View source: R/preprocess_data.R
preprocess_data | R Documentation |
Performs sanity checks (e.g., whether data
can be used as a data.frame),
computes duration of dominance phases (if necessary), assumes a single entry for
any missing session
, run
, random_effect
.
preprocess_data(
data,
state,
duration = NULL,
onset = NULL,
random_effect = NULL,
session = NULL,
run = NULL
)
data |
A table with one or many time-series. |
state |
String, the name of the column that specifies perceptual state. The column type should be a factor with two or three levels (the third level is assumed to correspond to a transition/mixed phase) or should be convertible to a two level factor (as it would be impossible to infer the identity of transition/ mixed phase). |
duration |
String, name of the column with duration of individual
perceptual dominance phases. Optional, you can specify |
onset |
String, name of the column with onsets of the perceptual
dominance states. Optional, used to compute duration of the dominance
phases, if these are not provided explicitly via |
random_effect |
String, name of the column that identifies random effect, e.g. individual participants, stimuli for a single participant, etc. If omitted, no random effect is assumed. If specified and there is more than one level (participant, stimulus, etc.), it is used in a hierarchical model. |
session |
String, name of the column that identifies unique
experimental session for which a mean dominance phase duration will
be computed (see |
run |
String, name of the column that identifies unique runs/blocks. If omitted, the data is assumed to belong to a single time series. Code assumes that run IDs are different within an experimental session but can be the same between the session. E.g. session A, runs 1, 2, 3.. and session B, runs 1, 2, 3 but not session A, runs 1, 2, 1. |
A tibble with columns
state
duration
random
irandom
- integer, index of random
values,
session
run
session_tmean
- numeric, mean duration of clear percepts for every combination of random
and session
.
is_used
- integer, whether computed history value needs to be used for linear model fitting.
run_start
- integer, 1 for the first row of the run time-series.
df <- preprocess_data(br_singleblock, state="State", duration="Duration")
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