All Functions of Week 8

summary

{base}

Obtain summary statistics or detailed regression output

library

{base}

Load an R package

lm

{stats}

Fit linear models using least squares

group_tt

{tinytable}

Grouping in tinytable

na.omit

{stats}

Remove missing values

mutate

{dplyr}

Create new variables

theme_latex

{tinytable}

A theme for modelsummary/tinytable tables

plm

{plm}

Estimates linear panel data models (fixed effects, random effects, pooling, between, first-differences)

lag

{dplyr}

Shift values in a vector or time series

ungroup

{dplyr}

Resolve grouping created with “group_by”

list

{base}

Create a list object

log

{base}

log (default base = e)

read.csv

{utils}

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

modelsummary

{modelsummary}

Creates regression and data tables

coeftest

{lmtest}

Inference for Estimated Coefficients

pdata.frame

{plm}

Creates a panel data frame, the data structure used by the plm package for panel/longitudinal data

nobs

{stats}

Return the number of observations in a model object

vcovSCC

{plm}

Computes Driscoll and Kraay (SCC) robust covariance matrix estimators for panel models

group_by

{dplyr}

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

filter

{dplyr}

Filter out rows of a data frame according to logical vector

c

{base}

Combine values/vectors into a vector

arrange

{dplyr}

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

The end!