I have a dataset with three columns
The first column is ID
The second column is Intervention with two levels : Pre, Post
The third column is Response with 5 levels : strongly disagree, disagree, neutral, agree, strongly agree
RecordId Intervention Response
26 Post neutral
26 Pre agree
27 Post Strongly Agree
27 Pre strongly disagree
29 Post neutral
. . .
. . .
. . .
The actual dataset is below
df <- structure(list(record_id = c(26, 26, 27, 27, 29, 29, 30, 30,
33, 33, 34, 34, 36, 36, 39, 39, 40, 40, 42, 42, 44, 44, 45, 45,
46, 46, 49, 49, 50, 50, 52, 52, 53, 53, 55, 55), Intervention = c("Post",
"Pre", "Post", "Pre", "Post", "Pre", "Post", "Pre", "Post", "Pre",
"Post", "Pre", "Post", "Pre", "Post", "Pre", "Post", "Pre", "Post",
"Pre", "Post", "Pre", "Post", "Pre", "Post", "Pre", "Post", "Pre",
"Post", "Pre", "Post", "Pre", "Post", "Pre", "Post", "Pre"),
Response = structure(c(3L, 4L, 5L, 1L, 3L, 5L, 5L, 5L, 4L,
5L, 3L, 2L, 4L, 4L, 4L, 5L, 2L, 5L, 4L, 4L, 3L, 4L, 1L, 1L,
2L, 5L, 2L, 2L, 5L, 5L, 4L, 4L, 4L, 4L, 3L, 4L), .Label = c("strongly disagree",
"disagree", "neutral", "agree", "strongly agree"), class = c("labelled",
"factor"), label = "")), .Names = c("record_id", "Intervention",
"Response"), row.names = c(1L, 2L, 3L, 4L, 6L, 7L, 8L, 9L, 12L,
13L, 14L, 15L, 17L, 18L, 21L, 22L, 23L, 24L, 26L, 27L, 29L, 30L,
31L, 32L, 33L, 34L, 37L, 38L, 39L, 40L, 42L, 43L, 44L, 45L, 47L,
48L), class = "data.frame")
How do I convert this to a 5 x 5 matrix like this below
Post
Pre StronglyAgree Agree Neutral Disagree StronglyDisagree
StronglyAgree --- --- --- --- ---
Agree --- --- --- --- ---
Neutral --- --- --- --- ---
Disagree --- --- --- --- ---
StronglyDisagree --- --- --- --- ---
If I understand you correctly, this may work:
library(dplyr)
library(tidyr)
df %>%
pivot_wider(record_id, names_from = Intervention, values_from = Response) %>%
select(Pre, Post) %>%
table()
# Post
# Pre strongly disagree disagree neutral agree strongly agree
# strongly disagree 1 0 0 0 1
# disagree 0 1 1 0 0
# neutral 0 0 0 0 0
# agree 0 0 3 4 0
# strongly agree 0 2 1 2 2
You can also use spread in the same way:
df %>%
spread(Intervention, Response) %>%
select(Pre, Post) %>%
table()