# summary.plm.list

##### Summary for plm objects

The summary method for plm objects generates some more information about estimated plm models.

- Keywords
- regression

##### Usage

```
# S3 method for plm.list
summary(object, ...)
```# S3 method for summary.plm.list
coef(object, eq = NULL, ...)

# S3 method for summary.plm.list
print(
x,
digits = max(3, getOption("digits") - 2),
width = getOption("width"),
...
)

# S3 method for plm
summary(object, vcov = NULL, ...)

# S3 method for summary.plm
print(
x,
digits = max(3, getOption("digits") - 2),
width = getOption("width"),
subset = NULL,
...
)

##### Arguments

- object
an object of class

`"plm"`

,- …
further arguments.

- eq
the selected equation for list objects

- x
an object of class

`"summary.plm"`

,- digits
number of digits for printed output,

- width
the maximum length of the lines in the printed output,

- vcov
a variance--covariance matrix furnished by the user or a function to calculate one (see

**Examples**),- subset
a character or numeric vector indicating a subset of the table of coefficients to be printed for

`"print.summary.plm"`

,

##### Details

The `summary`

method for plm objects (`summary.plm`

) creates an
object of class `c("summary.plm", "plm", "panelmodel")`

that
extends the plm object it is run on with various information about
the estimated model like (inferential) statistics, see
**Value**. It has an associated print method
(`print.summary.plm`

).

##### Value

An object of class `c("summary.plm", "plm", "panelmodel")`

. Some of its elements are carried over from the
associated plm object and described there
(`plm()`

). The following elements are new or changed
relative to the elements of a plm object:

'htest' object: joint test of significance of
coefficients (F or Chi-square test) (robust statistic in case of
supplied argument `vcov`

, see `pwaldtest()`

for details),

a matrix with the estimated coefficients,
standard errors, t--values, and p--values, if argument `vcov`

was
set to non-`NULL`

the standard errors (and t-- and p--values) in
their respective robust variant,

the "regular" variance--covariance matrix of the coefficients (class "matrix"),

only present if argument `vcov`

was set to non-`NULL`

:
the furnished variance--covariance matrix of the coefficients
(class "matrix"),

a named numeric containing the R-squared ("rsq") and the adjusted R-squared ("adjrsq") of the model,

an integer vector with 3 components, (p, n-p, p*), where p is the number of estimated (non-aliased) coefficients of the model, n-p are the residual degrees of freedom (n being number of observations), and p* is the total number of coefficients (incl. any aliased ones).

##### See Also

`plm()`

for estimation of various models; `vcovHC()`

for
an example of a robust estimation of variance--covariance
matrix; `r.squared()`

for the function to calculate R-squared;
`stats::print.power.htest()`

for some information about class
"htest"; `fixef()`

to compute the fixed effects for "within"
(=fixed effects) models and `within_intercept()`

for an
"overall intercept" for such models; `pwaldtest()`

##### Examples

```
# NOT RUN {
data("Produc", package = "plm")
zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
data = Produc, index = c("state","year"))
summary(zz)
# summary with a funished vcov, passed as matrix, as function, and
# as function with additional argument
data("Grunfeld", package = "plm")
wi <- plm(inv ~ value + capital,
data = Grunfeld, model="within", effect = "individual")
summary(wi, vcov = vcovHC(wi))
summary(wi, vcov = vcovHC)
summary(wi, vcov = function(x) vcovHC(x, method = "white2"))
# extract F statistic
wi_summary <- summary(wi)
Fstat <- wi_summary[["fstatistic"]]
# extract estimates and p-values
est <- wi_summary[["coefficients"]][ , "Estimate"]
pval <- wi_summary[["coefficients"]][ , "Pr(>|t|)"]
# print summary only for coefficent "value"
print(wi_summary, subset = "value")
# }
```

*Documentation reproduced from package plm, version 2.2-5, License: GPL (>= 2)*