mTools

mTools a collection of function I regularly use.

Installation

You can install the development version of mTools from GitHub with:

# install.packages("devtools")
devtools::install_github("m-mburu/mTools")

load package

library(mTools)

Example

This is a basic example which shows you how to solve a common problem:

iris_head  <- head(iris)
data_table(iris_head)

Produce nice Rmarkdowns tables from model objects

Tidy summary results

data("diabetes")
library(MASS)
library(knitr)
library(broom)
model <- glm(Outcome ~ .,
             family = binomial(),
             data = diabetes)


DT_tidy_model(model, round_digts = 2,
              tidy_function = "tidy", 
              output_function = "kable", 
              coefficient_name = "estimate",
              coefficient_name_new = "ODDS Ratio 95% CI",
              exp_estimate = TRUE, 
              coefficient_ci= TRUE,
              confint_level = .95)
#> Waiting for profiling to be done...

term	ODDS Ratio 95% CI	std.error	statistic	p.value
(Intercept)	0[0 0]	0.72	-11.73	0.00
Pregnancies	1.13[1.06 1.21]	0.03	3.84	0.00
Glucose	1.04[1.03 1.04]	0.00	9.48	0.00
BloodPressure	0.99[0.98 1]	0.01	-2.54	0.01
SkinThickness	1[0.99 1.01]	0.01	0.09	0.93
Insulin	1[1 1]	0.00	-1.32	0.19
BMI	1.09[1.06 1.13]	0.02	5.95	0.00
DiabetesPedigreeFunction	2.57[1.44 4.66]	0.30	3.16	0.00
Age	1.01[1 1.03]	0.01	1.59	0.11

Tidy glance results

DT_tidy_model(model,
              tidy_function ="glance" ,
              output_function = "kable")

null.deviance	df.null	logLik	AIC	BIC	deviance	df.residual	nobs
993.4839	767	-361.7227	741.4454	783.2395	723.4454	759	768