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# Pre-loaded data info
# path describes where to find the data
# varnames are the Phase identifier variable name, Outcome variable name, and then any number of clustering variable names
# phase vals are the values corresponding to the baseline and treatment phase, respectively
# direction describes direction type
# direction_var is the name of the variable that applies the direction.
example_list <- c("McKissick et al. (2010)" = "McKissick",
"Schmidt (2007)" = "Schmidt2007",
"Wright & McCathren (2012)" = "Wright2012",
"Olszewski et al. (2017)" = "Olszewski2017")
exampleMapping <- list(
Schmidt2007 = list(condition = "Condition",
outcome = "Outcome",
cluster_vars = c("Case_pseudonym", "Behavior_type"),
aggregate_vars = c("Phase_num"),
phase_vals = c("A", "B"),
direction = "series",
direction_var = "direction",
session_num = "Session_number",
scale = "series",
scale_var = "Metric",
intervals = "n_Intervals",
observation_length = "Session_length"),
McKissick = list(condition = "Condition",
outcome = "Outcome",
cluster_vars = "Case_pseudonym",
phase_vals = c("A", "B"),
direction = "decrease",
session_num = "Session_number",
scale = "count",
intervals = NA,
observation_length = "Session_length"),
Wright2012 = list(condition = "Condition",
outcome = "Prosocial_behavior",
cluster_vars = "Participant",
phase_vals = c("baseline", "intervention A", "intervention B"),
direction = "increase",
session_num = "Session",
scale = "count",
intervals = NA,
observation_length = NA),
Olszewski2017 = list(condition = "phase",
outcome = "score",
cluster_vars = "behavior",
phase_vals = c("A", "B"),
direction = "increase",
session_num = "session",
scale = "count",
intervals = NA,
observation_length = NA)
)
single_series_min_data_points_msg <- "Please enter at least three data points in each phase."
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