Description Usage Arguments Details Value Author(s) Examples
The cemtool()
package provides a step-by-step tool to guide users in building a default Markov model.
The tool guides the user though the steps of the development of a Markov model and will present the final result using graphs and tables.
The only prerequisite is that the user knows the structure of the model and the transition probabilities, no calculations or coding is required.
1 2 3 4 5 6 | cemprob(HS = cemtool.env$HS, HS1 = cemtool.env$HS1,
HS2 = cemtool.env$HS2, HS3 = cemtool.env$HS3,
HS4 = cemtool.env$HS4, HS5 = cemtool.env$HS5,
dead = cemtool.env$dead, n.t = cemtool.env$n.t,
control = cemtool.env$control,
intervention = cemtool.env$intervention)
|
HS |
Number of healthstates |
HS1 |
String with name of healthstate 1 |
HS2 |
String with name of healthstate 2 |
HS3 |
String with name of healthstate 3 |
HS4 |
String with name of healthstate 4 |
HS5 |
String with name of healthstate 5 |
dead |
String with name of absorption / death state |
n.t |
Number of cycles |
control |
String with name of the usual care strategy |
intervention |
String with name of the intervention strategy |
All input arguments can be generated and saved with the cemtool()
function. (cemtool.env <- cemtool())
There are multiple software systems that can be used to build Markov models for cost-effectiveness analyses
like TreeAge, Excel or R. Although there are numerous advantages to use R over the others,
the biggest downside is the steep learning curve from R.
The cemtool()
package aims to close this gap by introducing a step-by-step tool
to guide users in building a default Markov models.
The tool guides the user though the steps of the development of a Markov model
and will present the final result using graphs and tables.
The only prerequisite is that the user knows the structure of the model and the transition probabilities,
no calculations or coding is required.
The following variables will be created in the saved in the cemtool enviroment:
— Empty Markov trace matrices for both strategies (m.M and m.M_treatment)
— A dataframe with the modelinput (modelinput)
— Discount rate for costs (d.rc) and effects (d.re)
The function will automatically run cemtpm()
after finishing
S.R.W. Wijn MSc <stan.wijn@radboudumc.nl>
1 2 3 4 5 6 7 8 9 | ## Not run:
cemtool() # Start from stratch (clear the cemtool environment from the Global Environment)
cemprob() # Start from the second phase (definding the parameters)
cemtpm() # Start from the third phase (modify the transition probability matrix)
cemrun() # Run the model with the current m.M markov trace and m.P transition probability matrix
cemtool.env <- cemtool() # To save all input for further modification
## End(Not run)
|
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