All Functions of Week 7

as.numeric

{base}

Coerce a vector to numeric

subset

{base}

Return subsets of vectors, matrices or data frames which meet conditions.

auc

{pRoc}

Returns the area under the curve

data.frame

{base}

Create a data.frame from vectors

tibble

{tibble}

A modern data frame from the tidyverse

glm

{base}

Fits generalized linear models

mutate

{dplyr}

Modify/create a column in a data frame

grid.arrange

{gridExtra}

Places graphical objects into a rectangular grid

setwd

{base}

Set Working Directory

attr

{base}

Access or modify the attributes of an object

c

{base}

Combine values/vectors into a vector

read.csv

{utils}

Read a csv file to data frame. Specify stringsAsFactors = FALSE to keep all string columns as characters

summary

{base}

Obtain summary statistics or detailed regression output

predict

{stats}

Predict Probability

group_by

{dplyr}

Group tibble/data.frame by a factor variable. All further tidyverse operations are performed group-wise

ggsave

{ggplot2}

Saves the last ggplot or a specified ggplot object to a file

library

{base}

Load an R package

ungroup

{dplyr}

Resolve grouping created with “group_by”

regTermTest

{regress}

Perform statistical tests for individual regression coefficients

lag

{dplyr}

Shift values in a vector or time series

modelsummary

{modelsummary}

Creates regression and data tables

arrange

{dplyr}

Sort values of data frame according to a variable/combination of varaibles

is.na

{base}

Check if a value is NA/elements of vector are NA

plot

{graphics}

Generic function from base R to produce a plot

select

{dplyr}

Select columns from a tibble/data frame

read_dta

{haven}

Read a .dta file (Stata data)

binomial

{base}

Family argument in glm()

pnorm

{base}

Returns the cumulative distribution function (CDF) of the normal distribution

par

{graphics}

Set parameters of the plotting device

filter

{dplyr}

Filter out rows of a data frame according to logical vector

list

{base}

Create a list object

roc

{pRoc}

Create a Receiver Operating Characteristic (ROC) curve

rbind

{base}

Combine R objects by rows

group_tt

{tinytable}

Grouping in tinytable

seq

{base}

Create a sequence

nobs

{gdata}

Compute the number of non-missing observations

unlist

{base}

Flattens a list into a vector by extracting all its elements

The end!