profLikCITrueTies: Find confidence intervals for a parameter in an OADA with...
In whoppitt/NBDA: A Package For Implementing Network-Based Diffusion Analysis

Description Usage Arguments Details Value See Also

Find the confidence intervals for a specific parameter in an OADA with trueTies

1 2	profLikCITrueTies(which, model, interval, inflation = 1, conf = 0.95, startValue = NULL, lower = NULL, upper = NULL)

`which`	numeric giving the parameter for which the profile likelihood is to be plotted. The appropriate number can be identified from the fitted model, by entering `<modelName>@varNames` to extract the variable names from the model. Each variable name is preceded by its number.
`model`	object of class `oadaFit`.
`interval`	numeric vector of length two, providing a range within which the required endpoint of the confidence interval is known to be located. This range can be indentified using `plotProfLikTrueTies`.
`inflation`	numerical to be used if the confidence intervals are to be inflated by a specified amount, as suggested by Burnham & Anderson (2000) to allow for model selection uncertainty. This simply increases the height of the dotted line above the model maximum likelihood by a factor of `inflation`.
`conf`	numerical giving the level of confidence required, defaulting to the traditional 0.95.
`startValue`	optional numeric vector giving start values for the maximum likelihood optimization. Length to match the number of parameters fitted in the model.
`lower`	optional numeric vector giving lower values for the maximum likelihood optimization. Length to match the number of parameters fitted in the model. By default taken to be 0 for all s parameters and -Inf for coefficients of ILVs.
`upper`	optional numeric vector giving upper values for the maximum likelihood optimization. Length to match the number of parameters fitted in the model. By default taken to be Inf for all parameters.

An alternative to find confidence intervals, intended for data with trueTies, only works for socialmodels. Functions in much the same way as profLikCI, except it cannot be used to find the confidence intervalfor the difference between two parameters, and the upper and lower endpoints need to be found separately. To find the confidence intervalfor the difference between two parameters this use plotProfLikDiffTrueTies.

numeric giving the location of the required endpoint.

profLikCI,plotProfLikTrueTies, plotProfLikDiffTrueTies

whoppitt/NBDA documentation built on April 25, 2021, 7:55 a.m.