Last data update: 2014.03.03

 R: Converts measurements to standard deviation scores (SDS)
y2zR Documentation

Converts measurements to standard deviation scores (SDS)

Description

Converts measurements into age- and sex-conditional standard deviation score (SDS) using an external reference.

Usage

y2z(y = c(75, 80, 85), x = 1, sex = "M", sub = "N",
  ref = get("nl4.hgt"), dist = "LMS", dec = 3, sex.fallback = "M",
  sub.fallback = "N", tail.adjust = FALSE)

Arguments

y

A numerical vector containing the outcome measurements. The length length(y) determines the size of the output vector.

x

A vector containing the values of the numerical covariate (typically decimal age or height) at which conversion is desired. Values are replicated to match length(y).

sex

A character vector indicating whether the male ("M") of female ("F")reference should be used. Values are replicated to match length(y).

sub

A character vector indicating the level of the sub field of the reference standard defined in ref

ref

A data frame containing a factor sex, a numerical variable age containing the tabulated decimal point ages, and two or more numerical variables with reference values. See details.

dist

A string identifying the type of distribution. Values values are: "NO", "BCCG", "LMS", "BCPE" and "BCT". The default is "LMS".

dec

A scalar value indicating the number of decimals used to round the value.

sex.fallback

The level of the sex field used when no match is found. The default is "M" for males. Specify sex.fallback="NA" if unmatched entries should receive a NA value.

sub.fallback

The level of the sub field used when no match is found. The default is "N" for normal. Specify sub.fallback="NA" if unmatched entries should receive a NA value.

tail.adjust

Logical. If TRUE then the WHO method for tail adjustment is applied. The default is FALSE.

Details

Functions z2y() and y2z() are the inverse of each other.

The argument dist determines the statistical distribution. The possibilities are as follows:

list(""NO"")

ref should contain columns mean and sd, containing the mean and the standard deviation in the external reference population.

list(""LMS"")

ref should contain columns L, S and M containing the LMS parameters.

list(""BCCG"")

ref should contain columns mu, sigma and nu containing the Box-Cox Cole-Green parameters.

list(""BCPE"")

ref should contain columns mu, sigma, nu and tau containing the Box-Cox Power Exponential parameters.

list(""BCT"")

ref should contain columns mu, sigma, nu and tau containing the Box-Cox T distribution parameters.

Value

For y2z(): A vector with length(y) elements containing the standard deviation score. For z2y(): A vector with length(z) elements containing quantiles.

Author(s)

Stef van Buuren, 2010

See Also

z2y

Examples

boys <- boys7482

# SDS of height 115 cm at age 5 years,
# relative to Dutch boys reference
y2z(y=115, x=5)

# same relative to Dutch girls
y2z(y=115, x=5, sex="F")

# SDS of IOTF BMI cut-off value for overweight (boys 2-18)
# relative to Dutch boys reference
cutoff <- c(
18.41, 18.15, 17.89, 17.72, 17.55, 17.49, 17.42, 17.49, 17.55, 17.74,
17.92, 18.18, 18.44, 18.77, 19.10, 19.47, 19.84, 20.20, 20.55, 20.89,
21.22, 21.57, 21.91, 22.27, 22.62, 22.96, 23.29, 23.60, 23.90, 24.18,
24.46, 24.73, 25.00)
age <- seq(2, 18, by=0.5)
(z <- y2z(y=cutoff, x=age, sex="M", ref=nl4.bmi))

# apply inverse transformation to check calculations
round(z2y(z, age, ref=nl4.bmi), 2)
cutoff

# calculate percentiles of weight 12 kg at 2 years (boys, girls)
100*round(pnorm(y2z(y=c(12,12), x=2, sex=c("M","F"), ref=nl4.wgt)),2)

# # percentage of children lighter than 15kg at ages 2-5
e <- expand.grid(age=2:5, sex=c("M","F"))
z <- y2z(y=rep(15,nrow(e)), x=e$age, sex=e$sex, ref=nl4.wgt)
w <- matrix(100*round(pnorm(z),2), nrow=2, byrow=TRUE)
dimnames(w) <- list(c("boys","girls"),2:5)
w

# analysis in Z scale
hgt.z <- y2z(y=boys$hgt, x=boys$age, sex="M", ref=nl4.hgt)
wgt.z <- y2z(y=boys$wgt, x=boys$age, sex="M", ref=nl4.wgt)
plot(hgt.z, wgt.z, col="blue")


# z2y

# quantile at SD=0 of age 2 years,
# height Dutch boys
z2y(z=0, x=2)

# same for Dutch girls
z2y(z=0, x=2, sex="F")

# quantile at SD=c(-1,0,1) of age 2 years, BMI Dutch boys
z2y(z=c(-1,0,+1), x=2, ref=nl4.bmi)

# 0SD line (P50) in kg of weight for age in 5-10 year, Dutch boys
z2y(z=rep(0,6), x=5:10, ref=nl4.wgt)

# 95th percentile (P95), age 10 years, wfa, Dutch boys
z2y(z=qnorm(0.95), x=10, ref=nl4.wgt)

# table of P3, P10, P50, P90, P97 of weight for 5-10 year old dutch boys
# age per year
age <- 5:10
p <- c(0.03,0.1,0.5,0.9,0.97)
z <- rep(qnorm(p), length(age))
x <- rep(age, each=length(p))
w <- matrix(z2y(z, x=x, sex="M", ref=nl4.wgt), ncol=length(p),
 byrow=TRUE)
dimnames(w) <- list(age, p)
round(w,1)

# standard set of Z-scores of weight for all tabulated ages, boys & girls
# and three etnicities
sds <- c(-2.5, -2, -1, 0, 1, 2, 2.5)
age <- nl4.wgt$x
z <- rep(sds, times=length(age))
x <- rep(age, each=length(sds))
sex <- rep(c("M","F"), each=length(z)/2)
w <- z2y(z=z, x=x, sex=sex, ref=nl4.wgt)
w <- matrix(w, ncol=length(sds), byrow=TRUE)
dimnames(w) <- list(age, sds)
data.frame(sub=nl4.wgt$sub,sex=nl4.wgt$sex,round(w,2), row.names=NULL)

# P85 of BMI in 5-8 year old Dutch boys and girls
e <- expand.grid(age=5:8, sex=c("M","F"))
w <- z2y(z=rep(qnorm(0.85),nrow(e)), x=e$age, sex=e$sex, ref=nl4.bmi)
w <- matrix(w, nrow=2, byrow=TRUE)
dimnames(w) <- list(c("boys","girls"),5:8)
w

# data transformation of height z-scores to cm-scale
z <- c(-1.83, 0.09, 2.33, 0.81, -1.20)
x <- c(8.33,  0.23, 19.2, 24.3, 10)
sex <- c("M", "M", "F", "M", "F")
round(z2y(z=z, x=x, sex=sex, ref=nl4.hgt), 1)

# interpolate published height standard
# to daily values, days 0-31, boys
# on centiles -2SD, 0SD and +2SD
days <- 0:31
sds  <- c(-2, 0, +2)
z    <- rep(sds, length(days))
x    <- rep(round(days/365.25,4), each=length(sds))
w    <- z2y(z, x, sex="M", ref=nl4.hgt)
w    <- matrix(w, ncol=length(sds), byrow=TRUE)
dimnames(w) <- list(days, sds)
w

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(AGD)
AGD 0.35 2015-05-27
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AGD/y2z.Rd_%03d_medium.png", width=480, height=480)
> ### Name: y2z
> ### Title: Converts measurements to standard deviation scores (SDS)
> ### Aliases: y2z
> ### Keywords: distribution
> 
> ### ** Examples
> 
> boys <- boys7482
> 
> # SDS of height 115 cm at age 5 years,
> # relative to Dutch boys reference
> y2z(y=115, x=5)
[1] 0.424
> 
> # same relative to Dutch girls
> y2z(y=115, x=5, sex="F")
[1] 0.706
> 
> # SDS of IOTF BMI cut-off value for overweight (boys 2-18)
> # relative to Dutch boys reference
> cutoff <- c(
+ 18.41, 18.15, 17.89, 17.72, 17.55, 17.49, 17.42, 17.49, 17.55, 17.74,
+ 17.92, 18.18, 18.44, 18.77, 19.10, 19.47, 19.84, 20.20, 20.55, 20.89,
+ 21.22, 21.57, 21.91, 22.27, 22.62, 22.96, 23.29, 23.60, 23.90, 24.18,
+ 24.46, 24.73, 25.00)
> age <- seq(2, 18, by=0.5)
> (z <- y2z(y=cutoff, x=age, sex="M", ref=nl4.bmi))
 [1] 1.448 1.459 1.411 1.371 1.299 1.255 1.189 1.190 1.173 1.209 1.223 1.255
[13] 1.273 1.308 1.342 1.381 1.416 1.446 1.459 1.470 1.470 1.471 1.464 1.462
[25] 1.452 1.442 1.426 1.412 1.395 1.382 1.375 1.368 1.372
> 
> # apply inverse transformation to check calculations
> round(z2y(z, age, ref=nl4.bmi), 2)
 [1] 18.41 18.15 17.89 17.72 17.55 17.49 17.42 17.49 17.55 17.74 17.92 18.18
[13] 18.44 18.77 19.10 19.47 19.84 20.20 20.55 20.89 21.22 21.57 21.91 22.27
[25] 22.62 22.96 23.29 23.60 23.90 24.18 24.46 24.73 25.00
> cutoff
 [1] 18.41 18.15 17.89 17.72 17.55 17.49 17.42 17.49 17.55 17.74 17.92 18.18
[13] 18.44 18.77 19.10 19.47 19.84 20.20 20.55 20.89 21.22 21.57 21.91 22.27
[25] 22.62 22.96 23.29 23.60 23.90 24.18 24.46 24.73 25.00
> 
> # calculate percentiles of weight 12 kg at 2 years (boys, girls)
> 100*round(pnorm(y2z(y=c(12,12), x=2, sex=c("M","F"), ref=nl4.wgt)),2)
[1] 24 41
> 
> # # percentage of children lighter than 15kg at ages 2-5
> e <- expand.grid(age=2:5, sex=c("M","F"))
> z <- y2z(y=rep(15,nrow(e)), x=e$age, sex=e$sex, ref=nl4.wgt)
> w <- matrix(100*round(pnorm(z),2), nrow=2, byrow=TRUE)
> dimnames(w) <- list(c("boys","girls"),2:5)
> w
       2  3  4 5
boys  89 46 11 1
girls 96 57 16 2
> 
> # analysis in Z scale
> hgt.z <- y2z(y=boys$hgt, x=boys$age, sex="M", ref=nl4.hgt)
> wgt.z <- y2z(y=boys$wgt, x=boys$age, sex="M", ref=nl4.wgt)
> plot(hgt.z, wgt.z, col="blue")
> 
> 
> # z2y
> 
> # quantile at SD=0 of age 2 years,
> # height Dutch boys
> z2y(z=0, x=2)
[1] 88.85
> 
> # same for Dutch girls
> z2y(z=0, x=2, sex="F")
[1] 87.49
> 
> # quantile at SD=c(-1,0,1) of age 2 years, BMI Dutch boys
> z2y(z=c(-1,0,+1), x=2, ref=nl4.bmi)
[1] 15.173 16.420 17.770
> 
> # 0SD line (P50) in kg of weight for age in 5-10 year, Dutch boys
> z2y(z=rep(0,6), x=5:10, ref=nl4.wgt)
[1] 19.82 22.37 25.03 27.86 30.76 33.79
> 
> # 95th percentile (P95), age 10 years, wfa, Dutch boys
> z2y(z=qnorm(0.95), x=10, ref=nl4.wgt)
[1] 45.278
> 
> # table of P3, P10, P50, P90, P97 of weight for 5-10 year old dutch boys
> # age per year
> age <- 5:10
> p <- c(0.03,0.1,0.5,0.9,0.97)
> z <- rep(qnorm(p), length(age))
> x <- rep(age, each=length(p))
> w <- matrix(z2y(z, x=x, sex="M", ref=nl4.wgt), ncol=length(p),
+  byrow=TRUE)
> dimnames(w) <- list(age, p)
> round(w,1)
   0.03  0.1  0.5  0.9 0.97
5  15.8 16.9 19.8 23.4 25.4
6  17.6 19.0 22.4 26.8 29.3
7  19.5 21.1 25.0 30.3 33.4
8  21.6 23.3 27.9 34.1 37.8
9  23.6 25.5 30.8 38.1 42.5
10 25.6 27.8 33.8 42.2 47.5
> 
> # standard set of Z-scores of weight for all tabulated ages, boys & girls
> # and three etnicities
> sds <- c(-2.5, -2, -1, 0, 1, 2, 2.5)
> age <- nl4.wgt$x
> z <- rep(sds, times=length(age))
> x <- rep(age, each=length(sds))
> sex <- rep(c("M","F"), each=length(z)/2)
> w <- z2y(z=z, x=x, sex=sex, ref=nl4.wgt)
> w <- matrix(w, ncol=length(sds), byrow=TRUE)
> dimnames(w) <- list(age, sds)
> data.frame(sub=nl4.wgt$sub,sex=nl4.wgt$sex,round(w,2), row.names=NULL)
    sub sex X.2.5   X.2   X.1    X0    X1    X2   X2.5
1     N   M  2.58  2.77  3.15  3.55  3.97  4.40   4.62
2     N   M  2.73  2.93  3.33  3.75  4.19  4.65   4.89
3     N   M  2.87  3.08  3.50  3.94  4.40  4.89   5.14
4     N   M  3.01  3.23  3.67  4.13  4.62  5.12   5.39
5     N   M  3.16  3.38  3.84  4.33  4.84  5.37   5.65
6     N   M  3.31  3.54  4.02  4.53  5.06  5.62   5.91
7     N   M  3.46  3.70  4.20  4.72  5.27  5.85   6.15
8     N   M  3.61  3.86  4.37  4.92  5.50  6.10   6.41
9     N   M  3.75  4.01  4.54  5.11  5.71  6.34   6.66
10    N   M  3.89  4.16  4.71  5.30  5.92  6.57   6.91
11    N   M  4.03  4.30  4.87  5.48  6.12  6.80   7.15
12    N   M  4.30  4.59  5.19  5.84  6.53  7.25   7.63
13    N   M  4.56  4.86  5.51  6.19  6.92  7.69   8.09
14    N   M  4.81  5.13  5.80  6.51  7.27  8.07   8.49
15    N   M  5.05  5.38  6.07  6.82  7.62  8.46   8.90
16    N   M  5.27  5.61  6.33  7.11  7.94  8.83   9.29
17    N   M  5.48  5.83  6.58  7.39  8.25  9.18   9.66
18    N   M  5.68  6.04  6.82  7.65  8.54  9.50  10.01
19    N   M  5.86  6.23  7.03  7.89  8.81  9.80  10.33
20    N   M  6.03  6.42  7.24  8.12  9.07 10.10  10.63
21    N   M  6.38  6.78  7.63  8.55  9.54 10.62  11.18
22    N   M  6.68  7.10  7.99  8.95  9.99 11.12  11.72
23    N   M  6.95  7.38  8.30  9.30 10.39 11.56  12.19
24    N   M  7.21  7.65  8.60  9.63 10.76 11.98  12.63
25    N   M  7.45  7.90  8.88  9.94 11.10 12.37  13.04
26    N   M  7.67  8.14  9.13 10.23 11.43 12.74  13.44
27    N   M  7.86  8.34  9.37 10.50 11.74 13.11  13.83
28    N   M  8.05  8.54  9.59 10.75 12.02 13.42  14.17
29    N   M  8.24  8.74  9.82 11.00 12.30 13.74  14.51
30    N   M  8.85  9.38 10.52 11.78 13.18 14.73  15.57
31    N   M  9.79 10.36 11.62 13.02 14.59 16.35  17.30
32    N   M 10.59 11.21 12.58 14.12 15.86 17.83  18.91
33    N   M 11.39 12.06 13.52 15.19 17.09 19.26  20.45
34    N   M 12.18 12.89 14.47 16.28 18.36 20.76  22.10
35    N   M 12.98 13.74 15.45 17.42 19.72 22.40  23.91
36    N   M 13.83 14.64 16.47 18.60 21.11 24.07  25.75
37    N   M 14.67 15.54 17.50 19.82 22.57 25.87  27.77
38    N   M 15.54 16.47 18.57 21.08 24.09 27.76  29.89
39    N   M 16.39 17.38 19.64 22.37 25.69 29.79  32.21
40    N   M 17.28 18.33 20.74 23.68 27.30 31.82  34.52
41    N   M 18.14 19.26 21.85 25.03 28.99 34.02  37.07
42    N   M 19.08 20.26 23.02 26.43 30.73 36.25  39.64
43    N   M 19.97 21.23 24.18 27.86 32.54 38.65  42.44
44    N   M 20.86 22.20 25.35 29.30 34.38 41.11  45.32
45    N   M 21.78 23.20 26.54 30.76 36.22 43.51  48.12
46    N   M 22.66 24.16 27.73 32.25 38.15 46.09  51.15
47    N   M 23.59 25.18 28.97 33.79 40.10 48.62  54.07
48    N   M 24.55 26.25 30.28 35.43 42.17 51.29  57.12
49    N   M 25.53 27.36 31.69 37.23 44.48 54.28  60.53
50    N   M 26.65 28.62 33.29 39.24 47.00 57.39  63.97
51    N   M 27.85 29.99 35.06 41.48 49.79 60.77  67.64
52    N   M 29.23 31.56 37.07 43.99 52.84 64.35  71.44
53    N   M 30.74 33.29 39.29 46.77 56.22 68.31  75.64
54    N   M 32.59 35.35 41.80 49.77 59.69 72.17  79.61
55    N   M 34.62 37.58 44.46 52.87 63.22 76.06  83.62
56    N   M 36.88 40.00 47.20 55.94 66.59 79.64  87.25
57    N   M 39.20 42.43 49.87 58.82 69.65 82.80  90.42
58    N   M 41.54 44.84 52.41 61.45 72.32 85.43  92.98
59    N   M 43.65 47.01 54.66 63.77 74.67 87.77  95.30
60    N   M 45.58 48.96 56.64 65.75 76.61 89.61  97.06
61    N   M 47.22 50.62 58.32 67.43 78.26 91.18  98.58
62    N   M 48.71 52.11 59.79 68.85 79.59 92.38  99.68
63    N   M 49.95 53.35 61.02 70.06 80.75 93.45 100.70
64    N   M 51.07 54.47 62.12 71.10 81.70 94.27 101.43
65    N   M 52.01 55.41 63.06 72.04 82.62 95.15 102.28
66    N   M 52.90 56.30 63.94 72.89 83.43 95.89 102.98
67    N   M 53.88 57.26 64.84 73.70 84.10 96.37 103.33
68    N   M 54.73 58.10 65.67 74.49 84.83 97.02 103.92
69    N   M 55.58 58.95 66.50 75.28 85.56 97.65 104.50
70    N   M 55.58 58.95 66.50 75.28 85.56 97.65 104.50
71    N   F  2.58  2.77  3.15  3.55  3.97  4.40   4.62
72    N   F  2.73  2.93  3.33  3.75  4.19  4.65   4.89
73    N   F  2.87  3.08  3.50  3.94  4.40  4.89   5.14
74    N   F  3.01  3.23  3.67  4.13  4.62  5.12   5.39
75    N   F  3.16  3.38  3.84  4.33  4.84  5.37   5.65
76    N   F  3.31  3.54  4.02  4.53  5.06  5.62   5.91
77    N   F  3.46  3.70  4.20  4.72  5.27  5.85   6.15
78    N   F  3.61  3.86  4.37  4.92  5.50  6.10   6.41
79    N   F  3.75  4.01  4.54  5.11  5.71  6.34   6.66
80    N   F  3.89  4.16  4.71  5.30  5.92  6.57   6.91
81    N   F  4.03  4.30  4.87  5.48  6.12  6.80   7.15
82    N   F  4.30  4.59  5.19  5.84  6.53  7.25   7.63
83    N   F  4.56  4.86  5.51  6.19  6.92  7.69   8.09
84    N   F  4.81  5.13  5.80  6.51  7.27  8.07   8.49
85    N   F  5.05  5.38  6.07  6.82  7.62  8.46   8.90
86    N   F  5.27  5.61  6.33  7.11  7.94  8.83   9.29
87    N   F  5.48  5.83  6.58  7.39  8.25  9.18   9.66
88    N   F  5.68  6.04  6.82  7.65  8.54  9.50  10.01
89    N   F  5.86  6.23  7.03  7.89  8.81  9.80  10.33
90    N   F  6.03  6.42  7.24  8.12  9.07 10.10  10.63
91    N   F  6.38  6.78  7.63  8.55  9.54 10.62  11.18
92    N   F  6.68  7.10  7.99  8.95  9.99 11.12  11.72
93    N   F  6.95  7.38  8.30  9.30 10.39 11.56  12.19
94    N   F  7.21  7.65  8.60  9.63 10.76 11.98  12.63
95    N   F  7.45  7.90  8.88  9.94 11.10 12.37  13.04
96    N   F  7.67  8.14  9.13 10.23 11.43 12.74  13.44
97    N   F  7.86  8.34  9.37 10.50 11.74 13.11  13.83
98    N   F  8.05  8.54  9.59 10.75 12.02 13.42  14.17
99    N   F  8.24  8.74  9.82 11.00 12.30 13.74  14.51
100   N   F  8.85  9.38 10.52 11.78 13.18 14.73  15.57
101   N   F  9.79 10.36 11.62 13.02 14.59 16.35  17.30
102   N   F 10.59 11.21 12.58 14.12 15.86 17.83  18.91
103   N   F 11.39 12.06 13.52 15.19 17.09 19.26  20.45
104   N   F 12.18 12.89 14.47 16.28 18.36 20.76  22.10
105   N   F 12.98 13.74 15.45 17.42 19.72 22.40  23.91
106   N   F 13.83 14.64 16.47 18.60 21.11 24.07  25.75
107   N   F 14.67 15.54 17.50 19.82 22.57 25.87  27.77
108   N   F 15.54 16.47 18.57 21.08 24.09 27.76  29.89
109   N   F 16.39 17.38 19.64 22.37 25.69 29.79  32.21
110   N   F 17.28 18.33 20.74 23.68 27.30 31.82  34.52
111   N   F 18.14 19.26 21.85 25.03 28.99 34.02  37.07
112   N   F 19.08 20.26 23.02 26.43 30.73 36.25  39.64
113   N   F 19.97 21.23 24.18 27.86 32.54 38.65  42.44
114   N   F 20.86 22.20 25.35 29.30 34.38 41.11  45.32
115   N   F 21.78 23.20 26.54 30.76 36.22 43.51  48.12
116   N   F 22.66 24.16 27.73 32.25 38.15 46.09  51.15
117   N   F 23.59 25.18 28.97 33.79 40.10 48.62  54.07
118   N   F 24.55 26.25 30.28 35.43 42.17 51.29  57.12
119   N   F 25.53 27.36 31.69 37.23 44.48 54.28  60.53
120   N   F 26.65 28.62 33.29 39.24 47.00 57.39  63.97
121   N   F 27.85 29.99 35.06 41.48 49.79 60.77  67.64
122   N   F 29.23 31.56 37.07 43.99 52.84 64.35  71.44
123   N   F 30.74 33.29 39.29 46.77 56.22 68.31  75.64
124   N   F 32.59 35.35 41.80 49.77 59.69 72.17  79.61
125   N   F 34.62 37.58 44.46 52.87 63.22 76.06  83.62
126   N   F 36.88 40.00 47.20 55.94 66.59 79.64  87.25
127   N   F 39.20 42.43 49.87 58.82 69.65 82.80  90.42
128   N   F 41.54 44.84 52.41 61.45 72.32 85.43  92.98
129   N   F 43.65 47.01 54.66 63.77 74.67 87.77  95.30
130   N   F 45.58 48.96 56.64 65.75 76.61 89.61  97.06
131   N   F 47.22 50.62 58.32 67.43 78.26 91.18  98.58
132   N   F 48.71 52.11 59.79 68.85 79.59 92.38  99.68
133   N   F 49.95 53.35 61.02 70.06 80.75 93.45 100.70
134   N   F 51.07 54.47 62.12 71.10 81.70 94.27 101.43
135   N   F 52.01 55.41 63.06 72.04 82.62 95.15 102.28
136   N   F 52.90 56.30 63.94 72.89 83.43 95.89 102.98
137   N   F 53.88 57.26 64.84 73.70 84.10 96.37 103.33
138   N   F 54.73 58.10 65.67 74.49 84.83 97.02 103.92
139   N   F 55.58 58.95 66.50 75.28 85.56 97.65 104.50
140   N   F 55.58 58.95 66.50 75.28 85.56 97.65 104.50
141   T   M  2.58  2.77  3.15  3.55  3.97  4.40   4.62
142   T   M  2.73  2.93  3.33  3.75  4.19  4.65   4.89
143   T   M  2.87  3.08  3.50  3.94  4.40  4.89   5.14
144   T   M  3.01  3.23  3.67  4.13  4.62  5.12   5.39
145   T   M  3.16  3.38  3.84  4.33  4.84  5.37   5.65
146   T   M  3.31  3.54  4.02  4.53  5.06  5.62   5.91
147   T   M  3.46  3.70  4.20  4.72  5.27  5.85   6.15
148   T   M  3.61  3.86  4.37  4.92  5.50  6.10   6.41
149   T   M  3.75  4.01  4.54  5.11  5.71  6.34   6.66
150   T   M  3.89  4.16  4.71  5.30  5.92  6.57   6.91
151   T   M  4.03  4.30  4.87  5.48  6.12  6.80   7.15
152   T   M  4.30  4.59  5.19  5.84  6.53  7.25   7.63
153   T   M  4.56  4.86  5.51  6.19  6.92  7.69   8.09
154   T   M  4.81  5.13  5.80  6.51  7.27  8.07   8.49
155   T   M  5.05  5.38  6.07  6.82  7.62  8.46   8.90
156   T   M  5.27  5.61  6.33  7.11  7.94  8.83   9.29
157   T   M  5.48  5.83  6.58  7.39  8.25  9.18   9.66
158   T   M  5.68  6.04  6.82  7.65  8.54  9.50  10.01
159   T   M  5.86  6.23  7.03  7.89  8.81  9.80  10.33
160   T   M  6.03  6.42  7.24  8.12  9.07 10.10  10.63
161   T   M  6.38  6.78  7.63  8.55  9.54 10.62  11.18
162   T   M  6.68  7.10  7.99  8.95  9.99 11.12  11.72
163   T   M  6.95  7.38  8.30  9.30 10.39 11.56  12.19
164   T   M  7.21  7.65  8.60  9.63 10.76 11.98  12.63
165   T   M  7.45  7.90  8.88  9.94 11.10 12.37  13.04
166   T   M  7.67  8.14  9.13 10.23 11.43 12.74  13.44
167   T   M  7.86  8.34  9.37 10.50 11.74 13.11  13.83
168   T   M  8.05  8.54  9.59 10.75 12.02 13.42  14.17
169   T   M  8.24  8.74  9.82 11.00 12.30 13.74  14.51
170   T   M  8.85  9.38 10.52 11.78 13.18 14.73  15.57
171   T   M  9.79 10.36 11.62 13.02 14.59 16.35  17.30
172   T   M 10.59 11.21 12.58 14.12 15.86 17.83  18.91
173   T   M 11.39 12.06 13.52 15.19 17.09 19.26  20.45
174   T   M 12.18 12.89 14.47 16.28 18.36 20.76  22.10
175   T   M 12.98 13.74 15.45 17.42 19.72 22.40  23.91
176   T   M 13.83 14.64 16.47 18.60 21.11 24.07  25.75
177   T   M 14.67 15.54 17.50 19.82 22.57 25.87  27.77
178   T   M 15.54 16.47 18.57 21.08 24.09 27.76  29.89
179   T   M 16.39 17.38 19.64 22.37 25.69 29.79  32.21
180   T   M 17.28 18.33 20.74 23.68 27.30 31.82  34.52
181   T   M 18.14 19.26 21.85 25.03 28.99 34.02  37.07
182   T   M 19.08 20.26 23.02 26.43 30.73 36.25  39.64
183   T   M 19.97 21.23 24.18 27.86 32.54 38.65  42.44
184   T   M 20.86 22.20 25.35 29.30 34.38 41.11  45.32
185   T   M 21.78 23.20 26.54 30.76 36.22 43.51  48.12
186   T   M 22.66 24.16 27.73 32.25 38.15 46.09  51.15
187   T   M 23.59 25.18 28.97 33.79 40.10 48.62  54.07
188   T   M 24.55 26.25 30.28 35.43 42.17 51.29  57.12
189   T   M 25.53 27.36 31.69 37.23 44.48 54.28  60.53
190   T   M 26.65 28.62 33.29 39.24 47.00 57.39  63.97
191   T   M 27.85 29.99 35.06 41.48 49.79 60.77  67.64
192   T   M 29.23 31.56 37.07 43.99 52.84 64.35  71.44
193   T   M 30.74 33.29 39.29 46.77 56.22 68.31  75.64
194   T   M 32.59 35.35 41.80 49.77 59.69 72.17  79.61
195   T   M 34.62 37.58 44.46 52.87 63.22 76.06  83.62
196   T   M 36.88 40.00 47.20 55.94 66.59 79.64  87.25
197   T   M 39.20 42.43 49.87 58.82 69.65 82.80  90.42
198   T   M 41.54 44.84 52.41 61.45 72.32 85.43  92.98
199   T   M 43.65 47.01 54.66 63.77 74.67 87.77  95.30
200   T   M 45.58 48.96 56.64 65.75 76.61 89.61  97.06
201   T   M 47.22 50.62 58.32 67.43 78.26 91.18  98.58
202   T   M 48.71 52.11 59.79 68.85 79.59 92.38  99.68
203   T   M 49.95 53.35 61.02 70.06 80.75 93.45 100.70
204   T   M 51.07 54.47 62.12 71.10 81.70 94.27 101.43
205   T   M 52.01 55.41 63.06 72.04 82.62 95.15 102.28
206   T   M 52.90 56.30 63.94 72.89 83.43 95.89 102.98
207   T   M 53.88 57.26 64.84 73.70 84.10 96.37 103.33
208   T   M 48.33 50.76 56.51 63.85 73.58 87.13  96.14
209   T   F  2.46  2.63  2.97  3.34  3.74  4.17   4.39
210   T   F  2.59  2.76  3.12  3.51  3.93  4.38   4.62
211   T   F  2.73  2.90  3.28  3.69  4.13  4.60   4.85
212   T   F  2.85  3.04  3.43  3.86  4.32  4.82   5.08
213   T   F  2.98  3.17  3.58  4.03  4.51  5.03   5.30
214   T   F  3.11  3.31  3.75  4.21  4.71  5.26   5.54
215   T   F  3.25  3.46  3.90  4.38  4.90  5.46   5.76
216   T   F  3.38  3.60  4.06  4.56  5.10  5.68   5.99
217   T   F  3.51  3.74  4.21  4.73  5.29  5.90   6.22
218   T   F  3.65  3.88  4.37  4.90  5.48  6.10   6.43
219   T   F  3.78  4.01  4.52  5.07  5.67  6.31   6.66
220   T   F  4.03  4.28  4.82  5.40  6.04  6.73   7.09
221   T   F  4.28  4.54  5.11  5.72  6.39  7.12   7.50
222   T   F  4.52  4.79  5.38  6.03  6.74  7.50   7.91
223   T   F  4.74  5.03  5.64  6.32  7.06  7.87   8.30
224   T   F  4.96  5.25  5.89  6.59  7.36  8.19   8.64
225   T   F  5.16  5.46  6.12  6.85  7.65  8.52   8.98
226   T   F  5.35  5.66  6.35  7.10  7.93  8.83   9.32
227   T   F  5.54  5.86  6.56  7.33  8.18  9.10   9.60
228   T   F  5.71  6.04  6.76  7.55  8.42  9.38   9.89
229   T   F  6.02  6.37  7.12  7.95  8.87  9.88  10.43
230   T   F  6.30  6.66  7.45  8.32  9.28 10.35  10.92
231   T   F  6.56  6.94  7.75  8.66  9.66 10.78  11.38
232   T   F  6.82  7.21  8.04  8.97 10.00 11.14  11.76
233   T   F  7.04  7.44  8.30  9.27 10.35 11.55  12.20
234   T   F  7.25  7.66  8.55  9.55 10.66 11.90  12.57
235   T   F  7.46  7.88  8.79  9.81 10.95 12.23  12.92
236   T   F  7.65  8.08  9.01 10.06 11.23 12.54  13.26
237   T   F  7.84  8.27  9.23 10.30 11.50 12.85  13.58
238   T   F  8.41  8.88  9.90 11.06 12.37 13.84  14.65
239   T   F  9.35  9.87 11.02 12.32 13.81 15.51  16.45
240   T   F 10.23 10.80 12.07 13.52 15.19 17.12  18.20
241   T   F 11.06 11.68 13.07 14.68 16.55 18.74  19.97
242   T   F 11.86 12.54 14.05 15.82 17.90 20.36  21.77
243   T   F 12.64 13.37 15.01 16.94 19.24 21.99  23.57
244   T   F 13.38 14.16 15.94 18.05 20.59 23.68  25.48
245   T   F 14.15 14.99 16.90 19.21 22.02 25.48  27.53
246   T   F 14.96 15.86 17.93 20.44 23.54 27.42  29.75
247   T   F 15.80 16.77 19.01 21.77 25.22 29.62  32.29
248   T   F 16.72 17.76 20.18 23.19 27.00 31.92  34.96
249   T   F 17.61 18.73 21.37 24.68 28.93 34.55  38.07
250   T   F 18.55 19.76 22.61 26.22 30.92 37.24  41.26
251   T   F 19.50 20.79 23.87 27.80 32.98 40.03  44.59
252   T   F 20.39 21.78 25.11 29.40 35.12 43.02  48.19
253   T   F 21.31 22.80 26.39 31.04 37.28 46.00  51.76
254   T   F 22.24 23.85 27.71 32.75 39.55 49.10  55.43
255   T   F 23.21 24.94 29.09 34.52 41.85 52.15  58.97
256   T   F 24.16 26.03 30.52 36.40 44.34 55.48  62.85
257   T   F 25.28 27.29 32.13 38.46 46.96 58.77  66.50
258   T   F 26.52 28.70 33.93 40.73 49.78 62.19  70.19
259   T   F 28.05 30.39 36.00 43.21 52.69 65.44  73.53
260   T   F 29.93 32.41 38.30 45.80 55.49 68.27  76.23
261   T   F 32.00 34.58 40.67 48.32 58.09 70.76  78.54
262   T   F 34.15 36.78 42.95 50.64 60.37 72.87  80.48
263   T   F 36.26 38.89 45.05 52.70 62.33 74.66  82.15
264   T   F 38.19 40.81 46.91 54.48 64.00 76.21  83.65
265   T   F 39.83 42.43 48.48 56.00 65.49 77.74  85.24
266   T   F 41.24 43.81 49.82 57.29 66.77 79.09  86.71
267   T   F 42.42 44.98 50.93 58.37 67.86 80.31  88.08
268   T   F 43.48 46.00 51.90 59.28 68.74 81.24  89.10
269   T   F 44.23 46.75 52.64 60.04 69.59 82.33  90.42
270   T   F 44.99 47.48 53.33 60.70 70.24 83.04  91.22
271   T   F 45.59 48.07 53.90 61.27 70.85 83.81  92.14
272   T   F 46.14 48.61 54.43 61.79 71.41 84.48  92.95
273   T   F 46.63 49.10 54.90 62.25 71.89 85.06  93.64
274   T   F 47.11 49.56 55.34 62.68 72.33 85.57  94.24
275   T   F 47.55 49.99 55.75 63.08 72.73 86.03  94.77
276   T   F 47.90 50.34 56.11 63.47 73.20 86.71  95.66
277   T   F 48.33 50.76 56.51 63.85 73.58 87.13  96.14
278   M   M  2.46  2.63  2.97  3.34  3.74  4.17   4.39
279   M   M  2.59  2.76  3.12  3.51  3.93  4.38   4.62
280   M   M  2.73  2.90  3.28  3.69  4.13  4.60   4.85
281   M   M  2.85  3.04  3.43  3.86  4.32  4.82   5.08
282   M   M  2.98  3.17  3.58  4.03  4.51  5.03   5.30
283   M   M  3.11  3.31  3.75  4.21  4.71  5.26   5.54
284   M   M  3.25  3.46  3.90  4.38  4.90  5.46   5.76
285   M   M  3.38  3.60  4.06  4.56  5.10  5.68   5.99
286   M   M  3.51  3.74  4.21  4.73  5.29  5.90   6.22
287   M   M  3.65  3.88  4.37  4.90  5.48  6.10   6.43
288   M   M  3.78  4.01  4.52  5.07  5.67  6.31   6.66
289   M   M  4.03  4.28  4.82  5.40  6.04  6.73   7.09
290   M   M  4.28  4.54  5.11  5.72  6.39  7.12   7.50
291   M   M  4.52  4.79  5.38  6.03  6.74  7.50   7.91
292   M   M  4.74  5.03  5.64  6.32  7.06  7.87   8.30
293   M   M  4.96  5.25  5.89  6.59  7.36  8.19   8.64
294   M   M  5.16  5.46  6.12  6.85  7.65  8.52   8.98
295   M   M  5.35  5.66  6.35  7.10  7.93  8.83   9.32
296   M   M  5.54  5.86  6.56  7.33  8.18  9.10   9.60
297   M   M  5.71  6.04  6.76  7.55  8.42  9.38   9.89
298   M   M  6.02  6.37  7.12  7.95  8.87  9.88  10.43
299   M   M  6.30  6.66  7.45  8.32  9.28 10.35  10.92
300   M   M  6.56  6.94  7.75  8.66  9.66 10.78  11.38
301   M   M  6.82  7.21  8.04  8.97 10.00 11.14  11.76
302   M   M  7.04  7.44  8.30  9.27 10.35 11.55  12.20
303   M   M  7.25  7.66  8.55  9.55 10.66 11.90  12.57
304   M   M  7.46  7.88  8.79  9.81 10.95 12.23  12.92
305   M   M  7.65  8.08  9.01 10.06 11.23 12.54  13.26
306   M   M  7.84  8.27  9.23 10.30 11.50 12.85  13.58
307   M   M  8.41  8.88  9.90 11.06 12.37 13.84  14.65
308   M   M  9.35  9.87 11.02 12.32 13.81 15.51  16.45
309   M   M 10.23 10.80 12.07 13.52 15.19 17.12  18.20
310   M   M 11.06 11.68 13.07 14.68 16.55 18.74  19.97
311   M   M 11.86 12.54 14.05 15.82 17.90 20.36  21.77
312   M   M 12.64 13.37 15.01 16.94 19.24 21.99  23.57
313   M   M 13.38 14.16 15.94 18.05 20.59 23.68  25.48
314   M   M 14.15 14.99 16.90 19.21 22.02 25.48  27.53
315   M   M 14.96 15.86 17.93 20.44 23.54 27.42  29.75
316   M   M 15.80 16.77 19.01 21.77 25.22 29.62  32.29
317   M   M 16.72 17.76 20.18 23.19 27.00 31.92  34.96
318   M   M 17.61 18.73 21.37 24.68 28.93 34.55  38.07
319   M   M 18.55 19.76 22.61 26.22 30.92 37.24  41.26
320   M   M 19.50 20.79 23.87 27.80 32.98 40.03  44.59
321   M   M 20.39 21.78 25.11 29.40 35.12 43.02  48.19
322   M   M 21.31 22.80 26.39 31.04 37.28 46.00  51.76
323   M   M 22.24 23.85 27.71 32.75 39.55 49.10  55.43
324   M   M 23.21 24.94 29.09 34.52 41.85 52.15  58.97
325   M   M 24.16 26.03 30.52 36.40 44.34 55.48  62.85
326   M   M 25.28 27.29 32.13 38.46 46.96 58.77  66.50
327   M   M 26.52 28.70 33.93 40.73 49.78 62.19  70.19
328   M   M 28.05 30.39 36.00 43.21 52.69 65.44  73.53
329   M   M 29.93 32.41 38.30 45.80 55.49 68.27  76.23
330   M   M 32.00 34.58 40.67 48.32 58.09 70.76  78.54
331   M   M 34.15 36.78 42.95 50.64 60.37 72.87  80.48
332   M   M 36.26 38.89 45.05 52.70 62.33 74.66  82.15
333   M   M 38.19 40.81 46.91 54.48 64.00 76.21  83.65
334   M   M 39.83 42.43 48.48 56.00 65.49 77.74  85.24
335   M   M 41.24 43.81 49.82 57.29 66.77 79.09  86.71
336   M   M 42.42 44.98 50.93 58.37 67.86 80.31  88.08
337   M   M 43.48 46.00 51.90 59.28 68.74 81.24  89.10
338   M   M 44.23 46.75 52.64 60.04 69.59 82.33  90.42
339   M   M 44.99 47.48 53.33 60.70 70.24 83.04  91.22
340   M   M 45.59 48.07 53.90 61.27 70.85 83.81  92.14
341   M   M 46.14 48.61 54.43 61.79 71.41 84.48  92.95
342   M   M 46.63 49.10 54.90 62.25 71.89 85.06  93.64
343   M   M 47.11 49.56 55.34 62.68 72.33 85.57  94.24
344   M   M 47.55 49.99 55.75 63.08 72.73 86.03  94.77
345   M   M 48.33 50.76 56.51 63.85 73.58 87.13  96.14
346   M   F  2.46  2.63  2.97  3.34  3.74  4.17   4.39
347   M   F  2.59  2.76  3.12  3.51  3.93  4.38   4.62
348   M   F  2.73  2.90  3.28  3.69  4.13  4.60   4.85
349   M   F  2.85  3.04  3.43  3.86  4.32  4.82   5.08
350   M   F  2.98  3.17  3.58  4.03  4.51  5.03   5.30
351   M   F  3.11  3.31  3.75  4.21  4.71  5.26   5.54
352   M   F  3.25  3.46  3.90  4.38  4.90  5.46   5.76
353   M   F  3.38  3.60  4.06  4.56  5.10  5.68   5.99
354   M   F  3.51  3.74  4.21  4.73  5.29  5.90   6.22
355   M   F  3.65  3.88  4.37  4.90  5.48  6.10   6.43
356   M   F  3.78  4.01  4.52  5.07  5.67  6.31   6.66
357   M   F  4.03  4.28  4.82  5.40  6.04  6.73   7.09
358   M   F  4.28  4.54  5.11  5.72  6.39  7.12   7.50
359   M   F  4.52  4.79  5.38  6.03  6.74  7.50   7.91
360   M   F  4.74  5.03  5.64  6.32  7.06  7.87   8.30
361   M   F  4.96  5.25  5.89  6.59  7.36  8.19   8.64
362   M   F  5.16  5.46  6.12  6.85  7.65  8.52   8.98
363   M   F  5.35  5.66  6.35  7.10  7.93  8.83   9.32
364   M   F  5.54  5.86  6.56  7.33  8.18  9.10   9.60
365   M   F  5.71  6.04  6.76  7.55  8.42  9.38   9.89
366   M   F  6.02  6.37  7.12  7.95  8.87  9.88  10.43
367   M   F  6.30  6.66  7.45  8.32  9.28 10.35  10.92
368   M   F  6.56  6.94  7.75  8.66  9.66 10.78  11.38
369   M   F  6.82  7.21  8.04  8.97 10.00 11.14  11.76
370   M   F  7.04  7.44  8.30  9.27 10.35 11.55  12.20
371   M   F  7.25  7.66  8.55  9.55 10.66 11.90  12.57
372   M   F  7.46  7.88  8.79  9.81 10.95 12.23  12.92
373   M   F  7.65  8.08  9.01 10.06 11.23 12.54  13.26
374   M   F  7.84  8.27  9.23 10.30 11.50 12.85  13.58
375   M   F  8.41  8.88  9.90 11.06 12.37 13.84  14.65
376   M   F  9.35  9.87 11.02 12.32 13.81 15.51  16.45
377   M   F 10.23 10.80 12.07 13.52 15.19 17.12  18.20
378   M   F 11.06 11.68 13.07 14.68 16.55 18.74  19.97
379   M   F 11.86 12.54 14.05 15.82 17.90 20.36  21.77
380   M   F 12.64 13.37 15.01 16.94 19.24 21.99  23.57
381   M   F 13.38 14.16 15.94 18.05 20.59 23.68  25.48
382   M   F 14.15 14.99 16.90 19.21 22.02 25.48  27.53
383   M   F 14.96 15.86 17.93 20.44 23.54 27.42  29.75
384   M   F 15.80 16.77 19.01 21.77 25.22 29.62  32.29
385   M   F 16.72 17.76 20.18 23.19 27.00 31.92  34.96
386   M   F 17.61 18.73 21.37 24.68 28.93 34.55  38.07
387   M   F 18.55 19.76 22.61 26.22 30.92 37.24  41.26
388   M   F 19.50 20.79 23.87 27.80 32.98 40.03  44.59
389   M   F 20.39 21.78 25.11 29.40 35.12 43.02  48.19
390   M   F 21.31 22.80 26.39 31.04 37.28 46.00  51.76
391   M   F 22.24 23.85 27.71 32.75 39.55 49.10  55.43
392   M   F 23.21 24.94 29.09 34.52 41.85 52.15  58.97
393   M   F 24.16 26.03 30.52 36.40 44.34 55.48  62.85
394   M   F 25.28 27.29 32.13 38.46 46.96 58.77  66.50
395   M   F 26.52 28.70 33.93 40.73 49.78 62.19  70.19
396   M   F 28.05 30.39 36.00 43.21 52.69 65.44  73.53
397   M   F 29.93 32.41 38.30 45.80 55.49 68.27  76.23
398   M   F 32.00 34.58 40.67 48.32 58.09 70.76  78.54
399   M   F 34.15 36.78 42.95 50.64 60.37 72.87  80.48
400   M   F 36.26 38.89 45.05 52.70 62.33 74.66  82.15
401   M   F 38.19 40.81 46.91 54.48 64.00 76.21  83.65
402   M   F 39.83 42.43 48.48 56.00 65.49 77.74  85.24
403   M   F 41.24 43.81 49.82 57.29 66.77 79.09  86.71
404   M   F 42.42 44.98 50.93 58.37 67.86 80.31  88.08
405   M   F 43.48 46.00 51.90 59.28 68.74 81.24  89.10
406   M   F 44.23 46.75 52.64 60.04 69.59 82.33  90.42
407   M   F 44.99 47.48 53.33 60.70 70.24 83.04  91.22
408   M   F 45.59 48.07 53.90 61.27 70.85 83.81  92.14
409   M   F 46.14 48.61 54.43 61.79 71.41 84.48  92.95
410   M   F 46.63 49.10 54.90 62.25 71.89 85.06  93.64
411   M   F 47.11 49.56 55.34 62.68 72.33 85.57  94.24
412   M   F 47.55 49.99 55.75 63.08 72.73 86.03  94.77
413   M   F 47.90 50.34 56.11 63.47 73.20 86.71  95.66
414   M   F 48.33 50.76 56.51 63.85 73.58 87.13  96.14
> 
> # P85 of BMI in 5-8 year old Dutch boys and girls
> e <- expand.grid(age=5:8, sex=c("M","F"))
> w <- z2y(z=rep(qnorm(0.85),nrow(e)), x=e$age, sex=e$sex, ref=nl4.bmi)
> w <- matrix(w, nrow=2, byrow=TRUE)
> dimnames(w) <- list(c("boys","girls"),5:8)
> w
           5      6      7      8
boys  17.152 17.282 17.508 17.857
girls 17.090 17.386 17.837 18.327
> 
> # data transformation of height z-scores to cm-scale
> z <- c(-1.83, 0.09, 2.33, 0.81, -1.20)
> x <- c(8.33,  0.23, 19.2, 24.3, 10)
> sex <- c("M", "M", "F", "M", "F")
> round(z2y(z=z, x=x, sex=sex, ref=nl4.hgt), 1)
[1] 123.8  60.7 185.3 189.7 135.6
> 
> # interpolate published height standard
> # to daily values, days 0-31, boys
> # on centiles -2SD, 0SD and +2SD
> days <- 0:31
> sds  <- c(-2, 0, +2)
> z    <- rep(sds, length(days))
> x    <- rep(round(days/365.25,4), each=length(sds))
> w    <- z2y(z, x, sex="M", ref=nl4.hgt)
> w    <- matrix(w, ncol=length(sds), byrow=TRUE)
> dimnames(w) <- list(days, sds)
> w
       -2      0      2
0  47.163 51.320 55.477
1  47.265 51.430 55.594
2  47.371 51.543 55.716
3  47.474 51.653 55.833
4  47.580 51.767 55.954
5  47.682 51.877 56.071
6  47.784 51.986 56.188
7  47.890 52.100 56.310
8  47.993 52.210 56.427
9  48.096 52.321 56.545
10 48.203 52.435 56.667
11 48.305 52.545 56.785
12 48.412 52.659 56.907
13 48.515 52.770 57.024
14 48.618 52.880 57.142
15 48.727 52.995 57.264
16 48.832 53.106 57.381
17 48.937 53.217 57.498
18 49.046 53.333 57.619
19 49.151 53.444 57.736
20 49.260 53.559 57.857
21 49.366 53.670 57.974
22 49.469 53.781 58.093
23 49.577 53.896 58.216
24 49.681 54.007 58.334
25 49.784 54.118 58.453
26 49.892 54.234 58.576
27 49.996 54.345 58.694
28 50.103 54.460 58.817
29 50.213 54.573 58.933
30 50.324 54.686 59.049
31 50.438 54.803 59.169
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>


Created & Maintained by Osamu Ogasawara (osamu.ogasawara@gmail.com) and IMSBIO