View source: R/count_intervals.R
count_intervals | R Documentation |
Calculates the number of total between-session intervals present in the data set and the number of between-session intervals that are available to identify sudden gains talking into account the pattern of missing data.
count_intervals(data, id_var_name, sg_var_list, identify_sg_1to2 = FALSE)
data |
A data set in wide format including an ID variable and variables for each measurement point. |
id_var_name |
String, specifying the name of the ID variable. Each row should have a unique value. |
sg_var_list |
Vector, specifying the variable names of each measurement point sequentially. |
identify_sg_1to2 |
Logical, indicating whether to identify sudden losses from measurement point 1 to 2.
If set to TRUE, this implies that the first variable specified in |
List with values for:
total_between_sess_intervals: The total number of between-session intervals present in the data set, NAs are also included here. This multiplies the number of cases (rows) with the number of specified between-session intervals: nrows * (length(sg_var_list) - 1)
.
total_between_sess_intervals_sg: The total number of between-session intervals where sudden gains can theoretically, NAs are also included here. This multiplies the number of cases (rows) with the number of between-session intervals where sudden gains can be identified using the 3 original criteria: nrows * (length(sg_var_list) - 3)
.
available_between_sess_intervals_sg: The total number of between-session intervals that can be analysed for sudden gains taking into account the pattern of missing data.
not_available_between_sess_intervals_sg: The total number of between-session intervals that can not be analysed for sudden gains due to the pattern of missing data.
# Count between session intervals in "sgdata" count_intervals(data = sgdata, id_var_name = "id", sg_var_list = c("bdi_s1", "bdi_s2", "bdi_s3", "bdi_s4", "bdi_s5", "bdi_s6", "bdi_s7", "bdi_s8", "bdi_s9", "bdi_s10", "bdi_s11", "bdi_s12"))
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