GetbYvalues: Experiments' outcome model intercepts for continuous ER.
In gpapadog/LERCA: Local Exposure-Response Confounding Adjustment

Description Usage Arguments

Get the bY values that make the ER curve continuous in simulated data when the X-Y relationship is truly piecewise linear.

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GetbYvalues(num_exper, Xrange = NULL, exper_change = NULL, bYX,
  interYexp1 = 0, out_coef, meanC, weights = NULL,
  XY_function = c("linear", "other"))

`num_exper`	The number of experiments. Should be > 1.
`Xrange`	The range of the exposure range. Specify if exper_change is NULL.
`exper_change`	The points of experiment change. Should be including the edges of the exposure range. If left NULL, exper_change will be specified as equally distanced points on Xrange such that num_exper experiments are defined.
`bYX`	If XY_function is set to linear, bYX includes the coefficient of the exposure within each experiment and is of length num_exper. If XY_function is set to other, bYX is of length 1 and corresponds to the coefficient in front of the exposure term.
`interYexp1`	The intercept of the outcome model in experiment 1. If not specified, it defaults to 0.
`out_coef`	A matrix with number of rows equal to the number of covariates and number of columns equal to the number of experiments including the outcome model coefficients.
`meanC`	A matrix of equal dimensions to out_coef including the mean of each covariate in each experiment.
`weights`	The weights to be given to the mean of each experiment in the calculation of the overall mean. Vector of length equal to the number of experiments. If left NULL, each experiment is given equal weight.
`XY_function`	String specifying whether the XY relationship is piece- wise linear (set 'linear'), or a continuous function supplied by the XY_spec arguement (set 'other').