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Darren Shaw

2004-May-14 10:11 UTC

[R] NLME model question

Dear R-helpers

I have a problem related to the use of NLME

I think is simply a matter of getting the nlme coding correct, but i cannot 
get my brain around it

I am analysing some 24 growth curves of some cells , and i wanted to say 
that there are significant differences between the curves in two parameters 
that describe the pattern of growth.  these parameters are from a logistic 
(r & k) .

i have attempted to construct a self starting routine for nlme ie:

SSGrowth_function(x, r, k)
{
         .expr2 <- (k - 100000)/100000
         .expr5 <- exp(((r * -1) * x))
         .expr7 <- 1 + (.expr2 * .expr5)
         .expr13 <- .expr7^2
         .value <- k/.expr7
         .actualArgs <- match.call()[c("r", "k")]
         if(all(unlist(lapply(as.list(.actualArgs), is.name)))) {
                 .grad <- array(0, c(length(.value), 2), list(NULL,
c("r",
"k")))
                 .grad[, "r"] <-  - ((k * (.expr2 * (.expr5 * (-1 *
x))))/.expr13)
                 .grad[, "k"] <- (1/.expr7) - ((k * (1e-005 *
.expr5))/.expr13)
                 dimnames(.grad) <- list(NULL, .actualArgs)
                 attr(.value, "gradient") <- .grad
         }
         .value
}

where x = time, 100000 = known starting conditions, r = growth and k = 
carrying capacity

  i guessed i should then write

nlme(NoofCells~SSGrowth(Time,r,k),fixed=r+k~1,data=CellData,random=r+k~1)


This runs and tells me that r & k's do differ

BUT.  The "CellData" actually consists of replicates - ie there are 4
cell
types, but they are done 6 times each.  Therefore, I do not want to ask if 
there are significant differences in r & k between 24 sets of data 
("Runs")- rather I want to be able to say that there are differences 
between the four cell types occurring 6 times each.  So how do 
i  incorporate "CellType" explicitly into my model structure??

i.e. If i was lust looking at say linear growth and was using lme I would 
have written something like

lme(NoofCells~Time*CellType,random=~1|Runs,data=CellData)

Any thoughts/suggestions gratefully received

Darren Shaw

-----------------------------------------------------------------
Dr Darren J Shaw
Centre for Tropical Veterinary Medicine (CTVM)
Royal School of Veterinary Studies
The University of Edinburgh
Scotland

Douglas Bates

2004-May-14 11:49 UTC

head link

[R] NLME model question

Darren Shaw <Darren.Shaw at ed.ac.uk> writes:
> Dear R-helpers
> 
> I have a problem related to the use of NLME
> 
> I think is simply a matter of getting the nlme coding correct, but i
> cannot get my brain around it
> 
> 
> I am analysing some 24 growth curves of some cells , and i wanted to
> say that there are significant differences between the curves in two
> parameters that describe the pattern of growth.  these parameters are
> from a logistic (r & k) .
> 
> 
> i have attempted to construct a self starting routine for nlme ie:
> 
> SSGrowth_function(x, r, k)
> {
>          .expr2 <- (k - 100000)/100000
>          .expr5 <- exp(((r * -1) * x))
>          .expr7 <- 1 + (.expr2 * .expr5)
>          .expr13 <- .expr7^2
>          .value <- k/.expr7
>          .actualArgs <- match.call()[c("r", "k")]
>          if(all(unlist(lapply(as.list(.actualArgs), is.name)))) {
>                  .grad <- array(0, c(length(.value), 2), list(NULL,
>                  c("r", "k")))
> 
>                  .grad[, "r"] <-  - ((k * (.expr2 * (.expr5 *
(-1 *
>                  x))))/.expr13)
> 
>                  .grad[, "k"] <- (1/.expr7) - ((k * (1e-005 *
.expr5))/.expr13)
>                  dimnames(.grad) <- list(NULL, .actualArgs)
>                  attr(.value, "gradient") <- .grad
>          }
>          .value
> }
> 
> where x = time, 100000 = known starting conditions, r = growth and k >
carrying capacity
> 
> 
>   i guessed i should then write
> 
> nlme(NoofCells~SSGrowth(Time,r,k),fixed=r+k~1,data=CellData,random=r+k~1)
> 
> 
> This runs and tells me that r & k's do differ
> 
> BUT.  The "CellData" actually consists of replicates - ie there
are 4
> cell types, but they are done 6 times each.  Therefore, I do not want
> to ask if there are significant differences in r & k between 24 sets
> of data ("Runs")- rather I want to be able to say that there are
> differences between the four cell types occurring 6 times each.  So
> how do i  incorporate "CellType" explicitly into my model
structure??
> 
> 
> i.e. If i was lust looking at say linear growth and was using lme I
> would have written something like
> 
> 
> lme(NoofCells~Time*CellType,random=~1|Runs,data=CellData)
> 
> Any thoughts/suggestions gratefully received
I believe you want

nlme(NoofCells~SSGrowth(Time,r,k),fixed=r+k~1,data=CellData,random=r+k~1|Runs)

kjetil@acelerate.com

2004-May-14 12:32 UTC

head link

[R] NLME model question

On 14 May 2004 at 11:11, Darren Shaw wrote:
> Dear R-helpers
> 
> I have a problem related to the use of NLME
> 
> I think is simply a matter of getting the nlme coding correct, but i
> cannot get my brain around it
> 
> I am analysing some 24 growth curves of some cells , and i wanted to
> say that there are significant differences between the curves in two
> parameters that describe the pattern of growth.  these parameters are
> from a logistic (r & k) .
> 
> i have attempted to construct a self starting routine for nlme ie:
> 
> SSGrowth_function(x, r, k)
> {
>          .expr2 <- (k - 100000)/100000
>          .expr5 <- exp(((r * -1) * x))
>          .expr7 <- 1 + (.expr2 * .expr5)
>          .expr13 <- .expr7^2
>          .value <- k/.expr7
>          .actualArgs <- match.call()[c("r", "k")]
>          if(all(unlist(lapply(as.list(.actualArgs), is.name)))) {
>                  .grad <- array(0, c(length(.value), 2), list(NULL,
>                  c("r", 
> "k")))
>                  .grad[, "r"] <-  - ((k * (.expr2 * (.expr5 *
(-1 *
> x))))/.expr13)
>                  .grad[, "k"] <- (1/.expr7) - ((k * (1e-005 *
>                  .expr5))/.expr13) dimnames(.grad) <- list(NULL,
>                  .actualArgs) attr(.value, "gradient") <-
.grad
>          }
>          .value
> }
> 
> where x = time, 100000 = known starting conditions, r = growth and k >
carrying capacity
> 
>   i guessed i should then write
> 
> nlme(NoofCells~SSGrowth(Time,r,k),fixed=r+k~1,data=CellData,random=r+k
> ~1)
> 
> 
> This runs and tells me that r & k's do differ
> 
> BUT.  The "CellData" actually consists of replicates - ie there
are 4
> cell types, but they are done 6 times each.  Therefore, I do not want
> to ask if there are significant differences in r & k between 24 sets
> of data ("Runs")- rather I want to be able to say that there are
> differences between the four cell types occurring 6 times each.  So
> how do i  incorporate "CellType" explicitly into my model
structure??
Something like
 nlme(NoofCells~SSGrowth(Time,r,k),fixed=r+k~1,data=CellData,random=r+k
 ~1 | CellType)
?

Kjetil Halvorsen
> 
> i.e. If i was lust looking at say linear growth and was using lme I
> would have written something like
> 
> lme(NoofCells~Time*CellType,random=~1|Runs,data=CellData)
> 
> Any thoughts/suggestions gratefully received
> 
> Darren Shaw
> 
> ----------------------------------------------------------------- Dr
> Darren J Shaw Centre for Tropical Veterinary Medicine (CTVM) Royal
> School of Veterinary Studies The University of Edinburgh Scotland
> 
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>

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