An example dataset with developmental scores at the item level for
50 random children from the GSED Validation Study (Cavellera et al, 2023).
Each child has measurements from GSED SF (gs1), GSED LF (gl1) and
BSID-III (by3).
tripleA data.frame with 50 rows and 559 variables:
| Name | Label |
id | Integer, child ID |
age | Numeric, age in decimal years |
agedays | Integer, age in days |
gs1sec001 | Integer, SF001 Does your child smile? |
gs1moc002 | Integer, SF002 When lying on his/her back, ... |
... | and so on.. |
The dataset contains 138 items from GSED SF (gs1),
(item gs1moc028 was skipped), 155 items from GSED LF (gl1),
and 263 (out of 326) items from BSID-III (by3).
Cavallera et al. (2023). Protocol for validation of the Global Scales for Early Development (GSED) for children under 3 years of age in seven countries. BMJ Open, 13(1), e062562. DOI: 10.1136/bmjopen-2022-062562. https://bmjopen.bmj.com/content/13/1/e062562
World Health Organization (WHO) (2023). Global Scales for Early Development (GSED) V1.0: Technical Report. Geneva: World Health Organization. https://www.who.int/publications/i/item/WHO-MSD-GSED-package-v1.0-2023.1
# calculate D-score from all instruments
ds_all <- dscore(triple)
head(ds_all)
#> a n p d sem daz
#> 1 1.9493 200 0.6050 66.62 0.6909583 0.527
#> 2 2.5325 147 0.6463 73.00 0.7293837 0.509
#> 3 2.3874 163 0.5153 64.92 0.7418813 -1.200
#> 4 0.8980 274 0.4124 43.78 0.8729957 -0.862
#> 5 2.1903 150 0.4533 59.58 0.7704544 -1.933
#> 6 0.8980 216 0.6759 51.06 0.7463839 1.380
# calculate D-score from only GSED SF items
ds_sf <- dscore(triple, items = get_itemnames(instrument = "gs1"))
head(ds_sf)
#> a n p d sem daz
#> 1 1.9493 65 0.6769 68.95 1.210561 1.186
#> 2 2.5325 34 0.7059 73.23 1.458141 0.572
#> 3 2.3874 36 0.5833 65.89 1.404537 -0.966
#> 4 0.8980 8 0.5000 38.64 2.527097 -2.228
#> 5 2.1903 31 0.2258 57.84 1.605532 -2.289
#> 6 0.8980 80 0.7625 54.78 1.325298 2.517