getEffects: Function to create a Siena effects object
In RSiena: Siena - Simulation Investigation for Empirical Network Analysis

Description Usage Arguments Details Value Author(s) References See Also Examples

Creates a basic list of effects for all dependent variables in the input siena object.

1	getEffects(x, nintn = 10, behNintn=4, getDocumentation=FALSE, onePeriodSde=FALSE)

`x`	an object of class 'siena" or 'sienaGroup"
`nintn`	Number of user-defined network interactions that can later be created.
`behNintn`	Number of user-defined behavior interactions that can later be created.
`getDocumentation`	Flag to allow documentation of internal functions, not for use by users.
`onePeriodSde`	Flag to indicate that the stochastic differential equation (SDE) model dZ(t) = [aZ(t) + b] dt + g dW(t) should be used, instead of the regular SDE with a scale parameter. This is only relevant in case the model includes a continuous dependent variable and one period is studied.

Creates a data frame of effects for use in siena model estimation. The regular way of changing this object is by the functions includeEffects, setEffect, and includeInteraction.

Note that the class of the return object may be lost if the data.frame is edited using fix. See fix and edit.data.frame.

An object of class sienaEffects or sienaGroupEffects: this is a data frame of which the rows are the effects available for data set x.
The effects object consists of consecutive parts, each of which relates to one dependent variable in the input object. The columns are:

`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 to define the effect, if any
`interaction2`	third variable to define the effect, if any
`type`	"eval", "endow", "creation", or "rate"
`basicRate`	boolean: whether a basic rate parameter
`include`	boolean: include in the model to be fitted or not
`randomEffects`	boolean: random or fixed effect. Currently not used.
`fix`	boolean: fix parameter value or not
`test`	boolean: test parameter value or not
`timeDummy`	comma separated list of periods, or "all", or "," for none – which time dummy interacted parameters should be included?
`initialValue`	starting value for estimation, also used for `fix` and `test`.
`parm`	internal effect parameter values
`functionType`	"objective" or "rate"
`period`	period for basic rate parameters
`rateType`	"Structural", "covariate", "diffusion"
`untrimmedValue`	Used to store initial values which could be trimmed
`effect1`	Used to indicate effect number in user-specified interactions
`effect2`	Used to indicate effect number in user-specified interactions
`effect3`	Used to indicate effect number in user-specified interactions
`interactionType`	Defines "dyadic" or "ego" or "OK" effects, used in `includeInteraction`
`local`	whether a local effect; used for the option `localML` in `sienaAlgorithmCreate`
`effectFn`	here NULL, but could be replaced by a function later
`statisticFn`	here NULL, but could be replaced by a function later
`netType`	Type of dependent variable: "oneMode", "behavior", or "bipartite"
`groupName`	name of relevant group data object
`group`	sequential number of relevant group data object in total
`effectNumber`	a unique identifier of the row

The combination of name, shortName, interaction1, interaction2, and type uniquely identifies any effect other than basic rate effects and user-specified interaction effects. For the latter, effect1, effect2 and effect3 are also required for the identification. The combination name, shortName, period and group uniquely identifies a basic rate effect.

The columns not used for identifying the effect define how the effect is used for the estimation.

The columns initialValue and parm should not be confused: initialValue gives the initial value for the parameter to be estimated, indicated in the manual by theta; parm gives the internal value of the parameter defining the effect, indicated in the manual (Chapter 12) by p, and is fixed during the estimation.

A list of all effects in a given effects object (e.g., myeff), including their names of dependent variables, effect names, short names, and values of interaction1 and interaction2 (if any), is obtained by executing effectsDocumentation(myeff).

Ruth Ripley

See http://www.stats.ox.ac.uk/~snijders/siena/

sienaDataCreate, sienaGroupCreate, includeEffects, setEffect, updateSpecification, print.sienaEffects,effectsDocumentation

mynet1 <- sienaDependent(array(c(s501, s502, s503), dim=c(50, 50, 3)))
mybeh <- sienaDependent(s50a, type="behavior")
mycovar <- coCovar(rnorm(50))
mydyadcovar <- coDyadCovar(matrix(as.numeric(rnorm(2500) > 2), nrow=50))
mydata <- sienaDataCreate(mynet1, mybeh, mycovar, mydyadcovar)
myeff <- getEffects(mydata)
myeff

Warning message:
no DISPLAY variable so Tk is not available 
  name   effectName                      include fix   test  initialValue parm
1 mynet1 constant mynet1 rate (period 1) TRUE    FALSE FALSE    4.69604   0   
2 mynet1 constant mynet1 rate (period 2) TRUE    FALSE FALSE    4.32885   0   
3 mynet1 outdegree (density)             TRUE    FALSE FALSE   -1.46770   0   
4 mynet1 reciprocity                     TRUE    FALSE FALSE    0.00000   0   
5 mybeh  rate mybeh (period 1)           TRUE    FALSE FALSE    0.70571   0   
6 mybeh  rate mybeh (period 2)           TRUE    FALSE FALSE    0.84939   0   
7 mybeh  mybeh linear shape              TRUE    FALSE FALSE    0.32237   0   
8 mybeh  mybeh quadratic shape           TRUE    FALSE FALSE    0.00000   0