 47, 316-323 (2000).
Fredriks, A.M., van Buuren, S., Wit, J.M., Verloove-Vanhorick, S.P., 2000. Body index measurements in 1996-7 compared with 1980. Archives of disease in childhood 82, 107-112.
https://cran.r-project.org/package=AGD
Parameters derived from the 4th Dutch growth study
nl4.refnl4.ref
Fredriks, A. M. et al. Nationwide age references for sitting height, leg length, and sitting height/height ratio, and their diagnostic value for disproportionate growth disorders. Archives of Disease in Childhood 90, 807–812 (2005); Fredriks, A. M. et al. Height, weight, body mass index and pubertal development references for children of Moroccan origin in The Netherlands. Acta Paediatr. 93, 817–824 (2004); Fredriks, A. M. et al. Continuing positive secular growth change in The Netherlands 1955–1997. Pediatric research 47, 316–323 (2000); Fredriks, A. M. et al. Height, weight, body mass index and pubertal development reference values for children of Turkish origin in the Netherlands. Eur. J. Pediatr. 162, 788–793 (2003); Fredriks, A. M., van Buuren, S., Wit, J. M. & Verloove-Vanhorick, S. P. Body index measurements in 1996–7 compared with 1980. Archives of disease in childhood 82, 107–112 (2000); R package: AGD, Stef van Buuren, http://www.stefvanbuuren.nl/
Parameters for fat and lean mass from Ofenheimer et al., 2020
ofenheimer_bf.refofenheimer_bf.ref
Ofenheimer A, Breyer-Kohansal R, Hartl S, et al. Reference values of body composition parameters and visceral adipose tissue (VAT) by DXA in adults aged 18–81 years—results from the LEAD cohort. European Journal of Clinical Nutrition 2020;74(8):1181–91.
one iteration
one_iteration( data.list, method, prop.fam = 0.75, prop.subject = 1, age.min = 0, age.max = 18, age.int = 1/12, x2.min = 25, x2.max = 42, x2.int = 1/12, keep.models = F, dist = "BCCGo", formula = NULL, sigma.df = 3, nu.df = 2, mu.df = 4, tau.df = 2, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, verbose = F, trans.x = F, lim.trans = c(0, 1.5), method.pb = "ML" )one_iteration( data.list, method, prop.fam = 0.75, prop.subject = 1, age.min = 0, age.max = 18, age.int = 1/12, x2.min = 25, x2.max = 42, x2.int = 1/12, keep.models = F, dist = "BCCGo", formula = NULL, sigma.df = 3, nu.df = 2, mu.df = 4, tau.df = 2, sigma.formula = ~1, nu.formula = ~1, tau.formula = ~1, verbose = F, trans.x = F, lim.trans = c(0, 1.5), method.pb = "ML" )
data.list |
list of dataframes as returned by prepare_data |
method |
use vgam or gamlss |
prop.fam |
proportion of families to be sampled |
prop.subject |
proportion of subject to be sampled |
age.min |
lower bound of age |
age.max |
upper bound of age |
age.int |
stepwidth of the age variable |
x2.min |
minimum limit for the second predictor |
x2.max |
maximum limit for the second predictor |
x2.int |
interval length between knots saved |
keep.models |
indicator whether or not models in each iteration should be kept |
dist |
distribution used for the fitting process, has to be one of BCCGo, BCPEo, BCTo as they are accepted by lms() |
formula |
formula for the location parameter |
sigma.df |
degree of freedem spread parameter |
nu.df |
degree of freedem skewness parameter |
mu.df |
degree of freedem location parameter |
tau.df |
degree of freedem kurtosis parameter |
sigma.formula |
formula for the sigma parameter |
nu.formula |
formula for the nu parameter |
tau.formula |
formula for the tau parameter |
verbose |
whether or not information about sampling will be printed during while iterate |
trans.x |
indicator wether age should be transformed or not |
lim.trans |
limits for the exponent of transformation of age |
method.pb |
GAIC or ML |
function samples families then measurements and fits the model
the function is called inside do_iterations and may not called directly
list of lists each containing a dataframe of the fitted lms parameter at the given age points and the fitted model
Mandy Vogel
Reference tables
itemidentifier of the item
distnamed list which contains the distribution which was used in fitting the references. One entry for male and one for female
Parameters derived from Portuguese children
portug.refportug.ref
Chaves, R., Baxter-Jones, A., Souza, M., Santos, D. & Maia, J. Height, weight, body composition, and waist circumference references for 7-to 17-year-old children from rural Portugal. HOMO-Journal of Comparative Human Biology 66, 264–277 (2015).
prepare data for repeated iteration process
prepare_data( data, group = NULL, subject = "SIC", sex = NULL, value = "value", age = "age", x2 = "x2", lb = -Inf, ub = Inf )prepare_data( data, group = NULL, subject = "SIC", sex = NULL, value = "value", age = "age", x2 = "x2", lb = -Inf, ub = Inf )
data |
dataframe containing measurement values, age, sex, and subject identifier |
group |
optional variable indicating groups of subjects within the data frame in most cases (families) |
subject |
subject identifier |
sex |
column containing the sex (or any other stratum), ideally of type character, iteration process will run on each of the levels separately |
value |
numeric column containing the measurement values |
age |
numeric column containing the age |
x2 |
numeric column containing a second covariate |
lb |
optional - lower bound for age |
ub |
optional - upper bound for age |
given a dataframe, the column name of the subject identifier, sex, age, value and group colums, the function creates a dataframe containing only these five columns with the standard column names group, subject, sex, age, value. lines containing missing values are removed.
list of dataframes containing the columns group, subject, sex, age, value; one dataframe for every level of sex
Mandy Vogel
Parameters Preterm and Intrauterine
preterm.refpreterm.ref
Olsen, I.E., Lawson, M.L., Ferguson, A.N., Cantrell, R., Grabich, S.C., Zemel, B.S., Clark, R.H., 2015. BMI Curves for Preterm Infants. PEDIATRICS 135, e572-e581. doi:10.1542/peds.2014-2777
Olsen, I.E., Groveman, S.A., Lawson, M.L., Clark, R.H., Zemel, B.S., 2010. New intrauterine growth curves based on United States data. Pediatrics 125, e214-224. doi:10.1542/peds.2009-0913
propabilities
props(v, maxrank = max(v), minrank = NULL)props(v, maxrank = max(v), minrank = NULL)
v |
vector of ranks |
maxrank |
max possible rank |
minrank |
min possible rank |
1-dim contingency table
Mandy Vogel
color palette Pediatric research
prs_pal(pal = "orig", primary = "blue", other = "violet", direction = 1)prs_pal(pal = "orig", primary = "blue", other = "violet", direction = 1)
pal |
orig, sat or bright |
primary |
first colour for two-color scales, must be one of the scale colors |
other |
second colour for two-color scales |
direction |
if -1 one order of colours is reversed |
function of n
Mandy Vogel
Container for reference tables
namename of the reference group
refsList of references, each reference refers to one item and contains independent variable age, and the parameter values for both genders
citationsinformation about the sources of the references
infoadditional infos regarding the references
Mandy Vogel
data(kiggs.ref) print(kiggs.ref) data(ukwho.ref) print(ukwho.ref) data(who.ref) print(who.ref)data(kiggs.ref) print(kiggs.ref) data(ukwho.ref) print(ukwho.ref) data(who.ref) print(who.ref)
ridits from ranks
ridits.from.ranks(v, maxrank = max(v), minrank = NULL)ridits.from.ranks(v, maxrank = max(v), minrank = NULL)
v |
vector of ranks |
maxrank |
min possible rank |
minrank |
max possible rank |
vector of ridits
Mandy Vogel
Parameters for fat and lean mass from Ripka et al, 2020
ripka_bf.refripka_bf.ref
Ripka, W.L. et al. (2020) Lean mass reference curves in adolescents using dual-energy x-ray absorptiometry (DXA), PLOS ONE, 15(2), p. e0228646. doi:10.1371/journal.pone.0228646.
Parameters derived from Saudi children
saudi.refsaudi.ref
Mouzan, M. I. E., Salloum, A. A. A., Alqurashi, M. M., Herbish, A. S. A. & Omar, A. A. The LMS and Z scale growth reference for Saudi school-age children and adolescents. Saudi Journal of Gastroenterology 22, 331 (2016)
Shaik, S.A., El Mouzan, M.I., AlSalloum, A.A., AlHerbish, A.S., 2016. Growth reference for Saudi preschool children: LMS parameters and percentiles. Ann Saudi Med 36, 2-6. doi:10.5144/0256-4947.2016.2
discrete ggplot colour scale
scale_colour_prs( pal = "orig", primary = "blue", other = "violet", direction = 1, ... )scale_colour_prs( pal = "orig", primary = "blue", other = "violet", direction = 1, ... )
pal |
orig, sat, or bright |
primary |
primary colour of two |
other |
the other colour |
direction |
if -1 one order of colours is reversed |
... |
further argument |
colour scale for use with ggplot()
Mandy Vogel
discrete ggplot fill scale
scale_fill_prs( pal = "orig", primary = "blue", other = "violet", direction = 1, ... )scale_fill_prs( pal = "orig", primary = "blue", other = "violet", direction = 1, ... )
pal |
orig, sat, or bright |
primary |
primary colour of two |
other |
the other colour |
direction |
if -1 one order of colours is reversed |
... |
further arguments |
colour scale for use with ggplot()
Mandy Vogel
Uchu colour scale
scale_colour_uchu( pal = c("gray", "red", "pink", "purple", "blue", "green", "yellow", "orange", "general"), ... ) scale_fill_uchu( pal = c("gray", "red", "pink", "purple", "blue", "green", "yellow", "orange", "general"), ... )scale_colour_uchu( pal = c("gray", "red", "pink", "purple", "blue", "green", "yellow", "orange", "general"), ... ) scale_fill_uchu( pal = c("gray", "red", "pink", "purple", "blue", "green", "yellow", "orange", "general"), ... )
pal |
colour palette |
... |
further arguments to scale |
provides the uchu colour scale as ggplot2 colour scale (https://github.com/NeverCease/uchu)
ggplot colour scale
Mandy Vogel
Parameters for bone mineral content/density, fm, lm (lower limbs) from Schafmeyer, 2022
schafmeyer_leg.refschafmeyer_leg.ref
Schafmeyer L, Linden T, Sill H, Rehberg M, Schoenau E, Duran I. Pediatric Reference Centiles of Bone Mineral Density and Body Composition of Lower Limbs. Journal of Clinical Densitometry. 2022 Jan;25(1):73–80.
Calculate SDS values
sds(value, age, sex, item, ref, type = "SDS", male = "male", female = "female")sds(value, age, sex, item, ref, type = "SDS", male = "male", female = "female")
value |
vector of measurement values |
age |
vector of age values |
sex |
vector of sex |
item |
name of the item e.g. "height" |
ref |
RefGroup object |
type |
"SDS" or "perc" |
male |
coding of sex for male |
female |
coding of sex for female |
The function takes a vector of measurement values, and of age and of sex and a RefGroup object as arguments. It calculates the sds or percentile values.
vector containing SDS or percentile values
Mandy Vogel
anthro <- data.frame(age = c(11.61,12.49,9.5,10.42,8.42,10.75,9.57,10.48), height = c(148.2,154.4,141.6,145.3,146,140.9,145.5,150), sex = sample(c("male","female"), size = 8, replace = TRUE), weight = c(69.5,72.65,47.3,51.6,45.6,48.9,53.5,58.5)) anthro$height_sds <- sds(anthro$height, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "height", type = "SDS") anthro$bmi <- anthro$weight/(anthro$height**2) * 10000 anthro$bmi_perc <- sds(anthro$bmi, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "bmi", type = "perc") data(who.ref) x <- data.frame(height=c(50,100,60,54), sex=c("m","f","f","m"), age=c(0,2.9,0.6,0.2)) sds(value = x$height, age = x$age, sex = x$sex, male = "m", female = "f", ref = who.ref, item = "height")anthro <- data.frame(age = c(11.61,12.49,9.5,10.42,8.42,10.75,9.57,10.48), height = c(148.2,154.4,141.6,145.3,146,140.9,145.5,150), sex = sample(c("male","female"), size = 8, replace = TRUE), weight = c(69.5,72.65,47.3,51.6,45.6,48.9,53.5,58.5)) anthro$height_sds <- sds(anthro$height, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "height", type = "SDS") anthro$bmi <- anthro$weight/(anthro$height**2) * 10000 anthro$bmi_perc <- sds(anthro$bmi, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "bmi", type = "perc") data(who.ref) x <- data.frame(height=c(50,100,60,54), sex=c("m","f","f","m"), age=c(0,2.9,0.6,0.2)) sds(value = x$height, age = x$age, sex = x$sex, male = "m", female = "f", ref = who.ref, item = "height")
Calculate SDS values for 2-dimensional matrix of covariates – old version
sds_2d( value, age, x2, sex, item, ref, type = "SDS", male = "male", female = "female" )sds_2d( value, age, x2, sex, item, ref, type = "SDS", male = "male", female = "female" )
value |
vector of measurement values |
age |
vector of age values |
x2 |
second vector of covariates |
sex |
vector of sex |
item |
name of the item e.g. "height" |
ref |
RefGroup object |
type |
"SDS" or "perc" |
male |
coding of sex for male |
female |
coding of sex for male |
The function takes a vector of measurement values, and of age and a second covariate (like age and height for blood pressure) of sex and a RefGroup object as arguments. It calculates the sds or percentile values. This function is beta.
the function searches for the nearest given point in the reference grid.
From there, the SDS/percentile value will be calculated. Different from sds,
no interpolation will be applied. The procedure is according to Neuhauser et al. Blood
Pressure Percentiles by Age and Height from Nonoverweight Children and Adolescents
in Germany. 2011.
vector containing SDS or percentile values
Mandy Vogel
Calculate SDS values depending on the Tanner stage
sds_pub( value, pubstatus, sex, item, ref, type = "SDS", male = "male", female = "female" )sds_pub( value, pubstatus, sex, item, ref, type = "SDS", male = "male", female = "female" )
value |
vector of measurement values |
pubstatus |
vector of Tanner stages coded 1 to 5 |
sex |
vector of sex |
item |
name of the item e.g. "height" |
ref |
RefGroup object |
type |
"SDS" or "perc" |
male |
coding of sex for male |
female |
coding of sex for female |
The function takes a vector of measurement values, and of tanner stage and of sex and a RefGroup object as arguments. It calculates the sds or percentile values.
vector containing SDS or percentile values
Mandy Vogel
Calculate SDS values depending on the Tanner stage and a second variable
sds_pub2d( value, pubstat, x2, sex, item, ref, type = "SDS", male = "male", female = "female", age = NULL, id = 1:length(value) )sds_pub2d( value, pubstat, x2, sex, item, ref, type = "SDS", male = "male", female = "female", age = NULL, id = 1:length(value) )
value |
vector of measurement values |
pubstat |
vector of Tanner stages coded 1 to 5 |
x2 |
2nd predictor (vector), e.g. bmisds must be contained in reference |
sex |
vector of sex |
item |
name of the item e.g. "height" |
ref |
RefGroup object |
type |
"SDS" or "perc" |
male |
coding of sex for male |
female |
coding of sex for female |
age |
not used yet |
id |
order of values |
The function takes a vector of measurement values, and of tanner stage of a second variable (x2) and of sex and a RefGroup object as arguments. It calculates the sds or percentile values.
vector containing SDS or percentile values
Mandy Vogel
Calculate SDS values for 2-dimensional matrix of covariates
sds2d( value, age, x2, sex, item, ref, type = "SDS", male = "male", female = "female" )sds2d( value, age, x2, sex, item, ref, type = "SDS", male = "male", female = "female" )
value |
vector of measurement values |
age |
vector of age values |
x2 |
second vector of covariates |
sex |
vector of sex |
item |
name of the item e.g. "height" |
ref |
RefGroup object |
type |
"SDS" or "perc" |
male |
coding of sex for male |
female |
coding of sex for male |
The function takes a vector of measurement values, and of age and a second covariate (like age and height for blood pressure) of sex and a RefGroup object as arguments. It calculates the sds or percentile values. This function is beta.
the function searches for the nearest given point in the reference grid.
From there, the SDS/percentile value will be calculated. Different from sds,
no interpolation will be applied. The procedure is according to Neuhauser et al. Blood
Pressure Percentiles by Age and Height from Nonoverweight Children and Adolescents
in Germany. 2011.
vector containing SDS or percentile values
Mandy Vogel
Calculate SDS values - old version for comparison
sdsold( value, age, sex, item, ref, type = "SDS", male = "male", female = "female" )sdsold( value, age, sex, item, ref, type = "SDS", male = "male", female = "female" )
value |
vector of measurement values |
age |
vector of age values |
sex |
vector of sex |
item |
name of the item e.g. "height" |
ref |
RefGroup object |
type |
"SDS" or "perc" |
male |
coding of sex for male |
female |
coding of sex for female |
The function takes a vector of measurement values, and of age and of sex and a RefGroup object as arguments. It calculates the sds or percentile values.
vector containing SDS or percentile values
Mandy Vogel
anthro <- data.frame(age = c(11.61,12.49,9.5,10.42,8.42,10.75,9.57,10.48), height = c(148.2,154.4,141.6,145.3,146,140.9,145.5,150), sex = sample(c("male","female"), size = 8, replace = TRUE), weight = c(69.5,72.65,47.3,51.6,45.6,48.9,53.5,58.5)) anthro$height_sds <- sds(anthro$height, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "height", type = "SDS") anthro$bmi <- anthro$weight/(anthro$height**2) * 10000 anthro$bmi_perc <- sds(anthro$bmi, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "bmi", type = "perc") data(who.ref) x <- data.frame(height=c(50,100,60,54), sex=c("m","f","f","m"), age=c(0,2.9,0.6,0.2)) sds(value = x$height, age = x$age, sex = x$sex, male = "m", female = "f", ref = who.ref, item = "height")anthro <- data.frame(age = c(11.61,12.49,9.5,10.42,8.42,10.75,9.57,10.48), height = c(148.2,154.4,141.6,145.3,146,140.9,145.5,150), sex = sample(c("male","female"), size = 8, replace = TRUE), weight = c(69.5,72.65,47.3,51.6,45.6,48.9,53.5,58.5)) anthro$height_sds <- sds(anthro$height, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "height", type = "SDS") anthro$bmi <- anthro$weight/(anthro$height**2) * 10000 anthro$bmi_perc <- sds(anthro$bmi, age = anthro$age, sex = anthro$sex, male = "male", female = "female", ref = kro.ref, item = "bmi", type = "perc") data(who.ref) x <- data.frame(height=c(50,100,60,54), sex=c("m","f","f","m"), age=c(0,2.9,0.6,0.2)) sds(value = x$height, age = x$age, sex = x$sex, male = "m", female = "f", ref = who.ref, item = "height")
Select groups (families)
select_fams(data, prop = 0.75, group, verbose = F)select_fams(data, prop = 0.75, group, verbose = F)
data |
dataframe as returned by prepare data |
prop |
proportion of families to be sampled |
group |
name of the group variable (character) if not "group", ignored |
verbose |
if TRUE information about sample size is printed out |
function selects a given proportion of groups/families from the data
if no grouping variable is given the original data set is returned
function is called inside do_iterations and may not called directly
dataframe containing only prop.fam percent the families in data
Mandy Vogel
Choose one measurement per subject
select_meas(data, subject = "subject", prop = 1, verbose = F)select_meas(data, subject = "subject", prop = 1, verbose = F)
data |
dataframe as returned by prepare data |
subject |
name of the column containing the subject identifier |
prop |
optional - proportion of measurements to sample |
verbose |
if TRUE information about sample size is printed out |
function samples one measurement per subject, if prop < 1 additional
a prop*100 percent will be sampled from the measurements
the function is called inside do_iterations and may not called directly
dataframe containing the sampled rows
Mandy Vogel
show method for ParTab
## S4 method for signature 'ParTab' show(object)## S4 method for signature 'ParTab' show(object)
object |
object of calss ParTab |
show method for ParTab
print information about the respective reference table
Mandy Vogel
show method for RefGroup
## S4 method for signature 'RefGroup' show(object)## S4 method for signature 'RefGroup' show(object)
object |
object of class RefGroup |
show method for RefGroup
prints information about age range, citations, etc.
Mandy Vogel
Parameters derived from Turkish children
turkish.refturkish.ref
Hatipoglu, N. et al. Waist circumference percentiles for 7- to 17-year-old Turkish children and adolescents. Eur J Pediatr 167, 383–389 (2008);Bundak, R. et al. Body mass index references for Turkish children. Acta Paediatrica 95, 194–198 (2006).
Neyzi, O., Furman, A., Bundak, R., Gunoz, H., Darendeliler, F., Bas, F., 2006. Growth references for Turkish children aged 6 to 18 years. Acta Paediatrica 95, 1635-1641. doi:10.1080/08035250600652013
Bundak, R. et al. Body mass index references for Turkish children. Acta Paediatrica 95, 194-198 (2006).
UCHU colour scales
uchu.paluchu.pal
https://github.com/NeverCease/uchu
Parameters from the 1990 UK growth study
uk1990.refuk1990.ref
Cole, T.J., Freeman, J.V., Preece, M.A., 1998. British 1990 growth reference centiles for weight, height, body mass index and head circumference fitted by maximum penalized likelihood. Statistics in medicine 17, 407-429.
Cole, T.J., Freeman, J.V., Preece, M.A., 1995. Body mass index reference curves for the UK, 1990. Archives of disease in childhood 73, 25-29.
LMS Parameters for UK-WHO growth charts for height, weight, bmi, head circumference
ukwho.refukwho.ref
Wright, Charlotte M., et a,Practice pointer: Using the new UK-WHO growth charts. British Medical Journal 340.c1140 (2010): 647-650.Preterm British 1990, 0-4 WHO2006, 4-18 British1990
Parameters derived from US children (additional to the cdc.ref)
us.refus.ref
Sharma, A. K., Metzger, D. L., Daymont, C., Hadjiyannakis, S. & Rodd, C. J. LMS tables for waist-circumference and waist-height ratio Z-scores in children aged 5-19 y in NHANES III: association with cardio-metabolic risks. Pediatric research (2015)
Parameters for neck circumference from Valencia-Sosa, 2021
valencia_nc.refvalencia_nc.ref
Valencia-Sosa E, Chavez-Palencia C, Vallarta-Robledo JR, et al. Percentile Reference Values for the Neck Circumference of Mexican Children. Children 2021;8(5):407.
LMS Parameters for WHO growth charts for height, weight, bmi, head circumference,arm mid upper arm circumference, subscapular and triceps skinfold, weight for height
who.refwho.ref
de Onis, M., Onyango, A., Borghi, E., Siyam, A., Blossner, M., & Lutter, C. (2012). Worldwide implementation of the WHO child growth standards. Public Health Nutr, 12, 1-8.
Parameters of bmi, height, and weight; WHO 2007
who2007.refwho2007.ref
Onis, M. de, Onyango, A.W., Borghi, E., Siyam, A., Nishida, C., Siekmann, J., 2007. Development of a WHO growth reference for school-aged children and adolescents. Bulletin of the World health Organization 85, 660-667.
Worm plot ggplot version
wormplot_gg( m = NULL, residuals = NULL, age = NA, n.inter = 1, y.limits = c(-1, 1) )wormplot_gg( m = NULL, residuals = NULL, age = NA, n.inter = 1, y.limits = c(-1, 1) )
m |
a gamlss model |
residuals |
nlormalized quantile residuals |
age |
numeric vector of ages |
n.inter |
number of age intervals or cut points |
y.limits |
limits of the y-axis |
creates a wormplot for a gamlss model or a given vector of normalized quantile residuals, either for all residuals or grouped by age intervals
ggplot object
Worm plot ggplot version, 2 covariates
wormplot2d_gg( m = NULL, residuals = NULL, age = NA, x2 = NA, name.x2, n.inter.age = 1, n.inter.x2 = 1, y.limits = c(-1, 1) )wormplot2d_gg( m = NULL, residuals = NULL, age = NA, x2 = NA, name.x2, n.inter.age = 1, n.inter.x2 = 1, y.limits = c(-1, 1) )
m |
a gamlss model |
residuals |
nlormalized quantile residuals |
age |
numeric vector of ages |
x2 |
numeric vector of second covariate |
name.x2 |
name of x2 for use in graphics |
n.inter.age |
number of age intervals or cut points |
n.inter.x2 |
number of x2 intervals or cut points |
y.limits |
limits of the y-axis |
creates a wormplot for a gamlss model or a given vector of normalized quantile residuals, either for all residuals or grouped by age intervals
ggplot object
Parameters derived from Chinese children (additional to nl4.ref)
zong13.refzong13.ref
Zong, X.-N., Li, H. Construction of a New Growth References for China Based on Urban Chinese Children: Comparison with the WHO Growth Standards. PLOS ONE 8, e59569 (2013).