runBraidAnalysis: BRAID Surface Analysis

In braidReports: Visualize Combined Action Response Surfaces and Report BRAID Analyses

BRAID Surface Analysis

Description

Performs a convenient pre-built set of BRAID and dose-response analysis tasks

Usage

runBraidAnalysis(
  formula,
  data,
  defaults,
  weights = NULL,
  start = NULL,
  direction = 0,
  lower = NULL,
  upper = NULL,
  useBIC = TRUE,
  ...
)

## S3 method for class 'formula'
runBraidAnalysis(
  formula,
  data,
  defaults,
  weights = NULL,
  start = NULL,
  direction = 0,
  lower = NULL,
  upper = NULL,
  useBIC = TRUE,
  ...
)

## Default S3 method:
runBraidAnalysis(
  formula,
  data,
  defaults,
  weights = NULL,
  start = NULL,
  direction = 0,
  lower = NULL,
  upper = NULL,
  useBIC = TRUE,
  ...
)

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.
defaults	Default minimal and maximal effect values used to fix effect parameters during model selection.
weights	A vector of weights (between 0 and 1) the same length as the data which determines the weight with which each measurement will impact the the sum of squared errors. Weights will be multiplied by errors before squaring. If NULL (the default) all weights will be set to 1. Can be a numeric vector, or the name of a column in data if formula is a symbolic formula
start	A BRAID parameter vector specifying the first guess where the non-linear optimization should begin. May be a length 7, 8, or 9 vector, though a full length vector is always preferable. If NULL (the default), it will be estimated from the data.
direction	Determines the possible directionality of the BRAID model. If 0 (the default) no additional constraints are placed on the parameters. If greater than 0, the fitting will require that the maximal effects are all greater than or equal to the minimal effect. If less than 0, the fitting will require that all maximal effect is less than or equal to the minimal effect.
lower	A numeric vector of lower bounds on the fitted parameter values. May be the same length as the number of fitted parameters, or a full, length-9 vector. Missing or unspecified lower bounds may be included as NA or Inf; if unspecified, lower bounds on the first five parameters (IDMA, IDMB, na, nb, and kappa) will be automatically estimated from the data. Bounds on the minimal and maximal effect parameters however (E0, EfA, EfB, and Ef) will be assumed to be infinite unless specified. A value of NULL, the default, will be treated as all lower parameter bounds being unspecified.
upper	A numeric vector of upper bounds on the fitted parameter values. Used in the same way as lower.
useBIC	If TRUE (the default), the best (read: most parsimonious) model will be selected from all tested models using the Bayesian information criterion (Schwarz 1978). If FALSE the function will follow the convention of earlier versions of the braidrm package and use the Akaike information criterion (Akaike 1974).
...	Additional parameters to be passed to braidrm::findBestBraid()

Value

An object of class braidAnalysis, containing the following values:

• concs: a width-two array containing the two tested doses for each measurement

• act: a numeric vector with as many values as concs has rows, containing the measured values for each measurement

• weights: a numeric vector of weights, the same length as act, specifying the weight given to each measurement in fitting. All weights are 1 by default

• braidFit: a fit object of class braidrm containing the best-fit BRAID surface according to the given constraints

• hillFit1: If the given data contains measurements of the first drug in isolation, those measurements are fit using basicdrm::findBestHillModel; the results of this analysis are stored as an object of class hillrm as hillFit1. If no such measurements are found, this will be NULL

• hillFit2: the corresponding fit for measurements of the second drug alone, if they are included; NULL otherwise

Examples

surface <- synergisticExample

analysis <- runBraidAnalysis(measure~concA+concB, surface, defaults=c(0,1))

names(analysis)

braidReports documentation built on Sept. 30, 2024, 1:06 a.m.