Show percentiles of Variable A, while the classification of percentiles is based on Variable B

Question

I have a dataset that looks like the following:

INCOME	WEALTH
10.000	100000
15.000	111000
14.200	123456
12.654	654321

I have many more rows.

I now want to now find how much INCOME a household in a specific WEALTH percentile has. The following quantiles are relevant:

c(0.01,0.05,0.1,0.25,0.5,0.75,0.9,0.95,0.99)

I have always used the following code to get specific percentile values:

a <- quantile(WEALTH, probs = c(0.01,0.05,0.1,0.25,0.5,0.75,0.9,0.95,0.99))

But now I want to base my percentiles on WEALTH but get the respective INCOME. I have tried the following code but the results are not plausible:

df$percentile = ntile(df$WEALTH,100)
df <- df[df$percentile %in% c(1,5,10,25,50,75,90,95,99), ]

a <- df %>% 
  group_by(percentile) %>% 
  summarise(max = max(INCOME))

The results that I get a not consistent with other parts of the analysis that I have done. I assume that the percentile when using the "quantile" function are calculated differently that simply taking the maximum.

Answer 1

Im not sure if i understood your question correctly, but the quantile has different methods of calculation. I for example always go for number 6, since this is what i was taought in my stat courses.

type: an integer between 1 and 9 selecting one of the nine quantile algorithms detailed below to be used.

Read more about different types by using ?quantile commands (help on quantile)