无法在 Jupyter Notebook 中加载 processR 包的 `model1` 函数

Question

I am very new to the whole R programming and trying to follow this tutorial , where the model1 function is used to find the Andrew F. Hayes correlation between three variables. As indicated in the tutorial I have the packages installed:

1. install.packages("devtools")
2. install.packages("processR")
3. devtools::install_github("markhwhiteii/processr")

I have also followed the steps:

set.seed(1839)
var1 <- rnorm(100)
cond <- rbinom(100, 1, .5)
var2 <- var1 * cond + rnorm(100)
df3 <- data.frame(var1, var2, cond)
head(df3)

accordingly. However, when running:

mod1result <- model1(iv = "var1", dv = "var2", mod = "cond", data = df3)

I get the error message:

Error in model1(iv = "var1", dv = "var2", mod = "cond", data = df3): could not find function "model1" Traceback:

and running

mod1result <- processr::model1(iv = "var1", dv = "var2", mod = "cond", data = df3)

Error in loadNamespace(name): there is no package called 'processr' Traceback:

The strange thing is that the same code just worked yesterday and now it doesn't. I would appreciate it if you could help me understand what is wrong and how I can resolve it.

PS1. I'm not sure what .libPaths() is but for some reason it returns two paths on my mac:

• /usr/local/lib/R/3.6/site-library
• /usr/local/Cellar/r/3.6.2/lib/R/library

does it mean that I have two installations of R and this is the main cause of the above issues?

PS2. OK. This seems to be Jupyter's fault as everything is just working fine in the terminal.

PS3. What seems to be working in the terminal is:

• sudo r
• devtools::install_github("markhwhiteii/processr")
• library(processr) notice lower case r in the processr

PS4. I'm not sure if this is Jupyter's fault.

PS5. I tried installing the packages on Windows as well. It was even worse. I can't get passed the issue:

Error: Failed to install 'processr' from GitHub: (converted from warning) cannot remove the prior installation of package 'digest'

I think maybe the key to solving this problem is to understand what is the difference between these packages:

• install.packages("processR")
• devtools::install_github("markhwhiteii/processr")
• devtools::install_github("cardiomoon/processR")

Answer 1

OK, after a couple of hours of trial and error, I think I have a messy workaround, not a solution though!

• run sudo r in one terminal
• run jupyter notebook in another and open an R notebook (I suppose you have the kernel installed)

• now you should understand that the devtools::install_github("markhwhiteii/processr") and install.packages("processR") are two different packages and you gave install both every time you restart your kernel in the Jupyter Notebook

• install devtools::install_github("markhwhiteii/processr") first in the R terminal

• now in the Jupyter side you should be able to library(processr) and run processr::model1
• next install the install.packages("processR") on the R terminal
• now import the library(processR)
• now you should be able to run the functions such as pmacroModel etc

Basically you need both processr and processR !

BTW, the same issue is the R terminal. You have to run as sudo and follow the above steps to get everything working!

Answer 2

From the tutorial page you references, install processr (not processR ) in the following way:

# Run this if devtools isn't installed.
# install.packages("devtools")

# Run to install "processr"
devtools::install_github("markhwhiteii/processr")

After that successfully completes, processr::model1 will be defined.

When running the code in this post it produces a result:

set.seed(1839)
var1 <- rnorm(100)
cond <- rbinom(100, 1, .5)
var2 <- var1 * cond + rnorm(100)
df3 <- data.frame(var1, var2, cond)
head(df3)

mod1result <- processr::model1(iv = "var1", dv = "var2", mod = "cond", data = df3)

mod1result
## # A tibble: 6 x 5
##   term          estimate std.error statistic       p.value
##   <chr>            <dbl>     <dbl>     <dbl>         <dbl>
## 1 intercept       0.133      0.146     0.916 0.362        
## 2 var1            0.0696     0.156     0.445 0.657        
## 3 cond           -0.173      0.200    -0.865 0.389        
## 4 interaction     0.854      0.213     4.01  0.000118     
## 5 when cond = 0   0.0696     0.156     0.445 0.657        
## 6 when cond = 1   0.924      0.144     6.40  0.00000000577