The goal of educ7610 is to make several aspects of the Regression
course (EDUC/PSY 7610) at Utah State University more accessible.
Specifically, it provides the data from Darlington and Hayes’ book
“Regression Analysis and Linear Models”, a syntax to perform
diagnostics and Johnson-Neyman, odds ratios from logistic regression,
among other things. In conjunction with packages like interactions and
the easystats group of packages, this package can make regression
analyses more straightforward.
You can install the development version from GitHub with:
# install.packages("remotes")
remotes::install_github("tysonstanley/educ7610")This is a basic example which shows you how to solve a common problem:
library(educ7610)
#> ── educ7610 0.2.0 ────────────────────────────────────────────────── learn more at tysonbarrett.com ──
#> ✔ educ7610 attached
#> ✔ No potential conflicts found
data("poverty") ## load the poverty data set
model <- lm(TeenBirth ~ ViolentCrime + poverty_pct,
data = poverty)
diagnostics(model) %>% head()
#> TeenBirth ViolentCrime poverty_pct pred resid dfb.1_
#> 1 54.5 11.2 20.1 54.97777 -0.4777688 0.01140240
#> 2 39.5 9.1 7.1 32.93430 6.5656964 0.21476505
#> 3 61.2 10.4 16.1 48.13306 13.0669381 -0.08407140
#> 4 59.9 10.4 14.9 46.17653 13.7234707 -0.01726762
#> 5 41.1 11.2 16.7 49.43426 -8.3342598 0.07141738
#> 6 47.0 5.8 8.8 34.37397 12.6260347 0.29388664
#> dfb.VlnC dfb.pvr_ dffit cov.r cook.d hat
#> 1 0.003853716 -0.01434251 -0.01704369 1.1535952 9.888197e-05 0.07683369
#> 2 0.108941094 -0.20044139 0.23370808 1.1046067 1.833345e-02 0.07562858
#> 3 -0.011028702 0.14825406 0.28167070 0.9325356 2.558198e-02 0.02937639
#> 4 0.024749616 0.07786167 0.26245140 0.9118951 2.209091e-02 0.02328784
#> 5 0.002990049 -0.10973056 -0.19000614 1.0324334 1.202486e-02 0.03364566
#> 6 0.062618745 -0.23177500 0.32712068 0.9529815 3.460873e-02 0.04150863