statistical test in r to show significant difference between groups

Question

I am working with small scale survey data in r.

I would be grateful for input on what would be best/most simple test to use to show any row-wise significance between group differences for a series of options (opt1-opt9). When my data is grouped/aggregated it looks like this (respondents can multi select options):

opt	group1_count	group1_percent	group2_count	group2_percent	diff_%
opt1	14	0.081395349	17	0.042821159	0.038574
opt2	23	0.13372093	59	0.14861461	-0.01489
opt3	29	0.168604651	65	0.16372796	0.004877
opt4	6	0.034883721	6	0.01511335	0.01977
opt5	2	0.011627907	7	0.017632242	-0.006
opt6	38	0.220930233	88	0.221662469	-0.00073
opt7	37	0.215116279	98	0.246851385	-0.03174
opt8	11	0.063953488	25	0.062972292	0.000981
opt9	12	0.069767442	32	0.080604534	-0.01084

Would a t-test be valid here to show whether there are significant differences between group 1 and group 2? If yes, is there a simple way of generating this row wise in r? If not, do you have any suggestions?

Here is first 3 rows as dput:

structure(list(opt = c("opt1", "opt2", "opt3"), group1_count = c(14, 
23, 29), group1_percent = c(0.081395349, 0.13372093, 0.168604651
), group2_count = c(17, 59, 65), group2_percent = c(0.042821159, 
0.14861461, 0.16372796), percent_diff = c(0.03857419, -0.01489368, 
0.00487669099999999)), row.names = c(NA, -3L), class = c("tbl_df", 
"tbl", "data.frame"))

Many thanks

David M. · Answer 1 · 2021-02-18T13:15:11.480

If you only want to compare the two groups in the first row, you can carry out a two-proportion z-test. For instance in R:

result <- prop.test(x = c(14, 17), n = c(172, 397))

where 172 = sum(group1_count) and 397 = sum(group2_count)

Output:

2-sample test for equality of proportions with continuity correction

data:  c(14, 17) out of c(172, 397)
X-squared = 2.758, df = 1, p-value = 0.09677
alternative hypothesis: two.sided
95 percent confidence interval:
 -0.01105128  0.08819966
sample estimates:
    prop 1     prop 2 
0.08139535 0.04282116

If you want to compare your proportions all at once, you can use a chi-square test:

data <- as.table(cbind(c(14, 23, 29, 6, 2, 38, 37, 11, 12),
                       c(17, 59, 65, 6, 7, 88, 98, 25, 32)))

chisq <- chisq.test(data, simulate.p.value = TRUE)

Output:

Pearson's Chi-squared test with simulated p-value (based on 2000 replicates)

data:  data
X-squared = 6.671, df = NA, p-value = 0.5787

statistical test in r to show significant difference between groups

1 Answers1