rankByGroup {cNORM} | R Documentation |
This is the initial step, usually done in all kinds of test norming projects, after the scale is constructed and the norm sample is established. First, the data is grouped according to a grouping variable and afterwards, the percentile for each raw value is retrieved. The percentile can be used for the modeling procedure, but in case, the samples to not deviate too much from normality, T, IQ or z scores can be computed via a normal rank procedure based on the inverse cumulative normal distribution. In case of bindings, we use the medium rank and there are different methods for estimating the percentiles (default RankIt).
rankByGroup(data, group = "group", raw = "raw", method = 4, scale = "T", descend = FALSE, descriptives = TRUE)
data |
data.frame with norm sample data |
group |
name of the grouping variable (default 'group'), e. g. grade, setting group to FALSE cancels grouping (data is treated as one group) |
raw |
name of the raw value variable (default 'raw') |
method |
Ranking method in case of bindings, please provide an index, choosing from the following methods: 1 = Blom (1958), 2 = Tukey (1949), 3 = Van der Warden (1952), 4 = Rankit (default), 5 = Levenbach (1953), 6 = Filliben (1975), 7 = Yu & Huang (2001) |
scale |
type of norm scale, either T (default), IQ, z or percentile (= no transformation); a double vector with the mean and standard deviation can as well, be provided f. e. c(10, 3) for Wechsler scale index points |
descend |
ranking order (default descent = FALSE): inverses the ranking order with higher raw scores getting lower norm scores; relevant for example when norming error scores, where lower scores mean higher performance |
descriptives |
If set to TRUE (default), information in n, mean, median and standard deviation per group is added to each observation |
the dataset with the percentiles and norm scales per group
rankBySlidingWindow, computePowers
#Transformation with default parameters: RandIt and converting to T scores data.elfe <- rankByGroup(elfe, group = "group") #Transformation into Wechsler scores with Yu & Huang (2001) ranking procedure data.elfe <- rankByGroup(elfe, group = "group", method = 7, scale=c(10, 3))