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Refer to the Rmd source code to see how to adapt this template to your project.
spec <- list()
spec[1:6] <- rpf.grm(factors=2)
## Warning in `[<-`(`*tmp*`, 1:6, value = new("rpf.mdim.grm", spec = c(2, 2, :
## implicit list embedding of S4 objects is deprecated
gen.param <- sapply(spec, rpf.rparam)
colnames(gen.param) <- paste("i", 1:ncol(gen.param), sep="")
gen.param[2,] <- c(0,0,.5,.5,1,1)
resp <- rpf.sample(1000, spec, gen.param)
# hide latent factor that we don't know about
tspec <- list()
tspec[1:length(spec)] <- rpf.grm(factors=1)
## Warning in `[<-`(`*tmp*`, 1:length(spec), value = new("rpf.mdim.grm", spec =
## c(2, : implicit list embedding of S4 objects is deprecated
grp <- list(spec=tspec, param=gen.param[-2,], mean=c(0), cov=diag(1), data=resp)
ChenThissen1997(grp)
## Chen & Thissen (1997) local dependence test
## Magnitudes larger than abs(log(.01))=4.6 are significant at the p=.01 level
## A positive (negative) sign indicates more (less) observed correlation than expected
##
## i1 i2 i3 i4 i5
## i2 -2.65 NA NA NA NA
## i3 1.25 2.67 NA NA NA
## i4 -2.39 2.99 3.11 NA NA
## i5 -2.74 -3.47 -0.86 8.36 NA
## i6 0.94 2.83 2.51 1.12 3.41
(got <- SitemFit(grp))
## Orlando & Thissen (2000) sum-score based item fit test
## Magnitudes larger than abs(log(.01))=4.6 are significant at the p=.01 level
##
## i1 : n = 1000, S-X2( 6) = 6.51, log(p) = -1
## i2 : n = 1000, S-X2( 6) = 6.99, log(p) = -1.13
## i3 : n = 1000, S-X2( 6) = 7.59, log(p) = -1.31
## i4 : n = 1000, S-X2( 6) = 3.13, log(p) = -0.23
## i5 : n = 1000, S-X2( 5) = 2.12, log(p) = -0.18
## i6 : n = 1000, S-X2( 5) = 4.32, log(p) = -0.69
Who can resist plotting these tables?
(got <- sumScoreEAP(grp))
## p a1 se1 cov1
## 0 0.177006547 -1.0022418 0.7508276 0.5637421
## 1 0.288513776 -0.4291543 0.7068011 0.4995677
## 2 0.263058519 0.1376443 0.6572072 0.4319213
## 3 0.157244624 0.6884698 0.6401668 0.4098135
## 4 0.080063208 1.2255142 0.6342668 0.4022944
## 5 0.029790612 1.6791792 0.6386705 0.4079001
## 6 0.004322714 1.9920902 0.6464811 0.4179379
data(science)
spec <- list()
spec[1:25] <- rpf.nrm(outcomes=3, T.c = lower.tri(diag(2),TRUE) * -1)
## Warning in `[<-`(`*tmp*`, 1:25, value = new("rpf.mdim.nrm", spec = c(3, :
## implicit list embedding of S4 objects is deprecated
param <- rbind(a=1, alf1=1, alf2=0,
gam1=sfif$MEASURE + sfsf[sfsf$CATEGORY==1,"Rasch.Andrich.threshold.MEASURE"],
gam2=sfif$MEASURE + sfsf[sfsf$CATEGORY==2,"Rasch.Andrich.threshold.MEASURE"])
colnames(param) <- sfif$NAME
iorder <- match(sfif$NAME, colnames(sfpf))
responses <- sfpf[,iorder]
rownames(responses) <- sfpf$NAME
rpf.1dim.fit(spec, param, responses, sfpf$MEASURE, 2, wh.exact=TRUE)
## Warning in rpf.1dim.fit(spec, param, responses, sfpf$MEASURE, 2, wh.exact =
## TRUE): Excluding item GO TO MUSEUM because outcomes != 3
## Warning in rpf.1dim.fit(spec, param, responses, sfpf$MEASURE, 2, wh.exact =
## TRUE): Excluding response ROSSNER, LAWRENCE F. because it is a minimum or
## maximum
## n infit infit.z outfit outfit.z
## 1 74 0.7334760 -1.93854363 0.6662677 -1.84016154
## 2 74 0.7557765 -1.49109930 0.5601381 -1.43788307
## 3 74 0.6562136 -2.62314065 0.6235471 -2.50977057
## 4 74 0.9885977 -0.02982227 0.9833379 -0.05803811
## 5 74 2.2854600 5.28398081 3.9687036 6.98045705
## 6 74 0.8806001 -0.79728007 0.8212982 -1.02012688
## 7 74 0.9694889 -0.16907311 1.0049137 0.08462788
## 8 74 1.1684407 1.13263699 1.2320360 1.40767658
## 9 74 1.1125813 0.82684751 1.1337003 0.75931289
## 10 74 0.7756357 -1.09399342 0.5617036 -1.14659113
## 11 74 0.7286889 -1.83371616 0.5881417 -1.68055554
## 12 74 0.8493121 -0.62542291 0.7008119 -0.43349100
## 13 74 0.8730059 -0.86823601 0.8058509 -1.13628429
## 14 74 0.7502023 -1.67364559 0.6057915 -1.69066099
## 15 74 1.0934249 0.65700883 1.0512049 0.36542993
## 16 74 0.6632654 -2.59174746 0.6005216 -2.35711937
## 17 74 1.2325992 0.58992208 1.1912748 0.50748517
## 18 74 0.9690502 0.02438538 1.0925458 0.35481861
## 19 74 1.3529043 2.12137594 1.7997411 3.71876933
## 20 74 0.7334508 -1.59075191 0.5470207 -1.51023199
## 21 74 0.8040046 -1.40104331 0.7127619 -1.48373014
## 22 74 2.3647156 5.80477994 4.6517042 8.53849619
## 23 74 0.7907684 -1.42062168 0.6910078 -1.22075027
## 24 74 0.7830659 -1.61643142 0.7215023 -1.66985954
## name
## 1 WATCH BIRDS
## 2 READ BOOKS ON ANIMALS
## 3 READ BOOKS ON PLANTS
## 4 WATCH GRASS CHANGE
## 5 FIND BOTTLES AND CANS
## 6 LOOK UP STRANGE ANIMAL OR PLANT
## 7 WATCH ANIMAL MOVE
## 8 LOOK IN SIDEWALK CRACKS
## 9 LEARN WEED NAMES
## 10 LISTEN TO BIRD SING
## 11 FIND WHERE ANIMAL LIVES
## 12 GROW GARDEN
## 13 LOOK AT PICTURES OF PLANTS
## 14 READ ANIMAL STORIES
## 15 MAKE A MAP
## 16 WATCH WHAT ANIMALS EAT
## 17 GO ON PICNIC
## 18 GO TO ZOO
## 19 WATCH BUGS
## 20 WATCH BIRD MAKE NEST
## 21 FIND OUT WHAT ANIMALS EAT
## 22 WATCH A RAT
## 23 FIND OUT WHAT FLOWERS LIVE ON
## 24 TALK W FRIENDS ABOUT PLANTS
head(rpf.1dim.fit(spec, param, responses, sfpf$MEASURE, 1, wh.exact=TRUE))
## Warning in rpf.1dim.fit(spec, param, responses, sfpf$MEASURE, 1, wh.exact =
## TRUE): Excluding item GO TO MUSEUM because outcomes != 3
## Warning in rpf.1dim.fit(spec, param, responses, sfpf$MEASURE, 1, wh.exact =
## TRUE): Excluding response ROSSNER, LAWRENCE F. because it is a minimum or
## maximum
## n infit infit.z outfit outfit.z name
## 1 24 0.9693598 -0.01898239 0.8675200 -0.2174955 ROSSNER, MARC DANIEL
## 2 24 0.4687608 -2.24283176 0.4341095 -1.3589919 ROSSNER, TOBY G.
## 3 24 0.7377522 -0.97658469 0.6784338 -0.8996851 ROSSNER, MICHAEL T.
## 4 24 0.7940946 -0.75849430 1.3987520 1.1557079 ROSSNER, REBECCA A.
## 5 24 1.6391409 2.12339795 2.5979105 3.4653767 ROSSNER, TR CAT
## 6 24 1.8561200 1.94796584 1.2288375 0.5464035 WRIGHT, BENJAMIN
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.