In the simulated data, we specify the outcome model and residual variance for every experiment and the outcome is generated.
1 | GenYgivenXC(dataset, out_coef, bY, bYX, Ysd, XY_function, XY_spec = NULL)
|
dataset |
A data frame containing X, C1, C2, ..., and E. |
out_coef |
A matrix where the ij element is the coefficient of covariate Ci in the outcome model of experiment j. |
bY |
Vector of length equal to the number of experiments including the intercept of the outcome model in each experiment. |
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. |
Ysd |
Vector of length number of experiments. Standard deviation of outcome model residual. |
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'). |
XY_spec |
Needs to be specified if XY_function is set to 'other'. It is the function that specifies the true ER relationship. Defaults to NULL. |
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