From testing of risk parameter

[Kyoshido]

Hello, I was testing funkcionality of risk and risk_threshold parameter. In recordSwap() was parameter swaprate set to 0, because I wanted to test swapping only of risky values. But when checking which households were swapped, there was one non-risky household that was swapped. This issue is for somebody with enough time to dig up why it happened.

Data used:

seed <- 2021 set.seed(seed) nhid <- 10000 dat <- sdcMicro::createDat( nhid )

k_anonymity <- 0 swaprate <- .05 similar <- list(c("hsize")) hier <- c("nuts1","nuts2","nuts3") risk_variables <- c("ageGroup","national") hid <- "hid" expect_swaps <- swaprate nhid risk <- matrix(data = rep(0,3dim(dat)[1]), ncol = 3) set.seed(seed) index <- sample(1:(length(hier)*nrow(dat)), size = expect_swaps) risk[index] <- 99 # risk value risk_threshold <- 0.9

Then run recordSwap() function:

dat_s <- recordSwap( data = dat, hid = hid, hierarchy = hier, similar, risk = risk, # TESTING risk_threshold = risk_threshold, # TESTING carry_along = NULL, return_swapped_id = TRUE, seed=seed, swaprate = 0 # to test swaping based only on risk values ) risk does not contain column names; the first column in risk will be used for the first hierarchy level, e.g nuts1 and so on. risk was adjusted in order to give each household member the maximum household risk value Donor household was not found in 16 case(s). See TRS_logfile.txt for a detailed list

Following calculation of households that should be swapped

risk_check <- copy(data.table(risk)) risk_variables_names <- copy(colnames(risk_check)) risk_check[,hid_help:=dat[[5]]] # 5 = hid risk_check[,c(risk_variables_names):=lapply(.SD,max), .SDcols=c(risk_variables_names), by=.(hid_help)] # assign to each household its max value risk_check_uniq <- unique(risk_check) # calculate max value in household risk_check_uniq[, Sum := rowSums(.SD), .SDcols = 1:3] n_of_hd_to_swap <- sum(risk_check_uniq$Sum > 1) # number of households that should be swapped n_of_swapped_hd <- dat_s[hid != hid_swapped, uniqueN(hid)] # number of swapped households

n_of_hd_to_swap [1] 489 n_of_swapped_hd [1] 474

So what is difference in households

hd_to_swap <- risk_check_uniq$hid_help[risk_check_uniq$Sum > 1 ] # number of households that was should be swapped swapped_hd <- dat_s[hid != hid_swapped, unique(hid) ] # number of swapped households

Here are those 16 hd that could not find the donor household

hd_to_swap[which(!(hd_to_swap %in% swapped_hd))] # hd to swapp not in swapped hd [1] 1540 2823 3212 3588 3876 3996 4841 5717 5962 6885 7061 8621 9101 9168 9206 9257

Here is one non-risky household that was swapped. And the question is why?

swapped_hd[which(!(swapped_hd %in% hd_to_swap))] # swapped hd not in hd to swap [1] 10000

Here are data for this household

dat_s[which(dat_s$hid==10000),]

nuts1	nuts2	nuts3	lau2	hid	hsize	ageGroup	gender	national	htype	hincome	hid_swapped
3	34	3405	24075	10000	3	6	2	4	10	2	5064
3	34	3405	24075	10000	3	1	2	1	10	2	5064
3	34	3405	24075	10000	3	4	2	3	10	2	5064

Here are risk values for this household

risk_check[which(dat_s$hid==10000),]

V1	V2	V3	hid_help
0	0	0	10000
0	0	0	10000
0	0	0	10000

On recomendation of @JohannesGuss I created this issue. Whole script can be found in attachment. script_issue.docx