Diagnostic tests
Refer to the Rmd source code to see how to adapt thistemplate to your project.
Pair-wise local dependence test
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 deprecatedgen.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 abouttspec <- 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 deprecatedgrp <- 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 0.00 NA NA NA NA## i3 0.10 0.10 NA NA NA## i4 1.08 1.10 1.12 NA NA## i5 0.31 0.31 0.95 1.76 NA## i6 9.13 9.10 10.62 11.31 11.99Sum-score item fit test
(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( 1) = 0.00, log(p) = -0.04## i2 : n = 1000, S-X2( 1) = 0.01, log(p) = -0.07## i3 : n = 1000, S-X2( 4) = 0.84, log(p) = -0.07## i4 : n = 1000, S-X2( 4) = 3.07, log(p) = -0.6## i5 : n = 1000, S-X2( 4) = 2.76, log(p) = -0.51## i6 : n = 1000, S-X2( 4) = 23.05, log(p) = -9Who can resist plotting these tables?
Sum-score EAP table
(got <- sumScoreEAP(grp))## p a1 se1 cov1## 0 4.553754e-01 -0.49034712 0.8399553 0.7055250## 1 3.629155e-01 0.08752764 0.8320923 0.6923776## 2 1.363185e-01 0.88848487 0.7442791 0.5539514## 3 4.004353e-02 1.48774025 0.6857705 0.4702812## 4 5.315503e-03 2.02098264 0.6973134 0.4862460## 5 3.136865e-05 2.94497876 0.7680037 0.5898297## 6 1.847482e-07 3.81617186 0.7361128 0.5418621Rasch residual-based infit/outfit
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