select_cases | R Documentation |
Select sample for further sudden gains analyses depending on specified methods.
The following table shows the different data patterns that get selected when method = "pattern"
.
This function goes through the data and selects all cases with at least one of the following data patterns.
Pattern | x1 | x2 | x3 | x4 | x5 | x6 |
1. | x | N | x | x | . | . |
2. | x | N | x | . | x | . |
3. | x | . | N | x | x | . |
4. | x | . | N | x | . | x |
Note. x1 to x6 are consecutive data points of the primary outcome measure. 'x' = Available data; '.' = Missing data. 'N' represents available data to be examined as a possible pregain session.
select_cases( data, id_var_name, sg_var_list, method = c("pattern", "min_sess"), min_sess_num = NULL, return_id_lgl = FALSE )
data |
A dataset in wide format with an id variable and the sudden gains variables. |
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. |
method |
String, specifying the method used to select cases: |
min_sess_num |
Numeric, minimum number of available sessions to be selected.
This argument needs to be specified if |
return_id_lgl |
Logical, if |
A wide dataset indicating with all cases and a variable indicating whether each cases provides enough data to identify sudden gains.
# 1. method = "pattern" select_cases(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"), method = "pattern", return_id_lgl = FALSE) # 2. method = "min_sess" select_cases(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"), method = "min_sess", min_sess_num = 9, return_id_lgl = TRUE)
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