summary.lmList.RdThe 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.
# S3 method for class 'lmList'
summary(object, pool, ...)an object inheriting from class "lmList", representing
a list of lm fitted objects.
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.
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:
a list containing an image of the lmList call that
produced object.
a 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.
a 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.
a 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.
an array with the number of degrees of freedom for the model
and for residuals, for each lm component.
the total number of degrees of freedom for
residuals, corresponding to the sum of residuals df of all lm
components.
an array with the F test statistics and
corresponding degrees of freedom, for each lm component.
the value of the pool argument to the function.
a vector with the multiple R-squared statistics for
each lm component.
a list with components given by the residuals from
individual lm fits.
the pooled estimate of the residual standard error.
a vector with the residual standard error estimates for
the individual lm fits.
the terms object used in fitting the individual lm
components.
fm1 <- lmList(distance ~ age | Subject, Orthodont)
summary(fm1)
#> Call:
#> Model: distance ~ age | Subject
#> Data: Orthodont
#>
#> Coefficients:
#> (Intercept)
#> Estimate Std. Error t value Pr(>|t|)
#> M16 16.95 3.288173 5.1548379 3.695247e-06
#> M05 13.65 3.288173 4.1512411 1.181678e-04
#> M02 14.85 3.288173 4.5161854 3.458934e-05
#> M11 20.05 3.288173 6.0976106 1.188838e-07
#> M07 14.95 3.288173 4.5465974 3.116705e-05
#> M08 19.75 3.288173 6.0063745 1.665712e-07
#> M03 16.00 3.288173 4.8659237 1.028488e-05
#> M12 13.25 3.288173 4.0295930 1.762580e-04
#> M13 2.80 3.288173 0.8515366 3.982319e-01
#> M14 19.10 3.288173 5.8086964 3.449588e-07
#> M09 14.40 3.288173 4.3793313 5.509579e-05
#> M15 13.50 3.288173 4.1056231 1.373664e-04
#> M06 18.95 3.288173 5.7630783 4.078189e-07
#> M04 24.70 3.288173 7.5117696 6.081644e-10
#> M01 17.30 3.288173 5.2612799 2.523621e-06
#> M10 21.25 3.288173 6.4625549 3.065505e-08
#> F10 13.55 3.288173 4.1208291 1.306536e-04
#> F09 18.10 3.288173 5.5045761 1.047769e-06
#> F06 17.00 3.288173 5.1700439 3.499774e-06
#> F01 17.25 3.288173 5.2460739 2.665260e-06
#> F05 19.60 3.288173 5.9607565 1.971127e-07
#> F07 16.95 3.288173 5.1548379 3.695247e-06
#> F02 14.20 3.288173 4.3185072 6.763806e-05
#> F08 21.45 3.288173 6.5233789 2.443813e-08
#> F03 14.40 3.288173 4.3793313 5.509579e-05
#> F04 19.65 3.288173 5.9759625 1.863600e-07
#> F11 18.95 3.288173 5.7630783 4.078189e-07
#> age
#> Estimate Std. Error t value Pr(>|t|)
#> M16 0.550 0.2929338 1.8775576 6.584707e-02
#> M05 0.850 0.2929338 2.9016799 5.361639e-03
#> M02 0.775 0.2929338 2.6456493 1.065760e-02
#> M11 0.325 0.2929338 1.1094659 2.721458e-01
#> M07 0.800 0.2929338 2.7309929 8.511442e-03
#> M08 0.375 0.2929338 1.2801529 2.059634e-01
#> M03 0.750 0.2929338 2.5603058 1.328807e-02
#> M12 1.000 0.2929338 3.4137411 1.222240e-03
#> M13 1.950 0.2929338 6.6567951 1.485652e-08
#> M14 0.525 0.2929338 1.7922141 7.870160e-02
#> M09 0.975 0.2929338 3.3283976 1.577941e-03
#> M15 1.125 0.2929338 3.8404587 3.247135e-04
#> M06 0.675 0.2929338 2.3042752 2.508117e-02
#> M04 0.175 0.2929338 0.5974047 5.527342e-01
#> M01 0.950 0.2929338 3.2430540 2.030113e-03
#> M10 0.750 0.2929338 2.5603058 1.328807e-02
#> F10 0.450 0.2929338 1.5361835 1.303325e-01
#> F09 0.275 0.2929338 0.9387788 3.520246e-01
#> F06 0.375 0.2929338 1.2801529 2.059634e-01
#> F01 0.375 0.2929338 1.2801529 2.059634e-01
#> F05 0.275 0.2929338 0.9387788 3.520246e-01
#> F07 0.550 0.2929338 1.8775576 6.584707e-02
#> F02 0.800 0.2929338 2.7309929 8.511442e-03
#> F08 0.175 0.2929338 0.5974047 5.527342e-01
#> F03 0.850 0.2929338 2.9016799 5.361639e-03
#> F04 0.475 0.2929338 1.6215270 1.107298e-01
#> F11 0.675 0.2929338 2.3042752 2.508117e-02
#>
#> Residual standard error: 1.31004 on 54 degrees of freedom
#>