# summary.icdglm: Summarizing Output of an EM Algorithm by the Method of... In icdGLM: EM by the Method of Weights for Incomplete Categorical Data in Generlized Linear Models

## Description

This function gives a summary of the output of icdglm. summary.icdglm inherits from summary.glm.

## Usage

 ```1 2``` ```## S3 method for class 'icdglm' summary(object, dispersion = NULL, correlation = FALSE, symbolic.cor = FALSE, ...) ```

## Arguments

 `object` an object of class "icdglm", usually, a result of a call to icdglm. `dispersion` the dispersion parameter for the family used. Either a single numerical value or NULL (the default), when it is inferred from object (see details of summary.glm). `correlation` logical, if TRUE, the correlation matrix of the estimated parameters is returned and printed. `symbolic.cor` logical, if TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers. `...` further arguments passed to or from other methods.

## Value

summary.icdglm returns an object of class "summary.icdglm", a list with components:

• callfunction call of object

• termsthe terms object used.

• familythe component from object

• deviancethe component from object

• aicthe component from object

• df.residualthe residual degrees of freedom of the initial data set

• null.deviancethe component from object

• df.nullthe residual degrees of freedom for the null model.

• iterthe number of iterations in icdglm.fit, component from object

• deviance.residthe deviance residuals: see residuals.glm

• coefficientsthe matrix of coefficients, (corrected) standard errors, t-values and p-values.

• aliasednamed logical vector showing if the original coefficients are aliased.

• dispersioneither the supplied argument or the inferred/estimated dispersion if the latter is NULL.

• dfa 3-vector of the rank of the model and the number of residual degrees of freedom, plus number of coefficients (including aliased ones).

• cov.unscaledthe unscaled (dispersion = 1) estimated covariance matrix of the estimated coefficients.

• cov.scaledditto, scaled by dispersion

• correlation(only if correlation is TRUE) The estimated correlations of the estimated coefficients.

• symbolic.cor(only if correlation is TRUE) The value of the argument symbolic.cor.

## Note

The description of this function is taken from summary.glm apart from a few differences.

`icdglm`, `summary.glm`, `summary`, `glm`