Publications by N Foldnes
Document
The final item pool The SL items were removed, together with ill-fitting items. This resulted in 145 items: a b VM_385_Bakgården_1_kaka 5.0 -3.3 VM_386_Bakgården_2_gutten 1.4 -3.6 VM_388_Bakgården_4_Badebassenget 1.6 -3.6 VM_390_Bakgården_6_Verktøykassa 5.6 -2.1 VM_392_Bakgården_8_Løvetannen 1.5 -2.0 VM_394_Bakgården_10_...
6012 sym R (2730 sym/18 pcs) 7 img
Document
We use BM for ability estimation and compare 15 vs 25 items. 25 items truethetas <- seq(-2.2,2.2, length.out=n) est.df <- data.frame(truetheta=truethetas) NMAX <- 25 SEMTHR <- .01 # UNATTAINABLE SO LENGTH WILL BE 25 FOR ALL STUDENTS est.df$NMAX <- NMAX; est.df$SE <- SEMTHR; stop <- list(rule = c("precision","length"), thr = c(SEMTHR, NMAX)) re...
165 sym R (1983 sym/9 pcs) 5 img
Holsinger using RLS
Two models We consider a one-factor model with 4 indicators and the Holzinger 3-factor model. For the one-factor simple model we generate a random sample: library(lavaan) ## This is lavaan 0.6-7 ## lavaan is BETA software! Please report any bugs. #Simple factor model with random data Sim.model <- "F=~x1+x2+x3+x4" Sim.nobs <- 100 set.seed(1) Sim.c...
925 sym R (9946 sym/24 pcs) 3 img
Document
The population model The vita distribution and the thresholds The vita distribution consists of mostly joe copulas. The first two vine trees: We found some thresholds were the default nt approach seemed to perform poorly. For k=7 For k=10 Bootstrap SEs versus the default NT SEs The simulation design crossed two sample sizes \(n=500,1000\) wi...
656 sym R (1719 sym/4 pcs) 6 img
Document
Holzinger library(lavaan) ## This is lavaan 0.6-7 ## lavaan is BETA software! Please report any bugs. # Holzinger HS.model <- " visual =~ x1 + x2 + x3;textual =~ x4 + x5 + x6; speed =~ x7 + x8 + x9 " HS.cov <- cov(HolzingerSwineford1939[, paste0("x", 1:9)]) HS.nobs <- nrow(HolzingerSwineford1939) Step size reduction does not lead to solution ...
160 sym R (6883 sym/7 pcs)
Normindex1
Koden for normindex computeNormIndex ## function (my.data) ## { ## my.data <- data.frame(my.data) ## d <- ncol(my.data) ## indices <- NULL ## for (i2 in 1:(d - 1)) { ## for (i1 in (i2 + 1):d) { ## indices <- rbind(indices, c(i1, i2)) ## } ## } ## Tstat <- nrow(my.data) * computeT(my.data, indic...
466 sym R (1838 sym/6 pcs) 3 img
Longitudinal invariance
Generate longitudinal data load1 <- (5:8)/10 load2 <- load1# equal loadings set.seed(1) n <- 3000 # xi2 = .5*xi +1 xi <- MASS::mvrnorm(n, c(0,1), Sigma=matrix(c(1,.5, .5, 1),2)) ind1 <- xi[,1 ]%*% matrix(load1, nrow=1)+rnorm(4*n)# unique variance 1 ind2 <- xi[,2]%*% matrix(load2, nrow=1)+rnorm(4*n)# unique variance 1 dat <- cbind(ind1, ind2) da...
234 sym R (28770 sym/19 pcs)
Longitudinal with ordinal items
Configural model #plain lavaan m0 <- "ly1 =~ pc1_1+pc2_1+pc3_1+pc4_1; ly2 =~ pc1_2+pc2_2+pc3_2+pc4_2" f0 <- sem(m0, dat, ordered=T, std.lv=T, se="robust.sem", test="satorra.bentler", parameterization="theta") #using semtools syntax.config <- measEq.syntax(configural.model = f0, data=dat, parameterization="theta", ...
141 sym R (28203 sym/16 pcs)
Publish Document
Tippernes tabeller plass Grethe Andy Terje Bjelland Njål Olav Andreas Sagen Sverre 1 Bodø/Glimt Molde Molde Molde Molde Molde 2 Rosenborg Bodø/Glimt Rosenborg Bodø/Glimt Bodø/Glimt Bodø/Glimt 3 Viking Rosenborg Bodø/Glimt Vålerenga Vålerenga Rosenborg 4 Brann Vålerenga Vålerenga Viking Rosenborg Våle...
57 sym 2 img 2 tbl
Document
Structure and module numbering There are 6 modules (each with 6 items) numbered as follows stage1 stage2 stage3 M6 M3 M1 M5 M2 M4 Plots of theoretical and empirical modells Theoretical probabilities The overall final probabilites and probabilities as a function of \(\theta\) risk low med high 8.7 14 26.2 50.9 Items and cutoffs The cut...
374 sym R (1613 sym/1 pcs) 3 img 3 tbl