This semantic-priming experiment was reported in Masson, Rabe, & Kliegl (2017, Exp. 1, Memory & Cognition). It is a direct replication of an experiment reported in Masson & Kliegl (2013, Exp. 1, JEPLMC). Following a prime word a related or unrelated high- or low-frequency target word or a nonword was presented in clear or dim font. The subject’s task was to decide as quickly as possible whether the target was a word or a nonword, that is subjects performed a lexical decision task (LDT). The reaction time and the accuracy of the response were recorded.
Seventy-three subjects participated in the experiment. Following 32 practice trials (not included in data), the experiment comprised 480 trials with breaks after blocks of 48 trials. Experimental conditions were presented in eight different random orders.
The file MRK17_Exp1.csv contains 35040 (= 480 * 73) observations of the 10 variables
| Variable | Description |
|---|---|
| Subj | Subject identifier (S01 to S73) |
| CC | Eight different random trial sequences (cc1 to cc8); between-subject factor; not used |
| trial | Trial number (1 to 480 for each subject, performed in 10 blocks of 48) |
| Q | Target quality is clear (clr) or degraded (deg) |
| F | Target is nonword (NW), high frequency (HF) or low frequency (LF) |
| P | Prime word is related (rel) or unrelated (unr) to target |
| Pword | Prime word; not used |
| Item | Target word or nonword |
| rt | Reaction time [ms] |
| Score | Response was correct (C) or error (E) |
For the analyses described in this package, the observations were restricted to correct responses to word targets with response times in the range 300 ms. to 3000 ms. Responses outside that range are assumed to be spurious. In addition to the variables described above lagged target type (lT - either word (WD) or nonword (NW)) and lagged quality (lQ) were added to the analysis data set. The first trial in each block (i.e. the trial number has a remainder of 1 when divided by 48) is dropped because these lagged variables cannot be evaluated.
The resulting data set consists of 16409 observations of 9 variables.
The data are read and prepared for analysis using R in DataPrep.Rmd with the analysis data set being saved in RDS format as MRK17_Exp1.rds. This file can be read in Julia using either the RData or RCall packages. (At present it seems safer to use RCall.)
The original CSV file is read and prepared for analysis with Julia directly in DataPrep.jmd.