CODEWITHSUNDEEP
r
rose
rose

Reputation: 11

How to make a Cross Tabulations in r

I have this data frame:

ID <- c(1,1,2,3,3,3,4,5,6,6)

linguistic_fluency <- c("good", "very good", "bad", "bad", "very bad", "very good", "good", "very good", "normal", "very bad")

survey_year <- c(2007, 2008, 2009, 2009, 2008, 2007, 2007, 2008, 2007, 2008)

data <- data.frame(ID, linguistic_fluency, survey_year)

I would like to check whether the participants of the survey report their linguistic fluency consistently over years. Therefore, I would like to have the following table where the column is in t-1, and the row is in t.

enter image description here

I really appreciate your help. Thank you.

Upvotes: 1

Views: 69

Answers (1)

Niek
Niek

Reputation: 1624

You could lag the variable and then make a frequency table. For example:

# Re-order the factor levels first     
data$linguistic_fluency <- factor(data$linguistic_fluency, 
levels = c("very bad","bad","normal","good","very good"))

library(Hmisc) # load library containing Lag() function

# apply function to each student
data$Lag_fluency <- unlist(tapply(data$linguistic_fluency, data$ID,function(x) Lag(x,1))) 

# resulting in the following data frame. Some respondents only have one observation, 
# the Lag() function returns NA for these respondents
> data
   ID linguistic_fluency survey_year Lag_fluency
1   1               good        2007        <NA>
2   1          very good        2008        good
3   2                bad        2009        <NA>
4   3                bad        2009        <NA>
5   3           very bad        2008         bad
6   3          very good        2007    very bad
7   4               good        2007        <NA>
8   5          very good        2008        <NA>
9   6             normal        2007        <NA>
10  6           very bad        2008      normal

Then all you need is a frequency table between the original and lagged variable:

> table(data$Lag_fluency, data$linguistic_fluency)

            very bad bad normal good very good
  very bad         0   0      0    0         1
  bad              1   0      0    0         0
  normal           1   0      0    0         0
  good             0   0      0    0         1
  very good        0   0      0    0         0

Upvotes: 1

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