Spline dose-response functions
Used to fit B-splines, natural cubic splines, and piecewise linear splines\insertCite perperoglu2019MBNMAdose.
dspline( type = "bs", knots = 1, degree = 1, beta.1 = "rel", beta.2 = "rel", beta.3 = "rel", beta.4 = "rel", beta.5 = "rel", beta.6 = "rel" )
type: The type of spline. Can take "bs" (B-spline), "ns" (natural cubic spline), or "ls" (piecewise linear spline)knots: The number/location of spline internal knots. If a single number is given it indicates the number of knots (they will be equally spaced across the range of doses for each agent). If a numeric vector is given it indicates the location of the knots.degree: The degree of the piecewise B-spline polynomial - e.g. degree=1 for linear, degree=2 for quadratic, degree=3 for cubic.beta.1: Pooling for the 1st coefficient. Can take "rel", "common", "random" or be assigned a numeric value (see details).beta.2: Pooling for the 2nd coefficient. Can take "rel", "common", "random" or be assigned a numeric value (see details).beta.3: Pooling for the 3rd coefficient. Can take "rel", "common", "random" or be assigned a numeric value (see details).beta.4: Pooling for the 4th coefficient. Can take "rel", "common", "random" or be assigned a numeric value (see details).beta.5: Pooling for the 5th coefficient. Can take "rel", "common", "random" or be assigned a numeric value (see details).beta.6: Pooling for the 6th coefficient. Can take "rel", "common", "random" or be assigned a numeric value (see details).An object of class("dosefun")
| 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().
# Second order B spline with 2 knots and random effects on the 2nd coefficient dspline(type="bs", knots=2, degree=2, beta.1="rel", beta.2="rel") # Piecewise linear spline with knots at 0.1 and 0.5 quantiles # Single parameter independent of treatment estimated for 1st coefficient #with random effects dspline(type="ls", knots=c(0.1,0.5), beta.1="random", beta.2="rel")
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