Re: [R] spaghetti plot - urgent

[Rosa Oliveira]

Thanks for the tip! Ulrik, I've solved the problem with a different
code

Best ;)

Ulrik Stervbo  escreveu em qua, 19/07/2017 às
20:28 :

> Hi Rosa,
>
> You pass a vector to ggplot, which expects a data.frame. I am sure you
> meant to do this:
>
> point7$y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7
> $epsilon_7
>
> ggplot(point7, aes(time, y_point7)) + geom_line()
>
> HTH
> Ulrik
>
>
> On Wed, 19 Jul 2017 at 20:37 Rosa Oliveira  wrote:
>
>> Hi everyone,
>>
>> I’m trying to do a spaghetti plot and I know I’m doing all wrong, It must
>> be.
>>
>> What I need:
>>
>> 15 subjects, each with measurements over 5 different times (t1, ..., t5),
>> and the variable that I need to represent in the spaguetti plot is given by:
>>
>> PCR = b0 + b1 * ti + epsilon
>>
>> B0, - baseline of each subject
>> B1 - trajectory of each subject over time (so multiply by t)
>> Epsilon - error associated with each subject
>>
>> Regression model with mixed effects.
>>
>> Thus, I generated b0, b1, epsilon and time created sequence.
>>
>> But I need to do spaguetti plot of the outcome and I can not understand
>> how much I search the publications.
>>
>> Sorry for the stupidity, but I do not even know how to do it and I need
>> it with the utmost urgency to finish a publication proposal :(
>>
>> Follows what I tried to do :( :( :(
>>
>>
>> library(ggplot2)
>> library(reshape)
>> library(lattice)
>> library(gtable)
>> library(grid)
>>
>>
>> set.seed(9027)
>>
>> n.longitudinal.observations  = 5  # number of PCR
>> measures (per subject) in the hospital period
>> subjects = 15  # Number
>> of simulations (1 per subject in the study)
>>
>> beta0_7_gerar  = rnorm(subjects, mean = 1, sd = .5)
>> beta0_7=
>> as.data.frame(matrix(beta0_7_gerar,nrow=subjects,ncol=1))  # beta 0 -
>> input variable used to calculate PCR (the outcome)
>> beta1_7_gerar = rnorm(subjects, mean = -1, sd = .5)
>> beta1_7   =
>> as.data.frame(matrix(beta1_7_gerar,nrow=subjects,ncol=1) )  # beta 1 -
>> input variable used to calculate PCR (the outcome)
>>
>> tj_gerar= seq.int(1,
>> n.longitudinal.observations, 1)
>> epsilon_7_gerar  = rnorm(5*subjects, mean = 0, sd = .1)
>> epsilon_7 =
>> as.data.frame(matrix(epsilon_7_gerar,nrow=subjects,ncol=1) )   # epsilon_7
>> - input variable used to calculate PCR (the outcome) - associated with each
>> subject
>>
>> tj  =
>> as.data.frame(matrix(tj_gerar,nrow=subjects,ncol=1) )   #
>> time
>>
>> point7 <- cbind(beta0_7, beta1_7, tj, epsilon_7)
>> point7
>> point7 <- as.data.frame(point7)
>>
>> colnames(point7) = c("beta0_7","beta1_7","time", "epsilon_7")
>>
>>
>> y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7
>> $epsilon_7 (the outcome of the study - PCR)
>> y_point7
>>
>> require(ggplot2)
>>
>> png('test.png')
>> p = ggplot(y_point7, aes(time, y_point7)) + geom_line()
>> print(p)
>> dev.off()
>> savehistory()
>>
>>
>>
>>
>>
>>
>> OR:
>>
>> In the last part I also tried:
>>
>>
>> ID = rep(1:3, each = 5)
>>
>>
>> point7 <- cbind(ID,beta0_7, beta1_7, tj, epsilon_7)
>> point7
>> point7 <- as.data.frame(point7)
>>
>> colnames(point7) = c("ID","beta0_7","beta1_7","time", "epsilon_7")
>>
>>
>>
>>
>>
>> y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7
>> $epsilon_7
>> y_point7
>>
>> crp7 <- y_point7
>>
>> head(point7, n = 15)
>>
>>
>> ggplot(aes(x = tj_gerar, y = crp7), data = point7) +
>>   geom_line(aes(group = ID), color = "gray") +
>>   geom_smooth(aes(group = 1), method = "lm", size = 3, color = "red", se
>> = FALSE) +
>>   theme_bw()
>>
>> But none of these worked :(
>>
>> I was looking to have something like:
>>
>>
>> Being the outcome PCR and the year the times (1, 2, 3, 4, 5).
>>
>> Can someone help me please?
>>
>>
>> Thanks,
>>
>> Best Rosa
>>
>>
>>
>> __
>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> --
Enviado do Gmail Mobile

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Re: [R] spaghetti plot - urgent

[Ulrik Stervbo]

Hi Rosa,

You pass a vector to ggplot, which expects a data.frame. I am sure you
meant to do this:

point7$y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7
$epsilon_7

ggplot(point7, aes(time, y_point7)) + geom_line()

HTH
Ulrik


On Wed, 19 Jul 2017 at 20:37 Rosa Oliveira  wrote:

> Hi everyone,
>
> I’m trying to do a spaghetti plot and I know I’m doing all wrong, It must
> be.
>
> What I need:
>
> 15 subjects, each with measurements over 5 different times (t1, ..., t5),
> and the variable that I need to represent in the spaguetti plot is given by:
>
> PCR = b0 + b1 * ti + epsilon
>
> B0, - baseline of each subject
> B1 - trajectory of each subject over time (so multiply by t)
> Epsilon - error associated with each subject
>
> Regression model with mixed effects.
>
> Thus, I generated b0, b1, epsilon and time created sequence.
>
> But I need to do spaguetti plot of the outcome and I can not understand
> how much I search the publications.
>
> Sorry for the stupidity, but I do not even know how to do it and I need it
> with the utmost urgency to finish a publication proposal :(
>
> Follows what I tried to do :( :( :(
>
>
> library(ggplot2)
> library(reshape)
> library(lattice)
> library(gtable)
> library(grid)
>
>
> set.seed(9027)
>
> n.longitudinal.observations  = 5  # number of PCR
> measures (per subject) in the hospital period
> subjects = 15  # Number of
> simulations (1 per subject in the study)
>
> beta0_7_gerar  = rnorm(subjects, mean = 1, sd = .5)
> beta0_7=
> as.data.frame(matrix(beta0_7_gerar,nrow=subjects,ncol=1))  # beta 0 -
> input variable used to calculate PCR (the outcome)
> beta1_7_gerar = rnorm(subjects, mean = -1, sd = .5)
> beta1_7   =
> as.data.frame(matrix(beta1_7_gerar,nrow=subjects,ncol=1) )  # beta 1 -
> input variable used to calculate PCR (the outcome)
>
> tj_gerar= seq.int(1,
> n.longitudinal.observations, 1)
> epsilon_7_gerar  = rnorm(5*subjects, mean = 0, sd = .1)
> epsilon_7 =
> as.data.frame(matrix(epsilon_7_gerar,nrow=subjects,ncol=1) )   # epsilon_7
> - input variable used to calculate PCR (the outcome) - associated with each
> subject
>
> tj  =
> as.data.frame(matrix(tj_gerar,nrow=subjects,ncol=1) )   #
> time
>
> point7 <- cbind(beta0_7, beta1_7, tj, epsilon_7)
> point7
> point7 <- as.data.frame(point7)
>
> colnames(point7) = c("beta0_7","beta1_7","time", "epsilon_7")
>
>
> y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7
> $epsilon_7 (the outcome of the study - PCR)
> y_point7
>
> require(ggplot2)
>
> png('test.png')
> p = ggplot(y_point7, aes(time, y_point7)) + geom_line()
> print(p)
> dev.off()
> savehistory()
>
>
>
>
>
>
> OR:
>
> In the last part I also tried:
>
>
> ID = rep(1:3, each = 5)
>
>
> point7 <- cbind(ID,beta0_7, beta1_7, tj, epsilon_7)
> point7
> point7 <- as.data.frame(point7)
>
> colnames(point7) = c("ID","beta0_7","beta1_7","time", "epsilon_7")
>
>
>
>
>
> y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7 $epsilon_7
> y_point7
>
> crp7 <- y_point7
>
> head(point7, n = 15)
>
>
> ggplot(aes(x = tj_gerar, y = crp7), data = point7) +
>   geom_line(aes(group = ID), color = "gray") +
>   geom_smooth(aes(group = 1), method = "lm", size = 3, color = "red", se =
> FALSE) +
>   theme_bw()
>
> But none of these worked :(
>
> I was looking to have something like:
>
>
> Being the outcome PCR and the year the times (1, 2, 3, 4, 5).
>
> Can someone help me please?
>
>
> Thanks,
>
> Best Rosa
>
>
>
> __
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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and provide commented, minimal, self-contained, reproducible code.

[R] spaghetti plot - urgent

[Rosa Oliveira]

Hi everyone, 

I’m trying to do a spaghetti plot and I know I’m doing all wrong, It must be.

What I need:

15 subjects, each with measurements over 5 different times (t1, ..., t5), and 
the variable that I need to represent in the spaguetti plot is given by:

PCR = b0 + b1 * ti + epsilon

B0, - baseline of each subject
B1 - trajectory of each subject over time (so multiply by t)
Epsilon - error associated with each subject

Regression model with mixed effects.

Thus, I generated b0, b1, epsilon and time created sequence.

But I need to do spaguetti plot of the outcome and I can not understand how 
much I search the publications.

Sorry for the stupidity, but I do not even know how to do it and I need it with 
the utmost urgency to finish a publication proposal :(

Follows what I tried to do :( :( :( 


library(ggplot2)
library(reshape)
library(lattice)
library(gtable)
library(grid)


set.seed(9027)

n.longitudinal.observations  = 5  # number of PCR 
measures (per subject) in the hospital period
subjects = 15  # Number of 
simulations (1 per subject in the study)

beta0_7_gerar  = rnorm(subjects, mean = 1, sd = .5) 
beta0_7= 
as.data.frame(matrix(beta0_7_gerar,nrow=subjects,ncol=1))  # beta 0 - input 
variable used to calculate PCR (the outcome)  
beta1_7_gerar = rnorm(subjects, mean = -1, sd = .5)
beta1_7   = 
as.data.frame(matrix(beta1_7_gerar,nrow=subjects,ncol=1) )  # beta 1 - 
input variable used to calculate PCR (the outcome)

tj_gerar= seq.int(1, 
n.longitudinal.observations, 1)
epsilon_7_gerar  = rnorm(5*subjects, mean = 0, sd = .1)
epsilon_7 = 
as.data.frame(matrix(epsilon_7_gerar,nrow=subjects,ncol=1) )   # epsilon_7 - 
input variable used to calculate PCR (the outcome) - associated with each 
subject

tj  = 
as.data.frame(matrix(tj_gerar,nrow=subjects,ncol=1) )   # time 

point7 <- cbind(beta0_7, beta1_7, tj, epsilon_7) 
point7
point7 <- as.data.frame(point7)

colnames(point7) = c("beta0_7","beta1_7","time", "epsilon_7")


y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7 $epsilon_7 
(the outcome of the study - PCR)
y_point7

require(ggplot2)

png('test.png')
p = ggplot(y_point7, aes(time, y_point7)) + geom_line()
print(p)
dev.off()
savehistory()






OR:

In the last part I also tried:


ID = rep(1:3, each = 5)


point7 <- cbind(ID,beta0_7, beta1_7, tj, epsilon_7) 
point7
point7 <- as.data.frame(point7)

colnames(point7) = c("ID","beta0_7","beta1_7","time", "epsilon_7")





y_point7 <- point7$beta0_7 + point7$beta1_7*point7$time + point7 $epsilon_7
y_point7

crp7 <- y_point7

head(point7, n = 15)


ggplot(aes(x = tj_gerar, y = crp7), data = point7) +
  geom_line(aes(group = ID), color = "gray") + 
  geom_smooth(aes(group = 1), method = "lm", size = 3, color = "red", se = 
FALSE) +
  theme_bw()

But none of these worked :(

I was looking to have something like:


Being the outcome PCR and the year the times (1, 2, 3, 4, 5).

Can someone help me please?


Thanks,

Best Rosa 



__
R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.