Sets/gets the default dictionary used in the function etable, did_means and
coefplot. The dictionaries are used to relabel variables (usually towards a fancier, more
explicit formatting) when exporting them into a Latex table or displaying in graphs. By setting
the dictionary with setFixest_dict, you can avoid providing the argument dict.
Arguments
- dict
A named character vector or a character scalar. E.g. to change my variable named "a" and "b" to (resp.) "$log(a)$" and "$bonus^3$", then use
dict = c(a="$log(a)$", b3="$bonus^3$"). Alternatively you can feed a character scalar containing the dictionary in the form"variable 1: definition \n variable 2: definition". In that case the functionas.dictwill be applied to get a proper dictionary. This dictionary is used in Latex tables or in graphs by the functioncoefplot. If you want to separate Latex rendering from rendering in graphs, use an ampersand first to make the variable specific tocoefplot.- ...
You can add arguments of the form:
variable_name = "Definition". This is an alternative to using a named vector in the argumentdict.- reset
Logical, default is
FALSE. IfTRUE, then the dictionary is reset. Note that the default dictionary always relabels the variable "(Intercept)" in to "Constant". To overwrite it, you need to add "(Intercept)" explicitly in your dictionary.
Details
By default the dictionary only grows. This means that successive calls with not erase the
previous definitions unless the argument reset has been set to TRUE.
The default dictionary is equivalent to having setFixest_dict("(Intercept)" = "Constant"). To
change this default, you need to provide a new definition to "(Intercept)" explicitly.
Examples
data(trade)
est = feols(log(Euros) ~ log(dist_km)|Origin+Destination+Product, trade)
# we export the result & rename some variables
etable(est, dict = c("log(Euros)"="Euros (ln)", Origin="Country of Origin"))
#> est
#> Dependent Var.: Euros (ln)
#>
#> log(dist_km) -2.169*** (0.1542)
#> Fixed-Effects: ------------------
#> Country of Origin Yes
#> Destination Yes
#> Product Yes
#> _________________ __________________
#> S.E.: Clustered by: Country of O..
#> Observations 38,325
#> R2 0.70402
#> Within R2 0.21827
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# If you export many tables, it can be more convenient to use setFixest_dict:
setFixest_dict(c("log(Euros)"="Euros (ln)", Origin="Country of Origin"))
etable(est) # variables are properly relabeled
#> est
#> Dependent Var.: Euros (ln)
#>
#> log(dist_km) -2.169*** (0.1542)
#> Fixed-Effects: ------------------
#> Country of Origin Yes
#> Destination Yes
#> Product Yes
#> _________________ __________________
#> S.E.: Clustered by: Country of O..
#> Observations 38,325
#> R2 0.70402
#> Within R2 0.21827
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# The dictionary only 'grows'
# Here you get the previous two variables + the new one that are relabeled
# Btw you set the dictionary directly using the argument names:
setFixest_dict(Destination = "Country of Destination")
etable(est)
#> est
#> Dependent Var.: Euros (ln)
#>
#> log(dist_km) -2.169*** (0.1542)
#> Fixed-Effects: ------------------
#> Country of Origin Yes
#> Country of Destination Yes
#> Product Yes
#> ______________________ __________________
#> S.E.: Clustered by: Country of O..
#> Observations 38,325
#> R2 0.70402
#> Within R2 0.21827
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# Another way to set a dictionary: with a character string:
# See the help page of as.dict
dict = "log(dist_km): Distance (ln); Product: Type of Good"
setFixest_dict(dict)
etable(est)
#> est
#> Dependent Var.: Euros (ln)
#>
#> Distance (ln) -2.169*** (0.1542)
#> Fixed-Effects: ------------------
#> Country of Origin Yes
#> Country of Destination Yes
#> Type of Good Yes
#> ______________________ __________________
#> S.E.: Clustered by: Country of O..
#> Observations 38,325
#> R2 0.70402
#> Within R2 0.21827
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# And now we reset:
setFixest_dict(reset = TRUE)
etable(est)
#> est
#> Dependent Var.: log(Euros)
#>
#> log(dist_km) -2.169*** (0.1542)
#> Fixed-Effects: ------------------
#> Origin Yes
#> Destination Yes
#> Product Yes
#> _______________ __________________
#> S.E.: Clustered by: Origin
#> Observations 38,325
#> R2 0.70402
#> Within R2 0.21827
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1