etable: Estimations table (export the results of multiples... In fixest: Fast Fixed-Effects Estimations

Description

Aggregates the results of multiple estimations and displays them in the form of either a Latex table or a data.frame.

Usage

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 etable( ..., se = NULL, dof = NULL, cluster = NULL, stage = 2, agg = NULL, .vcov, .vcov_args = NULL, digits = 4, digits.stats = 5, tex, fitstat, title, coefstat = "se", ci = 0.95, sdBelow = NULL, keep, drop, order, dict, file, replace = FALSE, convergence, signifCode, label, float, subtitles = list("auto"), fixef_sizes = FALSE, fixef_sizes.simplify = TRUE, keepFactors = TRUE, family, powerBelow = -5, interaction.combine = " $\\times$ ", depvar = TRUE, style.tex = NULL, style.df = NULL, notes = NULL, group = NULL, extraline = NULL, fixef.group = NULL, placement = "htbp", drop.section = NULL, poly_dict = c("", " square", " cube"), postprocess.tex = NULL, postprocess.df = NULL, fit_format = "__var__", coef.just = NULL ) setFixest_etable( digits = 4, digits.stats = 5, fitstat, coefstat = c("se", "tstat", "confint"), ci = 0.95, sdBelow = TRUE, keep, drop, order, dict, signifCode, float, fixef_sizes = FALSE, fixef_sizes.simplify = TRUE, family, powerBelow = -5, interaction.combine = " $\\times$ ", depvar, style.tex = NULL, style.df = NULL, notes = NULL, group = NULL, extraline = NULL, fixef.group = NULL, placement = "htbp", drop.section = NULL, postprocess.tex = NULL, postprocess.df = NULL, fit_format = "__var__", reset = FALSE ) getFixest_etable() esttable( ..., se = NULL, dof = NULL, cluster = NULL, stage = 2, agg = NULL, .vcov, .vcov_args = NULL, digits = 4, digits.stats = 5, fitstat, coefstat = "se", ci = 0.95, sdBelow = NULL, keep, drop, order, dict, file, replace = FALSE, convergence, signifCode, subtitles = list("auto"), fixef_sizes = FALSE, fixef_sizes.simplify = TRUE, keepFactors = TRUE, family, powerBelow = -5, interaction.combine = " $\\times$ ", depvar = TRUE, style.df = NULL, group = NULL, extraline = NULL, fixef.group = NULL, drop.section = NULL, poly_dict = c("", " square", " cube"), postprocess.df = NULL, fit_format = "__var__", coef.just = NULL ) esttex( ..., se = NULL, dof = NULL, cluster = NULL, stage = 2, agg = NULL, .vcov, .vcov_args = NULL, digits = 4, digits.stats = 5, fitstat, title, coefstat = "se", ci = 0.95, sdBelow = NULL, keep, drop, order, dict, file, replace = FALSE, convergence, signifCode, label, float, subtitles = list("auto"), fixef_sizes = FALSE, fixef_sizes.simplify = TRUE, keepFactors = TRUE, family, powerBelow = -5, interaction.combine = " $\\times$ ", depvar = TRUE, style.tex = NULL, notes = NULL, group = NULL, extraline = NULL, fixef.group = NULL, placement = "htbp", drop.section = NULL, poly_dict = c("", " square", " cube"), postprocess.tex = NULL, fit_format = "__var__" ) 

 ... 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. se 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. dof 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. cluster 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". stage 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. agg 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. .vcov 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. .vcov_args A list containing arguments to be passed to the function .vcov. digits 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. digits.stats 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. tex 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. fitstat 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. title (Tex only.) Character scalar. The title of the Latex table. coefstat 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. ci Level of the confidence interval, defaults to 0.95. Only used if coefstat = confint. sdBelow Logical or NULL (default). Should the standard-errors be displayed below the coefficients? If NULL, then this is TRUE for Latex and FALSE otherwise. keep 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:]]$". If the first character is an exclamation mark, the effect is reversed (e.g. keep = "!Intercept" means: every variable that does not contain “Intercept” is kept). See details. drop Character vector. This element is used if some variables are not to be displayed. This should be a vector of regular expressions (see regex help for more info). Each variable satisfying any of the regular expressions will be discarded. This argument is applied post aliasing (see argument dict). Example: you have the variable x1 to x55 and want to display only x1 to x9, then you could use drop = "x[[:digit:]]{2}". If the first character is an exclamation mark, the effect is reversed (e.g. drop = "!Intercept" means: every variable that does not contain “Intercept” is dropped). See details. order Character vector. This element is used if the user wants the variables to be ordered in a certain way. This should be a vector of regular expressions (see regex help for more info). The variables satisfying the first regular expression will be placed first, then the order follows the sequence of regular expressions. This argument is applied post aliasing (see argument dict). Example: you have the following variables: month1 to month6, then x1 to x5, then year1 to year6. If you want to display first the x's, then the years, then the months you could use: order = c("x", "year"). If the first character is an exclamation mark, the effect is reversed (e.g. order = "!Intercept" means: every variable that does not contain “Intercept” goes first). See details. dict A named character vector or a logical scalar. It changes the original variable names to the ones contained in the dictionary. E.g. to change the variables named a and b3 to (resp.) “$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.. file 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. replace 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? convergence 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. signifCode 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). label (Tex only.) Character scalar. The label of the Latex table. float (Tex only.) Logical. By default, if the argument title or label is provided, it is set to TRUE. Otherwise, it is set to FALSE. subtitles 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. fixef_sizes (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. fixef_sizes.simplify 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). keepFactors Logical, default is TRUE. If FALSE, then factor variables are displayed as fixed-effects and no coefficient is shown. family 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. powerBelow (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. interaction.combine (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. depvar Logical, default is TRUE. Whether a first line containing the dependent variables should be shown. style.tex An object created by the function style.tex. It represents the style of the Latex table, see the documentation of style.tex. style.df 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. notes (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. group 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 discarded, 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 placement of the new row by using 1 or 2 special characters at the start of the row name. The meaning of these special characters are: 1) "^": 1st, "_": last, row; 2) "^": coef., "-": fixed-effect, "_": stats, section. For example: group=list("_Controls"=stuff) will place the line last in the stats sections, and using group=list("^_Controls"=stuff) will make the row appear first in the stats section. For details, see the dedicated section. extraline A list or a one sided formula. The list elements should be either a logical scalar,a vector of the same length as the number of models, or a function. This argument can be many things, please have a look at the dedicated help section; a simplified description follows. 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 placement of the new row by using 1 or 2 special characters at the start of the row name. The meaning of these special characters are: 1) "^": 1st, "_": last, row; 2) "^": coef., "-": fixed-effect, "_": stats, section. For example: group=list("_Controls"=stuff) will place the line last in the stats sections, and using group=list("^_Controls"=stuff) will make the row appear first in the stats section. For details, see the dedicated section. fixef.group Logical scalar or list (default is NULL). If equal to TRUE, then all fixed-effects always appearing jointly in models will be grouped in one row. If a list, its elements must be character vectors of regular expressions and the list names will be the row names. For ex. fixef.group=list("Dates fixed-effects"="Month|Day") will remove the "Month" and "Day" fixed effects from the display and replace them with a single row named "Dates fixed-effects". You can monitor the placement of the new row with the special characters telling where to place the row within a section: "^" (first), or "_" (last); and in which section it should appear: "^" (coef.), "-" (fixed-effects), or "_" (stat.). These two special characters must appear first in the row names. Please see the dedicated section. placement (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). drop.section 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. poly_dict 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. postprocess.tex 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. postprocess.df 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. fit_format 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. coef.just (DF only.) Either ".", "(", "l", "c" or "r", default is NULL. How the coefficients should be justified. If NULL then they are right aligned if sdBelow = FALSE and aligned to the dot if sdBelow = TRUE. The keywords stand respectively for dot-, parenthesis-, left-, center- and right-aligned. reset (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. Details The function esttex is equivalent to the function etable with argument tex = TRUE. The function esttable is equivalent to the function etable with argument tex = FALSE. You can permanently change the way your table looks in Latex by using setFixest_etable. The following vignette gives an example as well as illustrates how to use the style and postprocessing functions: Exporting estimation tables. When the argument postprocessing.tex is not missing, two additional tags will be included in the character vector returned by etable: "%start:tab\n" and "%end:tab\n". These can be used to identify the start and end of the tabular and are useful to insert code within the table environment. Value If tex = TRUE, the lines composing the Latex table are returned invisibly while the table is directly prompted on the console. If tex = FALSE, the data.frame is directly returned. If the argument file is not missing, the data.frame is printed and returned invisibly. Functions • esttable: Exports the results of multiple fixest estimations in a Latex table. • esttex: Exports the results of multiple fixest estimations in a Latex table. How does digits handle the number of decimals displayed? The default display of decimals is the outcome of an algorithm. Let's take the example of digits = 3 which "kind of" requires 3 significant digits to be displayed. For numbers greater than 1 (in absolute terms), their integral part is always displayed and the number of decimals shown is equal to digits minus the number of digits in the integral part. This means that 12.345 will be displayed as 12.3. If the number of decimals should be 0, then a single decimal is displayed to suggest that the number is not whole. This means that 1234.56 will be displayed as 1234.5. Note that if the number is whole, no decimals are shown. For numbers lower than 1 (in absolute terms), the number of decimals displayed is equal to digits except if there are only 0s in which case the first significant digit is shown. This means that 0.01234 will be displayed as 0.012 (first rule), and that 0.000123 will be displayed as 0.0001 (second rule). 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". You can use the special character "%" (percentage) to make reference to the original variable name instead of the aliased 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", or drop="%Month6" (which makes reference to its original name). 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). The argument extraline The argument extraline adds well... extra lines to the table. It accepts either a list, or a one-sided formula. If a one-sided formula: then the elements in the formula must represent either extraline macros, either fit statistics (i.e. valid types of the function fitstat). One new line will be added for each element of the formula, they will be appended right after the coefficients. To register extraline macros, you must first register them in extraline_register. If a list: then the elements must be either: a) a logical scalar, b) a vector of the same length as the number of models, c) a function to be applied to each model and which returns a scalar, or d) a one-sided formula of extraline macros (registered with extraline_register) or valid fitstat types. When a list, the elements of type a), b) and c) must have a name! Example: extraline = list("Controls" = TRUE) is good, extraline = list(TRUE) is bad. The name for element of type d) is optional. Example: extraline = list("^^My F-stat" = ~f) will add the row named "My F-stat" on top of the coefficients (for the placement, see the dedicated section), while extraline = list(~f) will add the F-stat row with its default name ("F-test") at its default placement (below the coefficients). You can combine elements in the list, so that the following extraline = list(~r2, "Controls" = TRUE), ~f+ivf is valid. Controlling the placement of extra lines The arguments group, extraline and fixef.group allow to add customized lines in the table. They can be defined via a list where the list name will be the row name. By default, the placement of the extra line is right after the coefficients (except for fixef.group, covered in the last paragraph). For instance, group = list("Controls" = "x[[:digit:]]") will create a line right after the coefficients telling which models contain the control variables. But the placement can be customized. The previous example (of the controls) will be used for illustration (the mechanism for extraline and fixef.group is identical). The row names accept 2 special characters at the very start. The first governs the placement of the new line within the section: it can be equal to "^", meaning first line, or "_", meaning last line. The second character tells in which section the line should appear: it can be equal to "^", "-", or "_", meaning respectively the coefficients, the fixed-effects and the statistics section (which typically appear at the top, mid and bottom of the table). Let's have some examples. Using the previous example, writing "^_Controls" would place the new line in at the top of the statistics section. Writing "_-Controls" places it as the last row of the fixed-effects section; "^^Controls" at the top row of the coefficients section; etc... On top of that there are shortcuts to avoid writing the two special characters. If only one special character is found, it is assumed to reflect the section, unless it corresponds to the default section, a case where the character then reflects the position within the section. An example will make it clear. Writing "^Controls" would place the line at the top of the coefficients section (since the default placement would have been this section). "_Controls" would place it at the bottom of the statistics section. The placement in fixef.group is defined similarly, only the default placement is different. Its default placement is at the top of the fixed-effects section. This means that the only difference with group and extraline is when a single special character is used. Here using, e.g., "^My FEs" would place the row at the bottom of the coefficients section, since "^" would refer to the section (and not the row within the section). Author(s) Laurent Berge See Also See also the main estimation functions femlm, feols or feglm. Use summary.fixest to see the results with the appropriate standard-errors, fixef.fixest to extract the fixed-effects coefficients. Examples   1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 aq = airquality est1 = feols(Ozone ~ i(Month) / Wind + Temp, data = aq) est2 = feols(Ozone ~ i(Month, Wind) + Temp | Month, data = aq) # Displaying the two results in a single table etable(est1, est2) # keep/drop: keeping only interactions etable(est1, est2, keep = " x ") # or using drop (see regexp help): etable(est1, est2, drop = "^(Month|Temp|\\()") # keep/drop: dropping interactions etable(est1, est2, drop = " x ") # or using keep ("!" reverses the effect): etable(est1, est2, keep = "! x ") # order: Wind variable first, intercept last (note the "!" to reverse the effect) etable(est1, est2, order = c("Wind", "!Inter")) # Month, then interactions, then the rest etable(est1, est2, order = c("^Month", " x ")) # # dict # # You can rename variables with dict = c(var1 = alias1, var2 = alias2, etc) # You can also rename values taken by factors. # Here's a full example: dict = c(Temp = "Temperature", "Month::5"="May", "6"="Jun") etable(est1, est2, dict = dict) # Note the difference of treatment between Jun and May # Assume the following dictionary: dict = c("Month::5"="May", "Month::6"="Jun", "Month::7"="Jul", "Month::8"="Aug", "Month::9"="Sep") # We would like to keep only the Months, but now the names are all changed... # How to do? # We can use the special character '%' to make reference to the original names. etable(est1, est2, dict = dict, keep = "%Month") # # signifCode # etable(est1, est2, signifCode = c(" A"=0.01, " B"=0.05, " C"=0.1, " D"=0.15, " F"=1)) # # Using the argument style to customize Latex exports # # If you don't like the default layout of the table, no worries! # You can modify many parameters with the argument style # To drop the headers before each section, use: # Note that a space adds an extra line style_noHeaders = style.tex(var.title = "", fixef.title = "", stats.title = " ") etable(est1, est2, dict = dict, tex = TRUE, style.tex = style_noHeaders) # To change the lines of the table + dropping the table footer style_lines = style.tex(line.top = "\\toprule", line.bottom = "\\bottomrule", tablefoot = FALSE) etable(est1, est2, dict = dict, tex = TRUE, style.tex = style_lines) # Or you have the predefined type "aer" etable(est1, est2, dict = dict, tex = TRUE, style.tex = style.tex("aer")) # # Group and extraline # # Sometimes it's useful to group control variables into a single line # You can achieve that with the group argument setFixest_fml(..ctrl = ~ poly(Wind, 2) + poly(Temp, 2)) est_c0 = feols(Ozone ~ Solar.R, data = aq) est_c1 = feols(Ozone ~ Solar.R + ..ctrl, data = aq) est_c2 = feols(Ozone ~ Solar.R + Solar.R^2 + ..ctrl, data = aq) etable(est_c0, est_c1, est_c2, group = list(Controls = "poly")) # 'group' here does the same as drop = "poly", but adds an extra line # with TRUE/FALSE where the variables were found # 'extraline' adds an extra line, where you can add the value for each model est_all = feols(Ozone ~ Solar.R + Temp + Wind, data = aq) est_sub1 = feols(Ozone ~ Solar.R + Temp + Wind, data = aq[aq$Month %in% 5:6, ]) est_sub2 = feols(Ozone ~ Solar.R + Temp + Wind, data = aq[aq$Month %in% 7:8, ]) est_sub3 = feols(Ozone ~ Solar.R + Temp + Wind, data = aq[aq$Month == 9, ]) etable(est_all, est_sub1, est_sub2, est_sub3, extraline = list("Sub-sample" = c("All", "May-June", "Jul.-Aug.", "Sept."))) # You can monitor the placement of the new lines with two special characters # at the beginning of the row name. # 1) "^" or "_" which mean first or last line of the section # 2) "^", "-" or "_" which mean the coefficients, the fixed-effects or the # statistics section. # # Ex: starting with "^_" will place the line at the top of the stat. section # starting with "_-" will place the line at the bottom of the FEs section # etc. # # You can use a single character which will represent the section, unless # it's # Examples etable(est_c0, est_c1, est_c2, group = list("_Controls" = "poly")) etable(est_all, est_sub1, est_sub2, est_sub3, extraline = list("^Sub-sample" = c("All", "May-June", "Jul.-Aug.", "Sept."))) # Note that since the default placement is the coefficients section, # a single "^" then refers to the position within the section. We end # up at the top of the coefficients section. # # fixef.group # # You can group the fixed-effects line with fixef.group est_0fe = feols(Ozone ~ Solar.R + Temp + Wind, aq) est_1fe = feols(Ozone ~ Solar.R + Temp + Wind | Month, aq) est_2fe = feols(Ozone ~ Solar.R + Temp + Wind | Month + Day, aq) # A) automatic way => simply use fixef.group = TRUE etable(est_0fe, est_2fe, fixef.group = TRUE) # Note that when grouping would lead to inconsistencies across models, # it is avoided etable(est_0fe, est_1fe, est_2fe, fixef.group = TRUE) # B) customized way => use a list etable(est_0fe, est_2fe, fixef.group = list("Dates" = "Month|Day")) # Note that when a user grouping would lead to inconsistencies, # the term partial replaces yes/no and the fixed-effects are not removed. etable(est_0fe, est_1fe, est_2fe, fixef.group = list("Dates" = "Month|Day")) # Using customized placement => as with 'group' and 'extraline', # the user can control the placement of the new line. # See the previous 'group' examples and the dedicated section in the help. # On top of the coefficients: etable(est_0fe, est_2fe, fixef.group = list("^^Dates" = "Month|Day")) # Last line of the statistics etable(est_0fe, est_2fe, fixef.group = list("_Dates" = "Month|Day")) # # Using custom functions to compute the standard errors # # You can customize the way you compute the SEs with the argument .vcov # Let's use some covariances from the sandwich package etable(est_c0, est_c1, est_c2, .vcov = sandwich::vcovHC) # To add extra arguments to vcovHC, you need to use .vcov_args etable(est_c0, est_c1, est_c2, .vcov = sandwich::vcovHC, .vcov_args = list(type = "HC0")) # # Customize which fit statistic to display # # You can change the fit statistics with the argument fitstat # and you can rename them with the dictionnary etable(est1, est2, fitstat = ~ r2 + n + G) # If you use a formula, '.' means the default: etable(est1, est2, fitstat = ~ ll + .) # # Computing a different SE for each model # est = feols(Ozone ~ Solar.R + Wind + Temp, data = aq) # # Method 1: use summary s1 = summary(est, "standard") s2 = summary(est, cluster = ~ Month) s3 = summary(est, cluster = ~ Day) s4 = summary(est, cluster = ~ Day + Month) etable(list(s1, s2, s3, s4)) # # Method 2: using a list in the argument 'cluster' est_bis = feols(Ozone ~ Solar.R + Wind + Temp | Month, data = aq) etable(list(est, est_bis), cluster = list("standard", ~ Month)) # # Method 3: Using rep() etable(rep(est, cluster = list("standard", ~ Month))) # When using rep on 2 or more objects, you need to embed them in .l() etable(rep(.l(est, est_bis), cluster = list("standard", ~ Month, ~ Day))) # Using each to order differently etable(rep(.l(est, est_bis), each = 3, cluster = list("standard", ~ Month, ~ Day))) 

fixest documentation built on June 19, 2021, 5:06 p.m.