Specify a minimum number of trajectories that each subject must complete during a treatment, trial, or session.
rm_by_trajnum( obj_name, trajnum = 5, mirrored = FALSE, treatment1, treatment2, ... )
obj_name | The input viewr object; a tibble or data.frame with attribute
|
---|---|
trajnum | Minimum number of trajectories; must be numeric. |
mirrored | Does the data have mirrored treatments? If so, arguments
|
treatment1 | The first treatment or session during which the threshold must be met. |
treatment2 | A second treatment or session during which the threshold must be met. |
... | Additional arguments passed to/from other pathviewR functions. |
A viewr object; a tibble or data.frame with attribute
pathviewR_steps
that includes "viewr"
that now has fewer
observations (rows) as a result of removal of subjects with too few
trajectories according to the trajnum
parameter.
Depending on analysis needs, users may want to remove subjects that
have not completed a certain number of trajectories during a treatment,
trial, or session. If mirrored = FALSE
, no treatment information is
necessary and subjects will be removed based on total number of trajectories
as specified in trajnum
. If mirrored = TRUE
, the
treatment1
and treatment2
parameters will allow users to
define during which treatments or sessions subjects must reach threshold as
specified in the trajnum
argument. For example, if mirrored =
TRUE
, setting treatment1 = "latA"
, treatment2 = "latB"
and
trajnum = 5
will remove subjects that have fewer than 5 trajectories
during the "latA"
treatment AND the "latB"
treatment.
treatment1
and treatment2
should be levels within a column
named "treatment"
.
Melissa S. Armstrong
library(pathviewR) ## Import the example Motive data included in the package motive_data <- read_motive_csv(system.file("extdata", "pathviewR_motive_example_data.csv", package = 'pathviewR')) ## Clean, isolate, and label trajectories motive_full <- motive_data %>% clean_viewr(desired_percent = 50, max_frame_gap = "autodetect", span = 0.95)#>##Remove subjects that have not completed at least 150 trajectories: motive_rm_unmirrored <- motive_full %>% rm_by_trajnum(trajnum = 150)#>## Add treatment information motive_full$treatment <- c(rep("latA", 100), rep("latB", 100), rep("latA", 100), rep("latB", 149)) ## Remove subjects by that have not completed at least 10 trajectories in ## both treatments motive_rm_mirrored <- motive_full %>% rm_by_trajnum( trajnum = 10, mirrored = TRUE, treatment1 = "latA", treatment2 = "latB" )#>