Error in NiPN data quality toolkit

[ernestguevarra]

I found a bug in the outliersUV() function in the NiPN data quality toolkit that can prevent calls such as:

svy[outliersUV(svy$muac), ]

from returning the correct set of records when there are NA values in the variable being tested.

I found this when using the toolkit with a dataset from MSF that had NA for all anthropometry when oedema was present. This may be a common case.

Here is an example of the problem using the example dataset in the NiPN toolkit:

svy <- read.table("rl.ex01.csv", header = TRUE, sep = ",")
head(svy)
## Test function
svy[outliersUV(svy$muac), ]

This gives:

Univariate outliers : Lower fence = 98, Upper fence = 178

	age	sex	weight	height	muac	oedema
33	24	1	9.8	74.5	180.0	2
93	12	2	6.7	67.0	96.0	1
126	16	2	9.0	74.6	999.0	2
135	18	2	8.5	74.5	999.0	2
194	24	M	7.0	75.0	95.0	2
227	8	M	6.2	66.0	11.1	2
253	35	2	7.6	75.6	97.0	2
381	24	1	10.8	82.8	12.4	2
501	36	2	15.5	93.4	185.0	2
594	21	2	9.8	76.5	13.2	2
714	59	2	18.9	98.5	180.0	2
752	48	2	15.6	102.2	999.0	2
756	59	1	19.4	101.1	180.0	2
873	59	1	20.6	109.4	179.0	2

Note that the values in the muac column are all outside of the fences. This is correct.

Adding a missing value:

## Add a missing value
svy$muac[1] <- NA
head(svy)
## Test function
svy[outliersUV(svy$muac), ]

gives us:

Univariate outliers : Lower fence = 98, Upper fence = 178

	age	sex	weight	height	muac	oedema
32	24	2	8.2	68.7	139	2
92	14	F	7.2	70.6	109	2
125	12	1	8.8	70.6	124	2
134	18	M	7.9	73.1	114	2
193	24	1	8.3	77.1	116	2
226	12	2	9.6	79.2	133	2
252	15	1	11.5	79.2	154	2
380	32	1	11.8	82.6	142	2
500	36	2	11.8	90.0	136	2
593	59	2	13.3	97.5	146	2
713	59	2	13.1	99.3	126	2
751	59	1	16.5	101.1	154	2
755	59	2	14.9	104.4	143	2
872	59	1	15.9	109.5	139	2

The listed records do not contain outliers. This is wrong.