create_design: Create design variables for a full description of a design.

In PopED: Population (and Individual) Optimal Experimental Design

Description

Create design variables to fully describe a design. If variables are supplied then these variables are checked for consistency and, if possible, changed to sizes that make sense if there are inconsistencies. Returns a list of matricies compatible with PopED.

Usage

create_design(
  xt,
  groupsize,
  m = NULL,
  x = NULL,
  a = NULL,
  ni = NULL,
  model_switch = NULL
)

Arguments

xt	Matrix defining the sampling schedule. Each row is a group.
groupsize	Vector defining the size of the different groups (number of individuals in each group).
m	A number defining the number of groups. Computed from xt if not defined.
x	A matrix defining the discrete design variables for the model Each row is a group.
a	Matrix defining the continuous design variables. Each row is a group.
ni	Vector defining the number of samples for each group, computed as all elements of xt for each group by default.
model_switch	Matrix defining which response a certain sampling time belongs to. Defaults to one for all elements of xt.

Details

If a value (or a vector/list of values) is supplied that corresponds to only one group and the design has multiple groups then all groups will have the same value(s). If a matrix is expected then a list of lists can be supplied instead, each list corresponding to a group.

See Also

Other poped_input: convert_variables(), create.poped.database(), create_design_space(), downsizing_general_design(), poped.choose()

Examples

library(PopED)

xt1 <- list(c(1,2,3),c(1,2,3,4))
xt4 <- list(c(1,2,3,4,5),c(1,2,3,4))
xt2 <- rbind(c(1,2,3,4),c(1,2,3,4))
xt3 <- c(1,2,3,4)

design_1 <- create_design(xt=xt1,groupsize=20)
design_2 <- create_design(xt=xt4,groupsize=20)
design_3 <- create_design(xt=xt2,groupsize=20)
design_4 <- create_design(xt=xt3,groupsize=20)

design_5 <- create_design(xt=xt3,groupsize=20,m=3)

design_6 <- create_design(xt=xt1,groupsize=20,model_switch=ones(2,4))

design_7 <-create_design(xt=xt1,groupsize=20,a=c(2,3,4))
design_8 <-create_design(xt=xt1,groupsize=20,a=rbind(c(2,3,4),c(4,5,6)))
design_9 <-create_design(xt=xt1,groupsize=20,a=list(c(2,3,4,6),c(4,5,6)))
design_10 <-create_design(xt=xt1,groupsize=20,a=list(c(2,3,4),c(4,5,6)))

design_11 <-create_design(xt=c(0,1,2,4,6,8,24),
                         groupsize=50,
                         a=c(WT=70,DOSE=1000))

design_12 <-create_design(xt=c(0,1,2,4,6,8,24),
                         groupsize=50,
                         a=c(WT=70,DOSE=1000),m=2)

design_13 <-create_design(xt=c(0,1,2,4,6,8,24),
                         groupsize=50,
                         a=list(c(WT=70,DOSE=1000),c(DOSE=90,WT=200,AGE=45)),m=2)

design_14 <-create_design(xt=c(0,1,2,4,6,8,24),
                         groupsize=50,
                         a=list(list(WT=70,DOSE=1000),list(DOSE=90,WT=200,AGE=45)),m=2)

design_15 <-create_design(xt=xt4,
                          groupsize=c(50,20),
                          a=rbind(c("DOSE"=2,"WT"=3,"AGE"=4),
                                  c(4,5,6)))

PopED documentation built on May 21, 2021, 5:08 p.m.