Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
#fig.path = "",
warning = FALSE,
message = FALSE
)
## ----setup--------------------------------------------------------------------
library(implicitMeasures)
## -----------------------------------------------------------------------------
data("raw_data")
# explore the dataframe
str(raw_data)
# explore the levels of the blockcode variable to identify the IAT blocks
levels(raw_data$blockcode)
## ----eval = T-----------------------------------------------------------------
iat_cleandata <- clean_iat(raw_data, sbj_id = "Participant",
block_id = "blockcode",
mapA_practice = "practice.iat.Milkbad",
mapA_test = "test.iat.Milkbad",
mapB_practice = "practice.iat.Milkgood",
mapB_test = "test.iat.Milkgood",
latency_id = "latency",
accuracy_id = "correct",
trial_id = "trialcode",
trial_eliminate = c("reminder", "reminder1"),
demo_id = "blockcode",
trial_demo = "demo")
## -----------------------------------------------------------------------------
str(iat_cleandata)
## -----------------------------------------------------------------------------
iat_data <- iat_cleandata[[1]]
head(iat_data)
## -----------------------------------------------------------------------------
dscore <- compute_iat(iat_data, Dscore = "d3")
str(dscore)
## -----------------------------------------------------------------------------
descript_d(dscore) # Data frame containing IAT D-scores
## -----------------------------------------------------------------------------
descript_d(dscore, # Data frame containing IAT D-scores
latex = TRUE) # obtain the code for latex tables
## -----------------------------------------------------------------------------
IAT_rel(dscore)
## ---- fig.align='center', fig.width=6, fig.cap="d_point() function with default settings"----
d_point(dscore) # Data frame containing IAT D scores
## ---- fig.align='center', fig.width=6, fig.cap="d_point() function with settings change"----
d_point(dscore, # dataframe containing IAT D-scores
order_sbj = "D-decreasing", # change respondents order
x_values = FALSE, # remove respodents' labels
include_stats = TRUE, # include descriptive statistics
col_point = "lightskyblue") # change points color
## ---- fig.align='center', fig.width=6, fig.cap="d_density() function with default settings"----
d_density(dscore) # dataframe containing IAT Dscores
## ----sampleSettings, fig.align='center', fig.width=6, fig.cap="\\label{fig:sampleSettings}d_density() function with settings change"----
d_density(dscore, # dataframe containing IAT Dscores
graph = "violin", # change graphical representation
include_stats = TRUE) # include descriptive statistics
## -----------------------------------------------------------------------------
multi_scores <- multi_dscore(iat_data, # object with class "iat_clean"
ds = "error-inflation") # string specifying the
# algorithms to compute
## -----------------------------------------------------------------------------
multi_d <- multi_scores[[1]]
head(multi_d)
str(multi_d)
## ---- fig.align='center', fig.width=6, fig.cap="Multiple D-scores representation"----
multi_scores[[2]]
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