mpt (version 0.5-4)

prospecMemory: Prospective Memory by Instruction Type

Description

Smith and Bayen (2004) tested the performance of 64 participants in an event-based prospective memory task that was embedded in a color-matching task. On each trial, participants were presented with four colored rectangles followed by a colored word. Their task was to press a key to indicate whether the color of the word matched one of the rectangles. Interspersed among these nontarget words were six target words for which subjects had to remember to press the tilde key (prospective memory response) regardless of the color. Participants received two different instruction types either stressing the importance of the color-matching (CMI) or of the prospective-memory task (PMI).

Usage

data(prospecMemory)

Format

A data frame consisting of five variables:

instruction

instruction type, either color-matching importance (cmi) or prospective memory importance (pmi).

item

a factor specifying one of four item types: either a target word that did or did not match the color of the rectangles, or a nontarget word that did or did not match.

resp

a factor giving the response categories: match, nonmatch, or the prospective memory response (prospec).

freq

the aggregate response frequencies per condition.

treeid

an identifier for the single trees of the joint multinomial model.

Examples

# NOT RUN {
## Prospective memory model: identifiability
qr(mptspec("prospec",
   .restr=list(M1=M, M2=M))$par2deriv(runif(6))$deriv)$rank
qr(mptspec("prospec",
   .restr=list(M1=M, M2=M, g=.1, c=.5))$par2deriv(runif(4))$deriv)$rank

## Prospective memory model: goodness of fit
data(prospecMemory)
cmi <- prospecMemory[prospecMemory$instruction == "cmi", ]
m2 <- mpt(mptspec("prospec", .restr=list(M1=M, M2=M, g=.1, c=.5)), cmi)
m1 <- mpt(update(m2$spec, .restr=list(C2=C1)), cmi)
anova(m1, m2)

pmi <- prospecMemory[prospecMemory$instruction == "pmi", ]
anova(mpt(m1$spec, pmi), mpt(m2$spec, pmi))

## Testing P_cmi = P_pmi and M_cmi = M_pmi
m2 <- mpt(mptspec("prospec", .replicates=2,
                  .restr=list(M11=M1, M21=M1, g1=.1, c1=.5,
                              M12=M2, M22=M2, g2=.1, c2=.5)),
          data=prospecMemory)
m1 <- mpt(update(m2$spec, .restr=list(P2=P1)), prospecMemory)
m0 <- mpt(update(m2$spec, .restr=list(M2=M1)), prospecMemory)
anova(m1, m2)
anova(m0, m2)

dotchart(coef(m2)[c("C12", "C22", "P2", "M2")], xlim=c(0, 1),
  labels=c("C1", "C2", "P", "M"), main="Smith and Bayen (2004, Exp. 1)",
  xlab="Parameter estimate (Prospective memory model)")
points(coef(m2)[c("C11", "C21", "P1", "M1")], 1:4, pch=16)
legend("bottomleft", c("CMI", "PMI"), pch=c(1, 16), title="Instruction",
       title.adj=1, bty="n")
# }