ED estimates marginal effective doses (ECp/EDp/ICp) for given reponse levels, conditional on the estimated variance components.
EDmarg(object, respLev, interval = c("none", "delta", "fls", "tfls"), clevel = NULL, level = ifelse(!(interval == "none"), 0.95, NULL), reference = c("control", "upper"), type = c("relative", "absolute"), nGQ = 5, rfinterval = c(0, 1000), lref, uref, bound = TRUE, display = TRUE, logBase = NULL, ...)
| object | an object of class 'medrc'. |
|---|---|
| respLev | a numeric vector containing the response levels. |
| interval | character string specifying the type of confidence intervals to be supplied. The default is "none". Use "delta" for asymptotics-based confidence intervals (using the delta method and the t-distribution). Use "fls" for from logarithm scale based confidence intervals (in case the parameter in the model is log(ED50) as for the |
| clevel | character string specifying the curve id in case on estimates for a specific curve or compound is requested. By default estimates are shown for all curves. |
| level | numeric. The level for the confidence intervals. The default is 0.95. |
| reference | character string. Is the upper limit or the control level the reference? |
| type | character string. Whether the specified response levels are absolute or relative (default). |
| nGQ | integer. Specifies the number nof nodes for Gauss-Hermite quadrature. |
| rfinterval | numeric vector. Interval for root finding (uniroot) to search for ED values. |
| lref | numeric value specifying the lower limit to serve reference. |
| uref | numeric value specifying the upper limit to serve reference (eg. 100%). |
| bound | logical. If TRUE only ED values between 0 and 100% are allowed. FALSE is useful for hormesis models. |
| display | logical. If TRUE results are displayed. Otherwise they are not (useful in simulations). |
| logBase | numeric. The base of the logarithm in case logarithm transformed dose values are used. |
| ... | additional arguments |
A matrix with two or more columns, containing the estimates and the corresponding estimated standard errors and possibly lower and upper confidence limits.