I have the following code for the Alpha calculation:

df <- tibble::tribble(

~seq, ~date, ~sales,

1, "3/01/2017", 40,

2, "4/01/2017", 2,

3, "5/01/2017", 2,

4, "6/01/2017", 2,

5, "7/01/2017", 30,

6, "8/01/2017", 2,

7, "1/02/2017", 9,

8, "2/02/2017", 5,

9, "3/02/2017", 65,

10, "4/02/2017", 3,

11, "5/02/2017", 65

)

library(tidyverse)

library(magrittr)

library(psy)

df %<>% mutate(lagsales = lag(sales))

df2 <- rowwise(df) %>% mutate(z = cronbach(cbind(sales,lagsales))$alpha) %>% ungroup

df2

It creates the following output:

df2

seq date sales lagsales z

1 1 3/01/2017 40 NA -1.232498

2 2 4/01/2017 2 40 -1.232498

3 3 5/01/2017 2 2 -1.232498

4 4 6/01/2017 2 2 -1.232498

5 5 7/01/2017 30 2 -1.232498

6 6 8/01/2017 2 30 -1.232498

7 7 1/02/2017 9 2 -1.232498

8 8 2/02/2017 5 9 -1.232498

9 9 3/02/2017 65 5 -1.232498

10 10 4/02/2017 3 65 -1.232498

11 11 5/02/2017 65 3 -1.232498

Question:

I am looking to get the Alpha for overlap for every 2nd line

Can I use this formula to calc Chronbachs Alpha for each item?;

Reliability = N / ( N - 1)x(Total Variance - Sum of Variance for Each number)/Total Variance

So I would not have – 1.232498 for every item.Only probably for item 1and 2 together.but 2 and 3 would have another alpha and 3 and 4 together would also have another alpha .etc.et. it has to look at row level and taking 2 rows rolling into consideration.

What would the R code look like?