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nlme (version 3.1-68.1)

summary.lmList: Summarize an lmList Object

Description

The summary.lm method is applied to each lm component of object to produce summary information on the individual fits, which is organized into a list of summary statistics. The returned object is suitable for printing with the print.summary.lmList method.

Usage

## S3 method for class 'lmList':
summary(object, pool, \dots)

Arguments

object
an object inheriting from class lmList, representing a list of lm fitted objects.
pool
an optional logical value indicating whether a pooled estimate of the residual standard error should be used. Default is attr(object, "pool").
...
some methods for this generic require additional arguments. None are used in this method.

Value

  • a list with summary statistics obtained by applying summary.lm to the elements of object, inheriting from class summary.lmList. The components of value are:
  • calla list containing an image of the lmList call that produced object.
  • coefficientsa three dimensional array with summary information on the lm coefficients. The first dimension corresponds to the names of the object components, the second dimension is given by "Value", "Std. Error", "t value", and "Pr(>|t|)", corresponding, respectively, to the coefficient estimates and their associated standard errors, t-values, and p-values. The third dimension is given by the coefficients names.
  • correlationa three dimensional array with the correlations between the individual lm coefficient estimates. The first dimension corresponds to the names of the object components. The third dimension is given by the coefficients names. For each coefficient, the rows of the associated array give the correlations between that coefficient and the remaining coefficients, by lm component.
  • cov.unscaleda three dimensional array with the unscaled variances/covariances for the individual lm coefficient estimates (giving the estimated variance/covariance for the coefficients, when multiplied by the estimated residual errors). The first dimension corresponds to the names of the object components. The third dimension is given by the coefficients names. For each coefficient, the rows of the associated array give the unscaled covariances between that coefficient and the remaining coefficients, by lm component.
  • dfan array with the number of degrees of freedom for the model and for residuals, for each lm component.
  • df.residualthe total number of degrees of freedom for residuals, corresponding to the sum of residuals df of all lm components.
  • fstatisticsan array with the F test statistics and corresponding degrees of freedom, for each lm component.
  • poolthe value of the pool argument to the function.
  • r.squareda vector with the multiple R-squared statistics for each lm component.
  • residualsa list with components given by the residuals from individual lm fits.
  • RSEthe pooled estimate of the residual standard error.
  • sigmaa vector with the residual standard error estimates for the individual lm fits.
  • termsthe terms object used in fitting the individual lm components.

See Also

lmList

Examples

Run this code
fm1 <- lmList(distance ~ age | Subject, Orthodont)
summary(fm1)

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