getEffects {RSiena} | R Documentation |
Creates a basic list of effects for each of the dependent variables in the input siena object.
getEffects(x, nintn = 10)
x |
an object of class `siena' or `sienaGroup' |
nintn |
Number of lines for user defined interactions. (maybe superfluous now!) |
Considers all the elements of the input siena data object and creates
lists of effects for use in siena model fits. Note that the class of the
return object may be lost if the data.frame is edited using fix
.
An object of class "effects" or "groupEffects": this is a data frame, each part of which relates to one dependent variable in the input object, with columns
name |
name of the dependent variable |
effectName |
name of the effect |
functionName |
name of the function |
shortName |
short name for the effect |
interaction1 |
second variable in interaction, if any |
interaction2 |
third variable in interaction, if any |
type |
"eval","endow", or "rate" |
basicRate |
boolean: whether a basic rate parameter |
include |
boolean: include or not |
randomEffects |
boolean: random or fixed effect |
fix |
boolean: fix value or not |
test |
boolean: test required or not |
initialValue |
starting value for estimation |
parm |
parameter values |
functionType |
"objective", "rate" |
period |
period for basic rate parameters |
rateType |
"Structural", "covariate" |
effectFn |
here NULL, but could be replaced by a function later |
statisticFn |
here NULL, but could be replaced by a function later |
untrimmedValue |
Used to store initial values which could be trimmed |
netType |
"oneMode", "Behavior", "Bipartite" |
groupName |
name of relevant data object |
group |
sequential number of relevant data object in total |
Ruth Ripley
See http://www.stats.ox.ac.uk/~snijders/siena/
mynet1 <- sienaNet(array(c(s501, s502, s503), dim=c(50, 50, 3))) mynet2 <- sienaNet(s50a, type='behavior') mycovar <- coCovar(rnorm(50)) mydyadcovar <- coDyadCovar(matrix(as.numeric(rnorm(2500) > 2), nrow=50)) mydata <- sienaDataCreate(mynet1, mynet2, mycovar, mydyadcovar) myeff <- getEffects(mydata)