Used to capture different fixest estimation objects (obtained with femlm, feols or feglm). Note that any other type of element is discarded. Note that you can give a list of fixest objects.

Character scalar. Which kind of standard error should be computed: “standard”, “hetero”, “cluster”, “twoway”, “threeway” or “fourway”? By default if there are clusters in the estimation: se = "cluster", otherwise se = "standard". Note that this argument can be implicitly deduced from the argument cluster.

An object of class dof.type obtained with the function dof. Represents how the degree of freedom correction should be done.You must use the function dof for this argument. The arguments and defaults of the function dof are: adj = TRUE, fixef.K="nested", cluster.adj = TRUE, cluster.df = "conventional", t.df = "conventional", fixef.force_exact=FALSE). See the help of the function dof for details.

Tells how to cluster the standard-errors (if clustering is requested). Can be either a list of vectors, a character vector of variable names, a formula or an integer vector. Assume we want to perform 2-way clustering over var1 and var2 contained in the data.frame base used for the estimation. All the following cluster arguments are valid and do the same thing: cluster = base[, c("var1", "var2")], cluster = c("var1", "var2"), cluster = ~var1+var2. If the two variables were used as clusters in the estimation, you could further use cluster = 1:2 or leave it blank with se = "twoway" (assuming var1 [resp. var2] was the 1st [res. 2nd] cluster). You can interact two variables using ^ with the following syntax: cluster = ~var1^var2 or cluster = "var1^var2".

Can be equal to 2 (default), 1, 1:2 or 2:1. Only used if the object is an IV estimation: defines the stage to which summary should be applied. If stage = 1 and there are multiple endogenous regressors or if stage is of length 2, then an object of class fixest_multi is returned.

A character scalar describing the variable names to be aggregated, it is pattern-based. All variables that match the pattern will be aggregated. It must be of the form "(root)", the parentheses must be there and the resulting variable name will be "root". You can add another root with parentheses: "(root1)regex(root2)", in which case the resulting name is "root1::root2". To name the resulting variable differently you can pass a named vector: c("name" = "pattern") or c("name" = "pattern(root2)"). It's a bit intricate sorry, please see the examples.

A function to be used to compute the standard-errors of each fixest object. You can pass extra arguments to this function using the argument .vcov_args. See the example.

A list containing arguments to be passed to the function .vcov.

Integer or character scalar. Default is 4 and represents the number of significant digits to be displayed for the coefficients and standard-errors. To apply rounding instead of significance use, e.g., digits = "r3" which will round at the first 3 decimals. If character, it must be of the form "rd" or "sd" with d a digit (r is for round and s is for significance). For the number of digits for the fit statistics, use digits.stats. Note that when significance is used it does not exactly display the number of significant digits: see details for its exact meaning.

Integer or character scalar. Default is 5 and represents the number of significant digits to be displayed for the fit statistics. To apply rounding instead of significance use, e.g., digits = "r3" which will round at the first 3 decimals. If character, it must be of the form "rd" or "sd" with d a digit (r is for round and s is for significance). Note that when significance is used it does not exactly display the number of significant digits: see details for its exact meaning.

Logical: whether the results should be a data.frame or a Latex table. By default, this argument is TRUE if the argument file (used for exportation) is not missing; it is equal to FALSE otherwise.

A character vector or a one sided formula (both with only lowercase letters). A vector listing which fit statistics to display. The valid types are 'n', 'll', 'aic', 'bic' and r2 types like 'r2', 'pr2', 'war2', etc (see all valid types in r2). Also accepts valid types from the function fitstat. The default value depends on the models to display. Example of use: fitstat=c('n', 'cor2', 'ar2', 'war2'), or fitstat=~n+cor2+ar2+war2 using a formula. You can use the dot to refer to default values: ~ . + ll would add the log-likelihood to the default fit statistics.

(Tex only.) Character scalar. The title of the Latex table.

One of "se" (default), "tstat" or "confint". The statistic to report for each coefficient: the standard-error, the t-statistics or the confidence interval. You can adjust the confidence interval with the argument ci.

Level of the confidence interval, defaults to 0.95. Only used if coefstat = confint.

(Tex only.) Logical, default is TRUE. Should the standard-errors be displayed below the coefficients?

Character vector. This element is used to display only a subset of variables. This should be a vector of regular expressions (see 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). 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 = "!Intercept" means: every variable that does not contain “Intercept” is kept). See details.

Character vector. This element is used if some variables are not to be displayed. This should be a vector of regular expressions (see 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). 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 = "!Intercept" means: every variable that does not contain “Intercept” is dropped). See details.

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 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). 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 = "!Intercept" means: every variable that does not contain “Intercept” goes first). See details.

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..

A character scalar. If provided, the Latex (or data frame) table will be saved in a file whose path is file. If you provide this argument, then a Latex table will be exported, to export a regular data.frame, use argument tex = FALSE.

Logical, default is FALSE. Only used if option file is used. Should the exported table be written in a new file that replaces any existing file?

Logical, default is missing. Should the convergence state of the algorithm be displayed? By default, convergence information is displayed if at least one model did not converge.

Named numeric vector, used to provide the significance codes with respect to the p-value of the coefficients. Default is c("***"=0.01, "**"=0.05, "*"=0.10) for a Latex table and c("***"=0.001, "**"=0.01, "*"=0.05, "."=0.10) for a data.frame (to conform with R's default). To suppress the significance codes, use signifCode=NA or signifCode=NULL. Can also be equal to "letters", then the default becomes c("a"=0.01, "b"=0.05, "c"=0.10).

(Tex only.) Character scalar. The label of the Latex table.

(Tex only.) Logical. By default, if the argument title or label is provided, it is set to TRUE. Otherwise, it is set to FALSE.

Character vector or list. The elements should be of length 1 or of the same length as the number of models. If a list, the names of the list will be displayed on the leftmost column. By default it is equal to list("auto") which means that if the object is a split sample estimation, the sample will be automatically added as a sub-title.

(Tex only.) Logical, default is FALSE. If TRUE and fixed-effects were used in the models, then the number of "individuals" per fixed-effect dimension is also displayed.

Logical, default is TRUE. Only used if fixef_sizes = TRUE. If TRUE, the fixed-effects sizes will be displayed in parentheses instead of in a separate line if there is no ambiguity (i.e. if the size is constant across models).

Logical, default is TRUE. If FALSE, then factor variables are displayed as fixed-effects and no coefficient is shown.

Logical, default is missing. Whether to display the families of the models. By default this line is displayed when at least two models are from different families.

(Tex only.) Integer, default is -5. A coefficient whose value is below 10**(powerBelow+1) is written with a power in Latex. For example 0.0000456 would be written 4.56$\times 10^{-5}$ by default. Setting powerBelow = -6 would lead to 0.00004 in Latex.

(Tex only.) Character scalar, defaults to " $\times$ ". When the estimation contains interactions, then the variables names (after aliasing) are combined with this argument. For example: if dict = c(x1="Wind", x2="Rain") and you have the following interaction x1:x2, then it will be renamed (by default) Wind $\times$ Rain – using interaction.combine = "*" would lead to Wind*Rain.

Logical, default is TRUE. Whether a first line containing the dependent variables should be shown.

An object created by the function style.tex. It represents the style of the Latex table, see the documentation of style.tex.

An object created by the function style.df. It represents the style of the data frame returned (if tex = FALSE), see the documentation of style.df.

(Tex only.) Character vector. If provided, a "notes" section will be added at the end right after the end of the table, containing the text of this argument. Note that if it is a vector, it will be collapsed with new lines.

A list. The list elements should be vectors of regular expressions. For each elements of this list: A new line in the table is created, all variables that are matched by the regular expressions are discarded (same effect as the argument drop) and TRUE or FALSE will appear in the model cell, depending on whether some of the previous variables were found in the model. Example: group=list("Controls: personal traits"=c("gender", "height", "weight")) will create an new line with "Controls: personal traits" in the leftmost cell, all three variables gender, height and weight are discared, TRUE appearing in each model containing at least one of the three variables (the style of TRUE/FALSE is governed by the argument yesNo). You can control the style with the title and where keywords in curly brackets. For example group=list("{title:Controls; where:stats}Personal traits"=c("gender", "height", "weight")) will add an extra line right before with "Control" written in it, and the group information will appear after the statistics. The keyword where can be equal to either var (default), fixef or stats. Starting the list name with an underscore is equivalent to adding "{where:stats}": eg list("_Controls"="x") is equivalent to list("{where:stats}Controls"="x").

A list. The list elements should be either a single logical or a vector of the same length as the number of models. For each elements of this list: A new line in the table is created, the list name being the row name and the vector being the content of the cells. Example: extraline=list("Sub-sample"=c("<20 yo", "all", ">50 yo")) will create an new line with "Sub-sample" in the leftmost cell, the vector filling the content of the cells for the three models. You can control the style with the title and where keywords in curly brackets. For example extraline=list("{title:Sub-sample; where:stats}By age"=c("<20 yo", "all", ">50 yo")) will add an extra line right before with "Sub-sample" written in it, and the extraline information will appear after the statistics section. The keyword where can be equal to either var (default), fixef or stats. Starting the list name with an underscore is equivalent to adding "{where:stats}": eg list("_Controls"=TRUE) is equivalent to list("{where:stats}Controls"=TRUE).

(Tex only.) Character string giving the position of the float in Latex. Default is "htbp". It must consist of only the characters 'h', 't', 'b', 'p', 'H' and '!'. Reminder: h: here; t: top; b: bottom; p: float page; H: definitely here; !: prevents Latex to look for other positions. Note that it can be equal to the empty string (and you'll get the default placement).

Character vector which can be of length 0 (i.e. equal to NULL). Can contain the values "fixef", "slopes" or "stats". It would drop, respectively, the fixed-effects section, the variables with varying slopes section or the fit statistics section.

Character vector, default is c("", " square", " cube"). When raw polynomials (x^2, etc) are used, the variables are automatically renamed and poly_dict rules the display of the power. For powers greater than the number of elements of the vector, the value displayed is $^{pow}$ in Latex and ^ pow in the R console.

A function that will postprocess the character vector defining the latex table. Only when tex = TRUE. By default it is equal to NULL, meaning that there is no postprocessing. When tex = FALSE, see the argument postprocess.df. See details.

A function that will postprocess.tex the resulting data.frame. Only when tex = FALSE. By default it is equal to NULL, meaning that there is no postprocessing. When tex = TRUE, see the argument postprocess.tex.

Character scalar, default is "__var__". Only used in the presence of IVs. By default the endogenous regressors are named fit_varname in the second stage. The format of the endogenous regressor to appear in the table is governed by fit_format. For instance, by default, the prefix "fit_" is removed, leading to only varname to appear. If fit_format = "$\\hat{__var__}$", then "$\hat{varname}$" will appear in the table.

(setFixest_etable only.) Logical, default is FALSE. If TRUE, this will reset all the default values that were already set by the user in previous calls.