Basic function for running the frequentist's repeated measures analysis of variance (ANOVA)
rm_anova_mf(
cs1,
cs2,
data,
subj,
time = TRUE,
group = NULL,
phase = "acquisition",
dv = "scr",
exclusion = "full data",
cut_off = "full data",
correction = FALSE
)The column name(s) of the conditioned responses for the first conditioned stimulus
The column name(s) of the conditioned responses for the second conditioned stimulus
A data frame containing all the relevant columns for the analyses
The name of the column including the participant numbers. Unique numbers are expected
should time be included? Default to TRUE
the name of the group, if included, default to NULL
The conditioned phase that the analyses refer to. Accepted values are acquisition, acq, extinction, or ext
name of the measured conditioned response. Default to "SCR"
Name of the data reduction procedure used. Default to full data
cut off Name of the cut_off applied. Default to full data
whether the Greenhouse-Geisser correction should be applied or not. Default to FALSE
A basic function for running repeated measures ANOVAs.
A tibble with the following column names:
x: the name of the independent variable (e.g., cs)
y: the name of the dependent variable as this defined in the dv argument
exclusion: see exclusion argument
model: the model that was run (e.g., t-test)
controls: ignore this column for this test
method: the model that was run
p.value: the p-value of the test
effect.size: the estimated effect size
effect.size.ma: the estimated effect size for the meta-analytic plots
effect.size.ma.lci: low confidence intervals for the meta-analytic effect size
effect.size.ma.hci: high confidence intervals for the meta-analytic effect size
estimate: the estimate of the test run
statistic: the F-value
conf.low: the lower confidence interval for the estimate
conf.high: the higher confidence interval for the estimate
framework: were the data analysed within a NHST or Bayesian framework?
data_used: a list with the data used for the specific test
In case the time argument is set to TRUE (default value), the function will include this as a within subjects factor, assuming that the columns in
cs1 and cs2 correspond to ascending time points (e.g., cs1
trial 1, cs1 trial 2 ... cs1 trial n). If this is not the case, the
results are not to be trusted.
The function uses the ez::ezANOVA function. The function gives by default a warning regarding the collapsing of factors. This function here suppresses this warning but the user should be aware of it. Please note that at the moment no sphericity correction is performed. The reported effect size is omega squared as this is computed by sjstats::omega_sq. The meta-analytic effect size is eta squared.
# Load example data
data(example_data)
# Briefly define argument values that will be plugged in later on in the functions
cs1 <- paste0("CSP", 1:10)
cs2 <- paste0("CSM", 1:10)
subj <- "id"
group <- "group"
# Repeated measures ANOVA without groups
rm_anova_mf(cs1 = cs1, cs2 = cs2, subj = subj, data = example_data, time = TRUE)
#> # A tibble: 1 × 20
#> x y exclusion cut_off model controls method p.value effect.size
#> <chr> <chr> <chr> <chr> <chr> <lgl> <chr> <dbl> <dbl>
#> 1 cs:time scr full data full data rep ANO… NA rep A… 3.70e-9 0.0244
#> # … with 11 more variables: effect.size.lci <dbl>, effect.size.hci <dbl>,
#> # effect.size.ma <dbl>, effect.size.ma.lci <dbl>, effect.size.ma.hci <dbl>,
#> # estimate <lgl>, statistic <dbl>, conf.low <lgl>, conf.high <lgl>,
#> # framework <chr>, data_used <list>
# Repeated measures ANOVA with groups
rm_anova_mf(cs1 = cs1, cs2 = cs2, subj = subj, group = "group",
data = example_data, time = TRUE)
#> # A tibble: 1 × 20
#> x y exclusion cut_off model controls method p.value effect.size
#> <chr> <chr> <chr> <chr> <chr> <lgl> <chr> <dbl> <dbl>
#> 1 group:cs:ti… scr full data full d… rep … NA rep A… 0.205 0.00148
#> # … with 11 more variables: effect.size.lci <dbl>, effect.size.hci <dbl>,
#> # effect.size.ma <dbl>, effect.size.ma.lci <dbl>, effect.size.ma.hci <dbl>,
#> # estimate <lgl>, statistic <dbl>, conf.low <lgl>, conf.high <lgl>,
#> # framework <chr>, data_used <list>