Generalized Estimating Equation Design Object

DESCRIPTION:

Objects of class geeDesign created by designing a generalized estimating equation model before fitting.

GENERATION:

These objects are generated by function geeDesign.

METHODS:

The class "geeDesign" has print and summary methods.

STRUCTURE:

Object of class "geeDesign" is a list with three components:

VALUE:

call
an image of the call that produced the object.
gee.model
an object of class "geeModel" used in the algorithm iterations. It contains the following components.
"family": a character string indicating the family.
"link": a character string indicating the link used in the family.
"x": numeric, the design matrix.
"y": numeric, the response vector.
"z": numeric, the random effect design vector.
"id": an integer vector of cluster ids.
"offset": numeric vector for offset.
"n.trials": an integer vector indicates the sample size of each observation in binomial experiments. Only used for binomial family, otherwise use a vector of 1s.
"regressionParInit": numeric, a vector of initial estimates of regression parameters.
"varStruct": an objact of class "geeVarStruct" with five components: (1) "type": a character string indicating a variance type. When random effect is specified, "type" is specified as "mixedQuad"; (2) "info": an integer vector listing the information of variance design. It contains an indicator for the number of additive terms, the number of unknown scale parameters to be estimated, the number of unknow varaince of the random effect varaibles, number of weights used in the variance, and number of weights used in the variance of random effect variables; (3) "scale": a numeric vector containing unknown scales and fixed scales for variance together with the variance of random effect variables. (4) "data": a numeric vector containing the weights, and the square of covariates of the random effect variables .
"corStruct": an object with eleven components (1) "type": a vector of character strings, one per layer, containing the correlation type for the given layer. This includes "fixed" for fixed design; (2) "nLayer": an integer specifying the number of layers in correlation design; (3) "nParLayer": a vector of integers indicating the number of parameters associated with each layer of correlation structure; (4) "parLayerID": an integers vector of length of the number of parameters used in the correlation design; ; (5) "parInit": a numeric vector of initial values of correlation parameters. This is only used if the estimation.flag for alpha is set to 0; (6) "parMap": a matrix of integers indicating the correlation parameterization. Each matrix entry is either -1, the diagonal, -9 ,not used, or a positive integer, the parameter id for that entry; (7) "layerMap": a matrix of integers indicating the correlation design. The value in each matrix cell, if positive, is the layer id associated with that cell. Otherwise no layer is associated with that cell; (8) "fixed": a null matrix or a correlation matrix used in fixed correlation design or used as a fixed correlation value for negative corrLayerMap entries; (9) "X": a list of two components, "names" and "map" . The "names" contains a vector of character strings listing the names of variables in "data" . The "map" is itself a list of length n.layer, and each component, a vector of positive integers, maps a layer.id to variables in "data" to indicate the usage of variables in the structure of the layer; (10) "data": a list with components of "record.names" and other variables as a column referring to time for "AR" or "ARcont", or for resolving positions within a cluster for each block of an "unstruct" layer. (11) "flags": a list with components of estInitAlpha" indicating whether to estimate the scale and initialize correlation parameters, respectively (1=estimate values, 0=do not estimate values). balanced" indicating a balanced design or longitudinal design respectively. (1=True,0=False), and "cor.once" . A longitudinal design is such that the correlation matrix can be calculated once, and subset as needed for each cluster.
"ksStruct":
"control": A list of control parameters: algorithm, tolerance.reg, tolerance.cor, maxit, trace. When trace=T, information in the iteration process is printed.
gee.misc
a list of miscellaneous information on geeDesign. It includes the correlation design object, cor.design, the initial values, initial, and the names and parameters associated with the design.

DETAILS:

The object is mainly used to specify the argument design in the gee.fit function.

SEE ALSO:

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