Calculate D-score

Once the data are in proper shape, calculation of the D-score is
straightforward. The hf dataset has properly named columns
that identify each item.

results <- dscore(hf, xname = "agedays", xunit = "days", key = "gsed2406")
head(results)

##        a  n      p     d      sem    daz
## 1 2.2204  8 0.7500 66.46 3.099626 -0.365
## 2 2.4586  8 1.0000 73.55 3.959115  0.862
## 3 0.5558 29 0.6207 37.36 2.190590  0.552
## 4 2.6448  3 1.0000 74.12 4.231796  0.528
## 5 2.1081  7 1.0000 70.72 3.841959  1.149
## 6 0.8378 30 0.7000 42.55 2.182150 -0.731

The key = "gsed2406" argument is needed here because
GSED HH is not yet supported by the default key
"gsed2510".

The table below provides the interpretation of the output:

The number of rows of results is equal to the number of
rows of hf. We save the result for later processing.

hf2 <- data.frame(hf, results)

It is possible to calculate D-score for item subsets by setting the
items argument. We do not advertise this option for
practical application, but suppose we are interested in the D-score
based on items from gs1, gl1 and
gh1 for domains mo or gm (motor)
only. The “motor” D-score can be calculated as follows:

items_motor <- get_itemnames(
  instrument = c("gs1", "gl1", "gh1"),
  domain = c("mo", "gm")
)
results <- dscore(
  hf,
  items = items_motor,
  xname = "agedays",
  xunit = "days",
  key = "gsed2406"
)
head(results)

##        a  n      p     d      sem    daz
## 1 2.2204  1 1.0000 69.63 4.504147  0.491
## 2 2.4586  1 1.0000 71.52 4.583980  0.306
## 3 0.5558 18 0.5000 36.65 2.506216  0.331
## 4 2.6448  1 1.0000 72.86 4.642396  0.189
## 5 2.1081  1 1.0000 68.67 4.467450  0.577
## 6 0.8378 18 0.6111 42.29 2.508751 -0.807

:::