quasif dataset

Simulated data set with subjects and items requiring quasi-F ratios

Simulated lexical decision latencies with SOA as treatment, traditionally requiring an analysis using quasi-F ratios, as available in Raaijmakers et al. (1999). data

data(quasif)

Format

A data frame with 64 observations on the following 4 variables.

• Subject: a factor coding subjects.

• RT: a numeric vector for simulated reaction times in lexical decision.

• Item: a factor coding items.

• SOA: a factor coding SOA treatment with levels long

   and `short`.
  

Source

Raaijmakers, J.G.W., Schrijnemakers, J.M.C. & Gremmen, F. (1999) How to deal with "The language as fixed effect fallacy": common misconceptions and alternative solutions, Journal of Memory and Language, 41, 416-426.

Examples

## Not run:

data(quasif)
items.quasif.fnc(quasif)
## End(Not run)