Error: `expr` must quote a symbol, scalar, or call

[jacob-long]

Error: `expr` must quote a symbol, scalar, or call

[jacob-long]

Hmm, this is strange. Can you show me the output when you run sessionInfo()?

[pettitta]

Sure! Here it is

R version 3.4.1 (2017-06-30)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS 10.14.3

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] interactions_1.0.0 lmerTest_3.0-1 lme4_1.1-21 Matrix_1.2-10

loaded via a namespace (and not attached):
[1] Rcpp_0.12.17 pillar_1.2.3 compiler_3.4.1 nloptr_1.0.4 plyr_1.8.4
[6] bindr_0.1.1 tools_3.4.1 boot_1.3-19 tibble_1.4.2 nlme_3.1-131
[11] gtable_0.2.0 lattice_0.20-35 pkgconfig_2.0.1 rlang_0.2.1 cli_1.0.0
[16] rstudioapi_0.7 yaml_2.1.19 bindrcpp_0.2.2 dplyr_0.7.6 knitr_1.20
[21] jtools_2.0.0 grid_3.4.1 tidyselect_0.2.4 glue_1.2.0 R6_2.2.2
[26] minqa_1.2.4 ggplot2_3.0.0 purrr_0.2.5 magrittr_1.5 scales_0.5.0
[31] MASS_7.3-47 splines_3.4.1 assertthat_0.2.0 colorspace_1.3-2 numDeriv_2016.8-1
[36] lazyeval_0.2.1 munsell_0.5.0 crayon_1.3.4

[pettitta]

Edit: nvm. I just had to update R and it fixed the problem

[xiaoxuefu]

Hi,

I had the same error message with interact_plot. So I stumbled upon this post. I am using the updated R version.

I tried to use the same codes as pettitta:

library(interactions)
library(jtools)

fitiris <- lm(Petal.Length ~ Petal.Width * Species, data = iris)
summ(fitiris)

interact_plot(fitiris, pred = Petal.Width, modx = Species, plot.points = TRUE)

I got: Error: expr must quote a symbol, scalar, or call

Here is my traceback() outputs

8: stop(cnd)
7: abort("expr must quote a symbol, scalar, or call")
6: switch_type(expr, symbol = as_string(expr), quosure = , language = {
name <- deparse_one(expr)
name <- gsub("\n.$", "...", name)
name
}, if (is_scalar_atomic(expr)) {
as.character(expr)
} else if (length(expr) == 1) {
name <- expr_text(expr)
name <- gsub("\n.$", "...", name)
name
} else {
abort("expr must quote a symbol, scalar, or call")
})
5: expr_name(quo_squash(quo))
4: quo_name(enexpr(mod2))
3: (function (model, pred, modx, modx.values = NULL, mod2 = NULL,
mod2.values = NULL, centered = "all", data = NULL, plot.points = FALSE,
interval = FALSE, int.type = c("confidence", "prediction"),
int.width = 0.95, outcome.scale = "response", linearity.check = FALSE,
facet.modx = FALSE, robust = FALSE, cluster = NULL, vcov = NULL,
set.offset = 1, x.label = NULL, y.label = NULL, pred.labels = NULL,
modx.labels = NULL, mod2.labels = NULL, main.title = NULL,
legend.main = NULL, colors = NULL, line.thickness = 1, vary.lty = TRUE,
point.size = 1.5, point.shape = FALSE, jitter = 0, rug = FALSE,
rug.sides = "b", partial.residuals = FALSE, point.alpha = 0.6,
color.class = NULL, ...)
{
dots <- list(...)
if (length(dots) > 0) {
if ("modxvals" %in% names(dots)) {
modx.values <- dots$modxvals
}
if ("mod2vals" %in% names(dots)) {
mod2.values <- dots$mod2vals
}
}
if (!is.null(color.class)) {
colors <- color.class
msg_wrap("The color.class argument is deprecated. Please use 'colors'\n instead.")
}
pred <- quo_name(enexpr(pred))
modx <- quo_name(enexpr(modx))
if (modx == "NULL") {
modx <- NULL
}
mod2 <- quo_name(enexpr(mod2))
if (mod2 == "NULL") {
mod2 <- NULL
}
if (any(c(pred, modx, mod2) %in% centered)) {
warn_wrap("You cannot mean-center the focal predictor or moderators with\n this function.")
centered <- centered %not% c(pred, modx, mod2)
if (length(centered) == 0) {
centered <- "none"
}
}
modxvals2 <- mod2vals2 <- resp <- NULL
if (linearity.check == TRUE) {
facet.modx <- TRUE
}
if (is.null(data)) {
d <- get_data(model, warn = TRUE)
}
else {
d <- data
}
weights <- get_weights(model, d)$weights_name
pred_out <- prep_data(model = model, pred = pred, modx = modx,
modx.values = modx.values, mod2 = mod2, mod2.values = mod2.values,
centered = centered, interval = interval, int.type = int.type,
int.width = int.width, outcome.scale = outcome.scale,
linearity.check = linearity.check, robust = robust, cluster = cluster,
vcov = vcov, set.offset = set.offset, modx.labels = modx.labels,
mod2.labels = mod2.labels, facet.modx = facet.modx, d = d,
survey = "svyglm" %in% class(model), weights = weights,
preds.per.level = 100, partial.residuals = partial.residuals,
...)
meta <- attributes(pred_out)
lapply(names(meta), function(x, env) {
env[[x]] <- meta[[x]]
}, env = environment())
pm <- pred_out$predicted
d <- pred_out$original
if (!is.numeric(d[[pred]])) {
stop("Focal predictor ("pred") cannot be a factor. Either",
" use it as modx, convert it to a numeric dummy variable,",
" or use the cat_plot function for factor by factor interaction",
" plots.")
}
plot_mod_continuous(predictions = pm, pred = pred, modx = modx,
resp = resp, mod2 = mod2, data = d, plot.points = plot.points |
partial.residuals, interval = interval, linearity.check = linearity.check,
x.label = x.label, y.label = y.label, pred.labels = pred.labels,
modx.labels = modx.labels, mod2.labels = mod2.labels,
main.title = main.title, legend.main = legend.main, colors = colors,
line.thickness = line.thickness, vary.lty = vary.lty,
jitter = jitter, modxvals2 = modxvals2, mod2vals2 = mod2vals2,
weights = weights, rug = rug, rug.sides = rug.sides,
point.size = point.size, point.shape = point.shape, facet.modx = facet.modx)
})(model = fitiris, pred = Petal.Width, modx = Species, plot.points = TRUE)
2: do.call(get("interact_plot", asNamespace("interactions")), as.list(match.call(get("interact_plot",
asNamespace("interactions"))))[-1])
1: interact_plot(fitiris, pred = Petal.Width, modx = Species, plot.points = TRUE)

My sessionInfo():

R version 3.5.2 (2018-12-20)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats graphics grDevices utils datasets methods base

other attached packages:
[1] jtools_2.0.0 interactions_1.1.0.9000

loaded via a namespace (and not attached):
[1] Rcpp_0.12.17 rstudioapi_0.7 bindr_0.1.1 magrittr_1.5 tidyselect_0.2.4 munsell_0.5.0
[7] colorspace_1.3-2 R6_2.2.2 rlang_0.2.1 plyr_1.8.4 dplyr_0.7.6 tools_3.5.2
[13] grid_3.5.2 gtable_0.2.0 cli_1.0.0 yaml_2.1.19 lazyeval_0.2.1 assertthat_0.2.0
[19] tibble_1.4.2 crayon_1.3.4 bindrcpp_0.2.2 purrr_0.2.5 ggplot2_3.0.0 glue_1.3.0
[25] compiler_3.5.2 pillar_1.3.0 scales_0.5.0 pkgconfig_2.0.1

Thank you very much for your help!

[jacob-long]

Hi @xiaoxuefu, thank you for sharing your sessionInfo().

Can you try updating the rlang package (update.packages("rlang")) and see if that changes anything?

[xiaoxuefu]

@jacob-long Thank you so much! It solved the problem.

Great package!

[jacob-long]

Great news! Now I can change a setting to make sure everybody who installs this package has an up-to-date version of rlang.