eyetrackingR

analyze_time_bins()

Description

Runs a test on each time-bin of time_sequence_data. Supports t.test, wilcox.test, (g)lm, and (g)lmer. Also includes support for the "bootstrapped-splines" test (see ?make_boot_splines_data and the divergence vignette for more info). By default, this function uses 'proportion-looking' (Prop) as the DV, which can be changed by manually specifying the formula. Results can be plotted to see how test-results or parameters estimates vary over time. P-values can be adjusted for multiple comparisons with p_adjust_method.

Usage

analyze_time_bins(data, ...)

## S3 method for class 'time_sequence_data'
analyze_time_bins(data, predictor_column, test,
  threshold = NULL, alpha = NULL, aoi = NULL, formula = NULL,
  p_adjust_method = "none", quiet = FALSE, ...)

Arguments

data	The output of the 'make_time_sequence_data' function
...	Any other arguments to be passed to the selected 'test' function (e.g., paired, var.equal, etc.)
predictor_column	The variable whose test statistic you are interested in. If you are not interested in a predictor, but the intercept, you can enter "intercept" for this argument. Interaction terms are not currently supported.
test	What type of test should be performed in each time bin? Supports t.test, wilcox.test, (g)lm, and (g)lmer. Also includes support for the "bootstrapped-splines" test (see ?make_boot_splines_data and the divergence vignette for more info).
threshold	Value of statistic used in determining significance
alpha	Alpha value for determining significance, ignored if threshold is given
aoi	Which AOI should be analyzed? If not specified (and dataframe has multiple AOIs), then AOI should be a predictor/covariate in your model (so 'formula' needs to be specified).
formula	What formula should be used for the test? Optional for all but (g)lmer, if unset will use Prop ~ [predictor_column]. Change this if you want to use a custom DV.
p_adjust_method	Method to adjust p.values for multiple corrections (default="none"). See p.adjust.methods.
quiet	Should messages and progress bars be suppressed? Default is to show

Value

A dataframe indicating the results of the test at each time-bin.

Methods (by class)

• time_sequence_data:

Examples

data(word_recognition)
data <- make_eyetrackingr_data(word_recognition, 
                               participant_column = "ParticipantName",
                               trial_column = "Trial",
                               time_column = "TimeFromTrialOnset",
                               trackloss_column = "TrackLoss",
                               aoi_columns = c('Animate','Inanimate'),
                               treat_non_aoi_looks_as_missing = TRUE
)
response_time <- make_time_sequence_data(data, time_bin_size = 250, 
                                         predictor_columns = c("MCDI_Total"),
                                         aois = "Animate", summarize_by = "ParticipantName")
tb_analysis <- analyze_time_bins(response_time, predictor_column = "MCDI_Total", 
                                 test = "lm", threshold = 2)
summary(tb_analysis)