TODO: intro text to package altOp
See for further details e. g. Babbie, Earl R. (2016), The Practice of Social Research, chapter 5 ("Conceptualization, Operationalization, and Measurement")
We will use the dataset CEOcomp
with data on CEO compensation in this vignette to illustrate the package's function. This dataset is part of the package. Here are the first 5 rows of CEOComp
to give you an idea what the data looks like.
library(altOp) data(CEOcomp) knitr::kable(head(CEOcomp, 5))
The package broom
is a package for ..TODO short explanation ...
altOp
is particularly useful in combination with some other packages such as broom.
# allFormulas <- # TODO: list mit formulas generiert mit unseren Befehlen allFormulas <- list(form, form2, form3)
# estimate all models specified by the various formulae allModels <- lapply(allFormulas, function(form) lm(form, data=CEOcomp))
# save all tidied model results as list of data.frames library(broom) allModelResults <- lapply(allModels, function(mod) broom::tidy(mod))
# TODO: # * Place examples here how to rbind all the data.frames together in a useful format [variable estimates, t- and p-value in columns] (code is with KT) (maybe develop new way with dplyr?) # * Also support row-wise format (like tidy format, but data is not "tidy" anymore)? Introduce column with model number and formula
library(stargazer) # TODO: fertigstellen: stargazer(allModels, type="text")
library(texreg) ## TODO texreg(TODO)
#TODO: Pixiedust? #TODO: sjPlot?
# TODO: adapt parameters, function name etc., once the function is ready ex1_depVar <- c("compvar") # dependend variable ex1_opList <- list(c("roa", "roe", "tsr")) # various operationalizations of firm performance ex1_fixVars <- c("emp", "marketcap") # fixed variables (to appear in all formulae) # ex1_all_formulae <- generiere_alle_formeln(abhVar = ex1_depVar, # opList = ex1_opList, # festVar = ex1_fixVars) #print(ex1_all_formulae)
This returns a list with 3 different formulae, because there are 3 different operationalizations for 1 variable (firm performance).
# TODO: adapt parameters, function name etc., once the function is ready ex2_depVar <- c("compvar") # dependend variable ex2_opList <- list(c("roa", "roe", "tsr"), c("marketcap", "emp")) # various operationalizations for firm perf. and firm size ex2_fixVars <- c("beta") # fixed variables (to appear in all formulae) # ex2_all_formulae <- generiere_alle_formeln(abhVar = ex2_depVar, # opList = ex2_opList, # festVar = ex2_fixVars) #print(ex2_all_formulae)
This returns a list with 6 different formulae, because there are 3 different operationalizations for firm performance and 2 different operationalizations for firm size (6 = 3 * 2).
TODO: auch kurz, wie die LHS ersetzt wird (update.formula())
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