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plot methods for fixest and fixest_multi objects

Source: R/coefplot.R
plot.fixest.Rd

Plot method reporting the coefficient estimates and their confidence intervals. This is a wrapper to the more complete functions coefplot and iplot.

Usage

# S3 method for class 'fixest'
plot(
  x,
  vcov = NULL,
  add = FALSE,
  horiz = FALSE,
  do_iplot = NULL,
  zero = TRUE,
  zero.par = TRUE,
  dict = NULL,
  keep = NULL,
  drop = NULL,
  order = NULL,
  ci.width = "1%",
  ci_level = 0.95,
  plot_prms = list(),
  ylim = NULL,
  xlim = NULL,
  pch = c(20, 17, 15, 21, 24, 22),
  col = 1:8,
  cex = 1,
  lty = 1,
  lwd = 1,
  pt.pch = pch,
  pt.bg = NULL,
  pt.cex = cex,
  pt.col = col,
  ci.col = col,
  pt.lwd = lwd,
  ci.lwd = lwd,
  ci.lty = lty,
  main = "Effect on __depvar__",
  value.lab = "Estimate and __ci__ Conf. Int.",
  ylab = NULL,
  xlab = NULL,
  sub = NULL,
  ...
)

Arguments

x

A fixest estimation, for example from feols.

vcov

Versatile argument to specify the VCOV. In general, it is either a character scalar equal to a VCOV type, either a formula of the form: vcov_type ~ variables. The VCOV types implemented are: "iid", "hetero" (or "HC1"), "cluster", "twoway", "NW" (or "newey_west"), "DK" (or "driscoll_kraay"), and "conley". It also accepts object from vcov_cluster, vcov_NW, NW, vcov_DK, DK, vcov_conley and conley. It also accepts covariance matrices computed externally. Finally it accepts functions to compute the covariances. See the vcov documentation in the vignette.

You can pass several VCOVs (as above) if you nest them into a list. If the number of VCOVs equals the number of models, eahc VCOV is mapped to the appropriate model. If there is one model and several VCOVs, or if the first element of the list is equal to "each" or "times", then the estimations will be replicated and the results for each estimation and each VCOV will be reported.

add

Default is FALSE, if the intervals are to be added to an existing graph. Note that if it is the case, then the argument x MUST be numeric.

horiz

A logical scalar, default is FALSE. Whether to display the confidence intervals horizontally instead of vertically.

do_iplot

Logical, default is FALSE. For internal use only. If TRUE, then iplot is run instead of coefplot.

zero

Logical scalar, default is TRUE. Whether the 0 should be displayed in the limits of the y-axis. Note that you can set how this zero line looks like with the argument zero.par.

zero.par

A named list of graphical parameters or a logical scalar. This argument is a list containing the graphical parameters used to draw the zero-line. The default value is list(col = "black", lwd = 1) (it's the same if TRUE). Set it to FALSE to turn off the special emphasis of the zero line. You can add any graphical parameter that will be passed to graphics::abline. Example: zero.par = list(col = "darkblue", lwd = 3).

dict

A named character vector or a logical scalar. It changes the original variable names to the ones contained in the dictionary. E.g. to change the variables named a and b3 to (resp.) “$log(a)$” and to “$bonus^3$”, use dict=c(a="$log(a)$",b3="$bonus^3$"). By default, it is equal to getFixest_dict(), a default dictionary which can be set with setFixest_dict. You can use dict = FALSE to disable it. By default dict modifies the entries in the global dictionary, to disable this behavior, use "reset" as the first element (ex: dict=c("reset", mpg="Miles per gallon")).

keep

Character vector. This element is used to display only a subset of variables. This should be a vector of regular expressions (see base::regex help for more info). Each variable satisfying any of the regular expressions will be kept. This argument is applied post aliasing (see argument dict). Use the argument keep_raw for the same effect before aliasing.

Example: you have the variable x1 to x55 and want to display only x1 to x9, then you could use keep = "x[[:digit:]]$". If the first character is an exclamation mark, the effect is reversed (e.g. keep = "!Constant" means: every variable that does not contain “Constant” is kept). See details.

drop

Character vector. This element is used if some variables are not to be displayed. This should be a vector of regular expressions (see base::regex help for more info). Each variable satisfying any of the regular expressions will be discarded. This argument is applied post aliasing (see argument dict). Use the argument drop_raw for the same effect before aliasing.

Example: you have the variable x1 to x55 and want to display only x1 to x9, then you could use drop = "x[[:digit:]]{2}". If the first character is an exclamation mark, the effect is reversed (e.g. drop = "!Constant" means: every variable that does not contain “Constant” is dropped). See details.

order

Character vector. This element is used if the user wants the variables to be ordered in a certain way. This should be a vector of regular expressions (see base::regex help for more info). The variables satisfying the first regular expression will be placed first, then the order follows the sequence of regular expressions. This argument is applied post aliasing (see argument dict). Use the argument order_raw for the same effect before aliasing.

Example: you have the following variables: month1 to month6, then x1 to x5, then year1 to year6. If you want to display first the x's, then the years, then the months you could use: order = c("x", "year"). If the first character is an exclamation mark, the effect is reversed (e.g. order = "!Constant" means: every variable that does not contain “Constant” goes first). See details.

ci.width

The width of the extremities of the confidence intervals. Default is 0.1.

ci_level

Scalar between 0 and 1: the level of the CI. By default it is equal to 0.95.

plot_prms

A named list. It may contain additionnal parameters to be passed to the plot.

ylim

Numeric vector of length 2 which gives the limits of the plotting region for the y-axis. The default is NULL, which means that it is automatically defined. Use the argument ylim.add to simply increase or decrese the default limits.

xlim

Numeric vector of length 2 which gives the limits of the plotting region for the x-axis. The default is NULL, which means that it is automatically defined. Use the argument xlim.add to simply increase or decrese the default limits.

pch

The patch of the coefficient estimates. Default is 1 (circle). This is an alias to tha argument pt.pch.

col

The color of the points and the confidence intervals. Default is 1 ("black"). Note that you can set the colors separately for each of them with pt.col and ci.col.

cex

Numeric, default is 1. Expansion factor for the points

lty

The line type of the confidence intervals. Default is 1. This is an alias to the argument ci.lty.

lwd

General line with. Default is 1.

pt.pch

The patch of the coefficient estimates. Default is 1 (circle).

pt.bg

The background color of the point estimate (when the pt.pch is in 21 to 25). Defaults to NULL.

pt.cex

The size of the coefficient estimates. Default is the other argument cex.

pt.col

The color of the coefficient estimates. Default is equal to the argument col.

ci.col

The color of the confidence intervals. Default is equal to the argument col.

pt.lwd

The line width of the coefficient estimates. Default is equal to the other argument lwd.

ci.lwd

The line width of the confidence intervals. Default is equal to the other argument lwd.

ci.lty

The line type of the confidence intervals. Default is 1.

main

The title of the plot. Default is "Effect on __depvar__". You can use the special variable __depvar__ to set the title (useful when you set the plot default with setFixest_coefplot).

value.lab

The label to appear on the side of the coefficient values. If horiz = FALSE, the label appears in the y-axis. If horiz = TRUE, then it appears on the x-axis. The default is equal to "Estimate and __ci__ Conf. Int.", with __ci__ a special variable giving the value of the confidence interval.

ylab

The label of the y-axis, default is NULL. Note that if horiz = FALSE, it overrides the value of the argument value.lab.

xlab

The label of the x-axis, default is NULL. Note that if horiz = TRUE, it overrides the value of the argument value.lab.

sub

A subtitle, default is NULL.

...

Other arguments to be passed to coefplot.

Value

It returns invisibly the data used to create the graph.

Details

By default plot.fixest runs coefplot unless the estimation includes the function sunab, in which case it uses iplot.

The switch to iplot can be made with the argument do_iplot = TRUE.

Arguments keep, drop and order

The arguments keep, drop and order use regular expressions. If you are not aware of regular expressions, I urge you to learn it, since it is an extremely powerful way to manipulate character strings (and it exists across most programming languages).

For example drop = "Wind" would drop any variable whose name contains "Wind". Note that variables such as "Temp:Wind" or "StrongWind" do contain "Wind", so would be dropped. To drop only the variable named "Wind", you need to use drop = "^Wind$" (with "^" meaning beginning, resp. "$" meaning end, of the string => this is the language of regular expressions).

Although you can combine several regular expressions in a single character string using pipes, drop also accepts a vector of regular expressions.

You can use the special character "!" (exclamation mark) to reverse the effect of the regular expression (this feature is specific to this function). For example drop = "!Wind" would drop any variable that does not contain "Wind".

By default, the regular expressions are checked against the variables after they have been renamed with the dictionary (argument dict). You can use the *_raw versions of drop/keep/order to apply the regular expressions on the original variable names. Note that alternatively you can use the special character "%" (percentage) at the beginning of drop/keep/order's regular expressions to refer to the original variable name. For example, you have a variable named "Month6", and use a dictionary dict = c(Month6="June"). Thus the variable will be displayed as "June". If you want to delete that variable, you can use either drop="June", drop_raw="Month6", or drop="%Month6".

The argument order takes in a vector of regular expressions, the order will follow the elements of this vector. The vector gives a list of priorities, on the left the elements with highest priority. For example, order = c("Wind", "!Inter", "!Temp") would give highest priorities to the variables containing "Wind" (which would then appear first), second highest priority is the variables not containing "Inter", last, with lowest priority, the variables not containing "Temp". If you had the following variables: (Intercept), Temp:Wind, Wind, Temp you would end up with the following order: Wind, Temp:Wind, Temp, (Intercept).

Examples


#
# Single estimation
#

est = feols(Ozone ~ Temp + Solar.R, airquality)
#> NOTE: 42 observations removed because of NA values (LHS: 37, RHS: 7).
plot(est)


# focus only on the variables
plot(est, drop = "Cons")


#
# Multiple estimations
#

est_mult = feols(Ozone ~ csw(Temp, Solar.R, Wind), airquality)
#> NOTE: 37 observations removed because of NA values (LHS: 37).
#>       |-> this msg only concerns the variables common to all estimations
plot(est_mult, drop = "Const")


#
# DiD estimation: Sun & Abraham
#

data(base_stagg)
# The DiD estimation
res_sunab = feols(y ~ x1 + sunab(year_treated, year) | id + year, base_stagg)
plot(res_sunab)