Title: | Convert 'sjPlot' HTML-Tables to R 'data.frame' |
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Description: | A small set of helper functions to convert 'sjPlot' HTML-tables to R data.frame objects / knitr::kable-tables. |
Authors: | Lorenz A. Kapsner [cre, aut, cph]
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Maintainer: | Lorenz A. Kapsner <[email protected]> |
License: | GPL (>= 3) |
Version: | 0.0.3 |
Built: | 2025-02-01 03:42:35 UTC |
Source: | https://github.com/kapsner/sjtable2df |
Convert table from 'sjPlot::tab_model' to R data.frame or 'knitr::kable'
mtab2df(mtab, n_models, output = "data.table", ...)
mtab2df(mtab, n_models, output = "data.table", ...)
mtab |
A model table, created with 'sjPlot::tab_model'. |
n_models |
An integer, specifiying the number of models in the table. |
output |
A character vector. Allowed values are: "data.table" (default), "data.frame" or "kable". The function's return value is of the respective type. |
... |
Further arguments to be passed to 'kableExtra::kbl'. |
The table is returned as an R object of the type specified with the 'output' argument.
set.seed(1) dataset <- data.table::data.table( "var1" = factor(sample( x = c("yes", "no"), size = 100, replace = TRUE, prob = c(.3, .7) )), "var2" = factor(sample( x = c("yes", "no"), size = 100, replace = TRUE )), "var3" = rnorm(100) ) # models m0 <- stats::glm( var1 ~ 1, data = dataset, family = binomial(link = "logit") ) m1 <- stats::glm( var1 ~ var2, data = dataset, family = binomial(link = "logit") ) m2 <- stats::glm( var1 ~ var2 + var3, data = dataset, family = binomial(link = "logit") ) m_table <- sjPlot::tab_model(m0, m1, m2, show.aic = TRUE) final_tab <- sjtable2df::mtab2df(mtab = m_table, n_models = 3)
set.seed(1) dataset <- data.table::data.table( "var1" = factor(sample( x = c("yes", "no"), size = 100, replace = TRUE, prob = c(.3, .7) )), "var2" = factor(sample( x = c("yes", "no"), size = 100, replace = TRUE )), "var3" = rnorm(100) ) # models m0 <- stats::glm( var1 ~ 1, data = dataset, family = binomial(link = "logit") ) m1 <- stats::glm( var1 ~ var2, data = dataset, family = binomial(link = "logit") ) m2 <- stats::glm( var1 ~ var2 + var3, data = dataset, family = binomial(link = "logit") ) m_table <- sjPlot::tab_model(m0, m1, m2, show.aic = TRUE) final_tab <- sjtable2df::mtab2df(mtab = m_table, n_models = 3)
Convert table from 'sjPlot::tab_xtab' to R data.frame or 'knitr::kable'
xtab2df(xtab, output = "data.table", threeparttable = FALSE, ...)
xtab2df(xtab, output = "data.table", threeparttable = FALSE, ...)
xtab |
A contingency table, created with 'sjPlot::tab_xtab'. |
output |
A character vector. Allowed values are: "data.table" (default), "data.frame" or "kable". The function's return value is of the respective type. |
threeparttable |
Boolean value indicating if a threeparttable scheme should be used. |
... |
Further arguments to be passed to 'kableExtra::kbl'. |
The table is returned as an R object of the type specified with the 'output' argument.
set.seed(1) dataset <- data.table::data.table( "var1" = sample( x = c("yes", "no"), size = 100, replace = TRUE, prob = c(.3, .7) ), "var2" = sample( x = c("yes", "no"), size = 100, replace = TRUE ) ) xtab <- sjPlot::tab_xtab( var.row = dataset$var1, var.col = dataset$var2, show.summary = TRUE, use.viewer = FALSE ) sjtable2df::xtab2df(xtab = xtab)
set.seed(1) dataset <- data.table::data.table( "var1" = sample( x = c("yes", "no"), size = 100, replace = TRUE, prob = c(.3, .7) ), "var2" = sample( x = c("yes", "no"), size = 100, replace = TRUE ) ) xtab <- sjPlot::tab_xtab( var.row = dataset$var1, var.col = dataset$var2, show.summary = TRUE, use.viewer = FALSE ) sjtable2df::xtab2df(xtab = xtab)