fitBraidFlipped: Fit Flipped BRAID Surfaces

In braidrm: Fitting Combined Action with the BRAID Response Surface Model

Fit Flipped BRAID Surfaces

Description

Functions to fit protective, oppoistional and coactive BRAID surfaces, and more specific flipped surfaces if necessary.

Usage

fitBraidFlipped(formula, data, flip, model, links = NULL, ...)

fitProtectiveBraid_A(formula, data, ...)

fitProtectiveBraid_B(formula, data, ...)

fitOppositionalBraid_A(formula, data, ...)

fitOppositionalBraid_B(formula, data, ...)

fitCoactiveBraid_pure(formula, data, ...)

fitCoactiveBraid_partial(formula, data, ...)

Arguments

formula	Either an object of class formula such as would be provided to a modeling function like stats::lm(), or a width-2 numeric array vector of concentration pairs (including 0 or Inf). A formula should specify a single output as a function of two inputs, eg. activity ~ conc1 + conc2.
data	If forumula is a symbolic formula, a data frame containing the specified values. If formula is a numeric array of concentrations, a numeric vector of response values, the same length as the number of rows of formula.
flip	String specifying the direction or directions of the surface's flip. Must be one of "A", "B", or "both".
model, links	Parameters model and links are used to specify which variant of the BRAID model is fit to data. Model may be one of the following character strings: "kappa1", "kappa2", or "kappa3" (see Details), or a subset of the numbers 1 through 9 specifying which of the nine BRAID response surface parameters is allowed to vary when fitting. links allows the user to further specify constraints on the three BRAID maximal effect parameters (see Details for more). If model is one of the supported character strings, the parameter links will be ignored.
...	Additional parameters to be passed to braidrm

Details

Though fitBraidFlipped offers the option of fitting any flipped BRAID surface model specified by flip, this is not recommended, as the interplay between flipping paramteers and parameter constraints becomes very confusing very quickly. In nearly all cases, it is preferable to use one of the pre-defined flipped fitting functions.

fitProtectiveBraid_A and fitProtectiveBraid_B fit "protective" surfaces in which one drug has no effect in isolation, but attenuates or eliminates the effect of the other. fitProtectiveBraid_A generates a surface in which drug A is active and is attenuated by drug B; fitProtectiveBraid_B generates the reverse.

fitOppositinalBraid_A and fitOppositionalBraid_B produce "oppositional" surfaces in which a second drug produces an effect that is in the opposite direction to the first drug, but which is then overwhelmed by the effect of the first drug at higher concentrations. fitProtectiveBraid_A generates a surface in which the maximal effect of drug A dominates a high concentrations, fitProtectiveBraid_B generates the reverse. Note that the A and B in the function names specify which compound's effect is dominant, not the direction of the underlying flip; in actuality the surfaces generated by fitProtectiveBraid_A are produced by flipping along the B axis.

fitCoactiveBraid_pure and fitCoactiveBraid_partial produce "coactive" surfaces, in which both drugs have no or minimal effect in isolation, but produce a pronounced effect when both are present. fitCoactiveBraid_pure generates surfaces in which both drugs have no effect at all in isolation; fitCoactiveBraid_partial generates surfaces in which either drug may have a smaller partial effect in isolation.

Value

A fit object of class braidrmflip. This structure contains the exact same elements as an object of class braidrm (see braidrm() for details) along with one additional element: flip, a character value specifying the direction that the surface is flipped. The object's coefficients and flip fields can be used to evaluate and invert the best fit response surface using evalFlippedBraidModel() and invertFlippedBraidModel().

Examples

fbfit1 <- fitProtectiveBraid_A(measure ~ concA + concB,
                               protectiveExample, getCIs=FALSE)
coef(fbfit1)

fbfit2 <- fitOppositionalBraid_A(measure ~ concA + concB,
                                 oppositionalExample, getCIs=FALSE)
coef(fbfit2)

fbfit3 <- fitCoactiveBraid_pure(measure ~ concA + concB,
                                coactiveExample, getCIs=FALSE)
coef(fbfit3)

braidrm documentation built on Sept. 30, 2024, 9:40 a.m.