Toolkit for Compiling, (Post-Hoc) Testing, and Plotting Regression Results

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Documentation for package ‘regrrr’ version 0.1.3

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regrrr-package regrrr: a toolkit for compiling regression results
add.n.r Add row numbers to regression result data.frame
add.pr Add approximate p-value based on t score or z score, when sample size is large
add.sig Add significance level marks to the regression result
check_cor quickly check correlation matrix, or the correlation between a particular X and all other vars could be useful for looking for relevant instrument
check_na_in quickly check the proportion of NAs in each columns of a dataframe
check_vif quickly check the vifs in a regression model; for checking multi-collinearity
combine_long_tab Combine regression results from different models by columns
compare_models Compare regression models, which is compatible with the reg.table output # updated 9/13/2018 #
cor.table make the correlation matrix from the data.frame used in regression
load.pkgs load multiple packages
plot_effect plotting the marginal effect of X on Y, with or without one or multiple interaction terms
regrrr regrrr: a toolkit for compiling regression results
scale_01 Scale a vector into the 0-1 scale
test_coef_equality testing equality of two coefficients (difference between coefficients of regressors), a Wald test note: if v is not alternatively specified, use car::linearHypothesis(lm_model, "X1 = X2")
test_tilted_slopes significance of regression slope (the marginal effect) under moderation testing restriction: the sig. of beta_x under the moderation of z1, with or without additional interaction terms (z2, z3, etc.)
to_long_tab Convert the regression result to the long format: the standard errors are in parentheses and beneath the betas