I've been working on a data analysis with no hick-ups whatsoever. But when I try to find the Cronbach's alpha for certain(!) variable combinations - R insists that the data length is not a multiple of the number of columns
.
Here is one example:
PsycLoc <- subset(SCWB,select=c(Belong_2, Belong_3))
PSYCLOC <-data.matrix(PsycLoc)
alpha(PSYCLOC, check.keys=TRUE)
Reliability analysis
Call: alpha(x = PSYCLOC, check.keys = TRUE)
raw_alpha std.alpha G6(smc) average_r S/N ase mean sd median_r
0.69 0.69 0.53 0.53 2.2 0.017 8.1 1.8 0.53
lower alpha upper 95% confidence boundaries
0.66 0.69 0.72
Reliability if an item is dropped:
raw_alpha std.alpha G6(smc) average_r S/N alpha se var.r med.r
Belong_2 0.53 0.53 0.28 0.53 NA NA 0.53 0.53
Belong_3 0.28 0.53 NA NA NA NA 0.28 0.53
To give you an idea of data distribution, this is SCWB$Belong_2
1 2 3 4 5 6 7 8 8.211 9 10
18 11 13 25 82 95 135 275 15 156 527
And this is SCWB$Belong_3
1 2 3 4 5 6 7 7.992 8 9 10
20 20 19 26 105 82 159 28 269 161 463
I do receive an alpha (0.69). Is this alpha valid? Can I just ignore the warning message and continue with the data analysis? Would it mess with the integrity of a follow up Principal Component Analysis?
If the warning message IS detrimental - how can I fix this problem? Thank you for your advice
the message is indeed not exactly informative (related to something in the psych::alpha
computation)... but you are getting this result because you are loading Cronbach alpha with just 2 items. You need to have at least 3 items...