I am trying to calculate Cronbach alpha for an index of 5 different survey question. They are scaled identically, 0-10. I have created a matrix with the variable
I have 47000 observations, so the problem is not due to a lack of observations. When I use the psych package, I get less information than I would expect.
trust_alpha <- alpha(x = trust_ma)
trust_alpha
the output is:
Number of categories should be increased in order to count frequencies.
Reliability analysis
Call: alpha(x = trust_ma)
lower alpha upper 95% confidence boundaries
0.89 0.9 0.9
Reliability if an item is dropped:
Item statistics
I can't figure out what "Number of categories should be increased in order to count frequencies." means, and why I don't get the reliability if an item is dropped or item statistics. Is there a way, I can get this information?
I really appreciate any help you can provide.
EDIT
overview over the data with dput(head(trust))
structure(list(idno = c(27L, 137L, 194L, 208L, 220L, 254L), trstplt = c(5L,
3L, 5L, 3L, 7L, 5L), trstprt = c(5L, 4L, 5L, 3L, 7L, 5L), trstprl = c(5L,
7L, 6L, 0L, 7L, 6L), trstplc = c(10L, 8L, 8L, 8L, 8L, 7L), trstlgl = c(10L,
8L, 8L, 5L, 8L, 5L), trust_norris = c(7, 6, 6.4, 3.8, 7.4, 5.6
), trust_norris_na = c(0L, 0L, 0L, 0L, 0L, 0L)), row.names = c(NA,
-6L), groups = structure(list(.rows = structure(list(1L, 2L,
3L, 4L, 5L, 6L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame")), class = c("rowwise_df", "tbl_df", "tbl",
"data.frame"))
with head(trust)
head(trust)
# A tibble: 6 x 8
# Rowwise:
idno trstplt trstprt trstprl trstplc trstlgl trust_norris trust_norris_na
<int> <int> <int> <int> <int> <int> <dbl> <int>
1 27 5 5 5 10 10 7 0
2 137 3 4 7 8 8 6 0
3 194 5 5 6 8 8 6.4 0
4 208 3 3 0 8 5 3.8 0
5 220 7 7 7 8 8 7.4 0
6 254 5 5 6 7 5 5.6 0
idno is my ID variable, as it subset of a larger dataset, trust_norris is a reflexis index, that is the mean of trstplt, trstprt, trstprl, trstplc and trstlgl. trust_norris_na is a variable that describes how many NA there are in trstplt, trstprt, trstprl, trstplc and trstlgl pr. row.
I created a matrix of the relevant variables
trust_ma <- data.matrix(subset(trust, select = c(trstplt, trstprt, trstprl, trstplc, trstlgl)))