For this exercise, please try to reproduce the results from Experiment 2 of the associated paper (de la Fuente, Santiago, Roman, Dumitrache, & Casasanto, 2014). The PDF of the paper is included in the same folder as this Rmd file.
Researchers tested the question of whether temporal focus differs between Moroccan and Spanish cultures, hypothesizing that Moroccans are more past-focused, whereas Spaniards are more future-focused. Two groups of participants (\(N = 40\) Moroccan and \(N=40\) Spanish) completed a temporal-focus questionnaire that contained questions about past-focused (“PAST”) and future-focused (“FUTURE”) topics. In response to each question, participants provided a rating on a 5-point Likert scale on which lower scores indicated less agreement and higher scores indicated greater agreement. The authors then performed a mixed-design ANOVA with agreement score as the dependent variable, group (Moroccan or Spanish, between-subjects) as the fixed-effects factor, and temporal focus (past or future, within-subjects) as the random effects factor. In addition, the authors performed unpaired two-sample t-tests to determine whether there was a significant difference between the two groups in agreement scores for PAST questions, and whether there was a significant difference in scores for FUTURE questions.
Below is the specific result you will attempt to reproduce (quoted directly from the results section of Experiment 2):
According to a mixed analysis of variance (ANOVA) with group (Spanish vs. Moroccan) as a between-subjects factor and temporal focus (past vs. future) as a within-subjectS factor, temporal focus differed significantly between Spaniards and Moroccans, as indicated by a significant interaction of temporal focus and group, F(1, 78) = 19.12, p = .001, ηp2 = .20 (Fig. 2). Moroccans showed greater agreement with past-focused statements than Spaniards did, t(78) = 4.04, p = .001, and Spaniards showed greater agreement with future-focused statements than Moroccans did, t(78) = −3.32, p = .001. (de la Fuente et al., 2014, p. 1685).
library(tidyverse) # for data munging
library(knitr) # for kable table formating
library(haven) # import and export 'SPSS', 'Stata' and 'SAS' Files
library(readxl) # import excel files
# #optional packages/functions:
# library(afex) # anova functions
# library(ez) # anova functions 2
# library(scales) # for plotting
std.err <- function(x) sd(x)/sqrt(length(x)) # standard error
# Just Experiment 2
data_path <- 'data/DeLaFuenteEtAl_2014_RawData.xls'
d <- read_excel(data_path, sheet=3)
colnames(d)[5] = "Agreement"
Try to recreate Figure 2 (fig2.png, also included in the same folder as this Rmd file):
stat_summary(aes(x=group))
## mapping: x = ~group
## geom_pointrange: na.rm = FALSE, orientation = NA
## stat_summary: fun.data = NULL, fun = NULL, fun.max = NULL, fun.min = NULL, fun.args = list(), na.rm = FALSE, orientation = NA
## position_identity
means_d <- d %>%
group_by(group, subscale) %>%
summarize(Agreement = mean(Agreement), .groups = "keep") %>%
mutate(SEM = std.err(d$Agreement))
ggplot(means_d, aes(x = group, fill = subscale, y = Agreement)) + geom_col(position = "dodge") + scale_x_discrete(labels=c('Moroccans', 'Spaniards')) + geom_errorbar(aes(ymin = Agreement - SEM, ymax = Agreement + SEM), position="dodge") + coord_cartesian(ylim=c(2, 4))
According to a mixed analysis of variance (ANOVA) with group (Spanish vs. Moroccan) as a between-subjects factor and temporal focus (past vs. future) as a within-subjects factor, temporal focus differed significantly between Spaniards and Moroccans, as indicated by a significant interaction of temporal focus and group, F(1, 78) = 19.12, p = .001, ηp2 = .20 (Fig. 2).
# mixed_anova <- anova_test(data = d, dv = Agreement, wid = participant, between = group, within = subscale)
#summary(mixed_anova)
Moroccans showed greater agreement with past-focused statements than Spaniards did, t(78) = 4.04, p = .001,
# :(
and Spaniards showed greater agreement with future-focused statements than Moroccans did, t(78) = −3.32, p = .001.(de la Fuente et al., 2014, p. 1685)
# :(
Were you able to reproduce the results you attempted to reproduce? If not, what part(s) were you unable to reproduce?
I spent 3 hours and couldn’t figure out how to run a mixed anova given the structure of the data :(
How difficult was it to reproduce your results?
Quite.
What aspects made it difficult? What aspects made it easy?
It took me a really long time to figure out ggplot, which was pretty frustrating but not inherently hard. Similarly, I struggled with the format of the data for running an anova.