ditp.RdSimilar parameterisation to the Emax model but with non-asymptotic maximal effect (Emax). Proposed by proposed by Fu and Manner (2010)
ditp(emax = "rel", rate = "rel", p.expon = FALSE)Pooling for Emax parameter. Can take "rel", "common", "random" or be
assigned a numeric value (see details).
Pooling for Rate parameter. Can take "rel", "common", "random" or be
assigned a numeric value (see details).
A logical object to indicate whether ed50 and hill parameters should be
expressed within the dose-response function on an exponential scale
An object of class("dosefun")
Emax represents the maximum response. Rate represents the rate at which a change in the dose of the drug leads to a change in the effect
$${E_{max}}\times\frac{(1-exp(-{rate}\times{x}))}{(1-exp(-{rate}\times{max(x)}))}$$
| Argument | Model specification |
"rel" | Implies that relative effects should be pooled for this dose-response parameter separately for each agent in the network. |
"common" | Implies that all agents share the same common effect for this dose-response parameter. |
"random" | Implies that all agents share a similar (exchangeable) effect for this dose-response parameter. This approach allows for modelling of variability between agents. |
numeric() | Assigned a numeric value, indicating that this dose-response parameter should not be estimated from the data but should be assigned the numeric value determined by the user. This can be useful for fixing specific dose-response parameters (e.g. Hill parameters in Emax functions) to a single value. |
When relative effects are modelled on more than one dose-response parameter,
correlation between them is automatically estimated using a vague inverse-Wishart prior.
This prior can be made slightly more informative by specifying the scale matrix omega
and by changing the degrees of freedom of the inverse-Wishart prior
using the priors argument in mbnma.run().
Fu H, Manner D (2010). “Bayesian adaptive dose-finding studies with delayed responses.” J Biopharm Stat, 20(5), 1055-1070. doi:10.1080/10543400903315740 .
# Model a common effect on rate
ditp(emax="rel", rate="common")
#> $name
#> [1] "itp"
#>
#> $fun
#> ~emax * (1 - exp(-rate * dose))/(1 - exp(-rate * max(dose)))
#> <environment: 0x55e26c256f40>
#>
#> $params
#> [1] "emax" "rate"
#>
#> $nparam
#> [1] 2
#>
#> $jags
#> [1] "s.beta.1[agent[i,k]] * ((1-exp(-s.beta.2[agent[i,k]]*dose[i,k])) / (1-exp(-s.beta.2[agent[i,k]]*maxdose)))"
#>
#> $apool
#> emax rate
#> "rel" "common"
#>
#> $bname
#> emax rate
#> "beta.1" "beta.2"
#>
#> $p.expon
#> [1] FALSE
#>
#> attr(,"class")
#> [1] "dosefun"