Nothing
R/print.R
In LNIRT: LogNormal Response Time Item Response Theory Models
Defines functions
print.summary.LNIRTQ
print.summary.LNRT
print.summary.LNIRT
#' @method print summary.LNIRT
#' @export
print.summary.LNIRT <- function(x, ...)
{
if (x$gammamodel) {
cat("\n", "Gamma RT-IRT Modeling, 2013, J.P. Fox")
} else {
cat("\n", "Log-Normal RT-IRT Modeling, 2013, J.-P. Fox")
}
cat("\n\n", rep('-', 38))
cat("\n", "MCMC iterations:\t", x$XG)
cat("\n", "Burn-in period:\t", paste(x$burnin, "%", sep = ""))
if (x$ident == 1) {
cat("\n", "Identification:\t", "mu_beta = mu_lambda = 0")
if (!x$WL && x$td)
cat("\n", "\t\t\t prod(alpha) = prod(phi) = 1")
else
cat("\n", "\t\t\t prod(alpha) = 1")
}
else if (x$ident == 2) {
cat("\n", "Identification:\t", "mu_theta = mu_zeta = 0")
if (!x$WL && x$td)
cat("\n", "\t\t\t prod(alpha) = prod(phi) = 1")
else
cat("\n", "\t\t\t prod(alpha) = 1")
}
cat("\n", rep('-', 38))
cat("\n\n", "Summary of results")
if (x$simv) {
cat("\n\n\t",
"Item Discrimination parameter",
"\t",
"Item Difficulty parameter",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
} else {
cat("\n\n\t",
"Item Discrimination parameter",
"\t",
"Item Difficulty parameter",
"\n")
cat("\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\n")
}
for (ii in 1:x$K) {
cat("\t")
if (x$simv) {
cat("\n\t", ii, "\t")
printF(x$idiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seidiscr[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 1], w = 6, d = 3) # SIM
cat("\t", ii, "\t")
printF(x$idiff[ii], w = 6, d = 3)
cat("\t")
printF(x$seidiff[ii], w = 6, d = 3)
cat("\t")
printF(x$data$ab[ii, 2], w = 6, d = 3)
} else {
cat("\n\t", ii, "\t")
printF(x$idiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seidiscr[ii], w = 6, d = 3) # SD
cat("\t\t", ii, "\t")
printF(x$idiff[ii], w = 6, d = 3)
cat("\t")
printF(x$seidiff[ii], w = 6, d = 3)
}
}
if (x$simv) {
if (x$WL) {
cat("\n\n\t",
"Time Discrimination (Measurement Error)",
" ",
"Time Intensity",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t\t",
"Time Intensity",
"\t\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
}
} else {
if (x$WL) {
cat(
"\n\n\t",
"Time Discrimination (Measurement Error)",
"\t",
"Time Intensity",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t",
"Time Intensity",
"\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
}
for (ii in 1:x$K) {
cat("\t")
if (x$simv) {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(1 / sqrt(x$data$sigma2[ii]), w = 6, d = 3) #SIM
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 3], w = 6, d = 3) #SIM
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 4], w = 6, d = 3) # SIM
cat("\t")
if (x$WL) {
cat(" ")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$sigma2[ii], w = 6, d = 3) #SIM
}
} else {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t\t")
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
if (x$WL) {
cat("")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) #SD
}
}
}
if (x$guess) {
if (x$simv) {
cat("\n\n\t", "Guessing Parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
for (ii in 1:x$K) {
cat("\n\t", ii, "\t")
# Guessing Parameter
printF(x$iguess[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seiguess[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$quess[ii], w = 6, d = 3) # true value
}
} else {
cat("\n\n\t", "Guessing Parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\n")
for (ii in 1:x$K) {
cat("\n\t", ii, "\t")
# Guessing Parameter
printF(x$iguess[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seiguess[ii], w = 6, d = 3) # SD
}
}
}
if (x$nopredictori) {
if (round(x$pdiscr2[2], 3) == 0 &&
round(x$pdiscr2[4], 3) == 0 && (!x$WL)) {
cat("\n\n\t",
"Mean and Covariance matrix Items (mu_a,mu_phi)",
"\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t", "mu_a", "\t", "SD", "\t", "mu_phi", " ", "SD", "\n")
for (jj in c(1, 3)) {
cat("\t")
printF(x$pdiscr2[jj], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[jj], w = 6, d = 3)
}
} else{
cat("\n\n\t",
"Mean and Covariance matrix Items (mu_a,mu_b,mu_phi,mu_lambda)",
"\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat(
"\t",
"mu_a",
"\t",
"SD",
"\t",
"mu_b",
"\t",
"SD",
"\t",
"mu_phi",
"",
"SD",
"\t",
"mu_lam",
"",
"SD",
"\n\t"
)
for (jj in c(1, 2, 3, 4)) {
printF(x$pdiscr2[jj], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[jj], w = 6, d = 3)
cat("\t")
}
}
if (x$WL) {
cat("\n\n\t",
"--- Covariance matrix Items (a,b,error variance,lambda)---",
"\n")
cat("\t\t",
"SigmaI",
"\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
} else{
cat("\n\n\t",
"--- Covariance matrix Items (a,b,phi,lambda)---",
"\n")
cat("\t\t",
"SigmaI",
"\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
}
for (ii in 1:4) {
cat("\t")
printF(x$pSdiscr2[ii, ], w = 6, d = 3)
cat("\t")
if (max(x$sepSdiscr2) < 1e02) {
printF(x$sepSdiscr2[ii, ], w = 6, d = 3)
} else{
printF(x$sepSdiscr2[ii, ], w = 8, d = 3)
}
cat("\t")
printF(x$SigmaIcor[ii, ], w = 6, d = 3)
cat("\t\n")
}
} else{
if (round(x$pdiscr2[2], 3) == 0 &&
round(x$pdiscr2[x$kia + 3], 3) == 0 && (!x$WL)) {
cat("\n\n\t", "Item Effects and Covariance matrix Items ", "\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t\t\t", "EAP", "\t", "SD", "\n")
cat("\t mu_a", "\t\t")
printF(x$pdiscr2[1], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[1], w = 6, d = 3)
cat("\n\t", "mu_phi", "\t")
printF(x$pdiscr2[x$kia + 2], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[x$kia + 2], w = 6, d = 3)
if (x$simv) {
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > 2) {
printF(x$data$Bia[ii - 2], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
if (x$predictorit) {
cat("\t\t", "Time Intensity Predictor Effects", "\n")
sst <- 0
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > (x$kia + 3)) {
printF(x$data$Bit[sst - 1], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
} else{
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
if (x$predictorit) {
cat("\t\t", "Time Intensity Predictor Effects", "\n")
sst <- 0
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
} else{
cat("\n\n\t", "Item Effects and Covariance matrix Items ", "\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t\t\t", "EAP", "\t", "SD", "\n")
cat("\t mu_a", "\t\t")
printF(x$pdiscr2[1], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[1], w = 6, d = 3)
cat("\n\t", "mu_phi", "\t")
printF(x$pdiscr2[x$kia + 2], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[x$kia + 2], w = 6, d = 3)
if (x$simv) {
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > 2) {
printF(x$data$Bia[ii - 2], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
if (x$predictorit) {
sst <- 0
cat("\t\t", "Time Intensity Predictor Effects", "\n")
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > (x$kia + 3)) {
printF(x$data$Bit[sst - 1], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
} else{
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
if (x$predictorit) {
sst <- 0
cat("\t\t", "Time Intensity Predictor Effects", "\n")
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
}
if (x$WL) {
cat("\n\n\t",
"--- Covariance matrix Items (a,b,error variance,lambda)---",
"\n")
cat("\t",
"SigmaI",
"\t\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
} else{
cat("\n\n\t",
"--- Covariance matrix Items (a,b,phi,lambda)---",
"\n")
cat("\t",
"SigmaI",
"\t\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
}
for (ii in 1:4) {
cat("\t")
printF(x$pSdiscr2[ii, ], w = 6, d = 3)
cat("\t")
if (max(x$sepSdiscr2) < 1e02) {
printF(x$sepSdiscr2[ii, ], w = 6, d = 3)
} else{
printF(x$sepSdiscr2[ii, ], w = 8, d = 3)
}
cat("\t")
printF(x$SigmaIcor[ii, ], w = 6, d = 3)
cat("\t\n")
}
}
if (x$nopredictorp) {
cat("\n\n\t",
"Mean and Covariance matrix Persons (ability,speed)",
"\n")
cat("\n\t",
"--- Population Mean Person (Ability - Speed)---",
"\n")
cat("\t\t\t", "muP", "\t", "SD", "\n")
for (ii in 1:2) {
if (ii == 1) {
cat("\t Ability \t")
} else{
cat("\t Speed \t\t")
}
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t\n")
}
} else {
if (x$simv) {
cat("\n\n\t",
"Person Effects and Covariance matrix Persons (ability,speed)",
"\n")
cat("\n\t", "--- Person Effects (Ability - Speed)---", "\n")
if (x$predictora) {
cat("\t\t", "Ability Predictor Effects", "\n")
for (ii in 1:x$ka) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t")
if (!is.null(x$data$Ba[ii])) {
printF(x$data$Ba[ii], w = 6, d = 3)
cat("\t\n")
}
else {
cat("\n")
}
}
}
if (x$predictort) {
cat("\t\t", "Speed Predictor Effects", "\n")
for (ii in (x$ka + 1):(x$kt + x$ka)) {
if (ii == (x$ka + 1)) {
cat("\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
cat("\t X", ii, "\t")
#cat("\t X",ii,"\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t")
if (!is.null(x$data$Bt[ii - x$ka])) {
printF(x$data$Bt[ii - x$ka], w = 6, d = 3)
cat("\t\n")
}
else {
cat("\n")
}
}
}
} else {
cat("\n\n\t",
"Person Effects and Covariance matrix Persons (ability,speed)",
"\n")
cat("\n\t", "--- Person Effects (Ability - Speed)---", "\n")
if (x$predictora) {
cat("\t\t", "Ability Predictor Effects", "\n")
for (ii in 1:x$ka) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t\n")
}
}
if (x$predictort) {
cat("\t\t", "Speed Predictor Effects", "\n")
for (ii in (x$ka + 1):(x$kt + x$ka)) {
if (ii == (x$ka + 1)) {
cat("\t\t", "EAP", "\t", "SD", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
}
cat("\n\t",
"SigmaP",
"\t",
"SD SigmaP",
"\t",
"SigmaP (Correlation)",
"\n")
for (ii in 1:2) {
cat("\t")
printF(x$pSpers2[ii,], w = 6, d = 3)
cat("\t")
printF(x$sepSpers2[ii,], w = 6, d = 3)
cat("\t")
printF(x$SigmaPcor[ii,], w = 6, d = 3)
cat("\t\n")
}
if (x$gammamodel) {
cat("\n\n\t", "--- Shape Parameter Gamma ---", "\n")
cat("\t", "EAP", "\t", "SD", "\n\t")
printF(x$estnug, w = 6, d = 3)
cat("\t")
printF(x$seestnug[jj], w = 6, d = 3)
cat("\t")
}
if ("lZP" %in% names(x)) {
cat("\n\n\n\t", "*** \t\t\t\t\t\t ***", "\n")
cat("\t", "*** Person Fit Analysis (Log-Normal Speed) ***", "\n")
cat("\t", "*** \t\t\t\t\t\t ***", "\n")
# Percentage Aberrant lZP (chi-square statstic)
cat("\n\t", "Percentage Outliers Persons (5% level)", "\n")
cat("\n\t", "lZ", "\n")
cat("\t", round(100 * length(which(x$lZP < 0.05)) / x$N, 2), "%", "\t\n")
cat("\t 95% Posterior Probability: ",
round(100 * sum(x$EAPCP1 > 0.95) / x$N, 2),
"%",
"\t\n")
# Percentage Persons (Estimation Group, Aberrant Group)
# cat('\n\t', 'Percentage Persons (Estimation Group, Aberrant Group) (5% level)','\n') cat('\n\t', 'Estimation Group', '\t',
# 'Aberrant','\n') cat('\t',100*round(apply(out$Mingroup,2,mean)[1],3),'\t\t\t',100*round(apply(out$Mingroup,2,mean)[2],3),'\t\n')
cat("\n\n\t", "*** Item Fit Analysis ***", "\n")
cat("\n\t", "Misfitting Items (5% level)", "\n")
set <- which(x$lZI < 0.05)
if (length(set >= 1)) {
cat("\n\t", "lI", "\n")
cat("\t", set, "\t\n")
} else {
cat("\t", "No Misfitting Items", "\t\n")
}
cat("\n\t", "*** Residual Analysis ***", "\n")
set <- which(x$EAPresid > 0.95)
if (length(set >= 1)) {
cat("\n\t",
"Percentage Extreme Residuals (.95 Posterior Probability)",
"\n")
cat(
"\t",
round(100 * length(set) / (x$N * x$K), 4),
"% (general average across persons and items)",
"\t\n"
)
## Identify Extremes
set <- which(x$EAPresid > 0.95)
set <- cbind((set %% x$N), (floor(set / x$N) + 1), exp(x$RT[set]))
dd <- order(set[, 1])
colnames(set) <- c("Person", "Item", " RT ")
rownames(set) <- rep(c(""), nrow(set))
cat("\n\t", "Extreme Residuals", "\n")
cat("\t", "Person", " Item", "\t", " RT ", "\n")
for (jj in dd) {
cat("\t")
printF(set[jj, 1], w = 6, d = 0)
cat("\t")
printF(set[jj, 2], w = 6, d = 0)
cat("\t")
printF(set[jj, 3], w = 8, d = 4)
cat("\n")
}
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat(
"\t",
round(100 * length(which(x$EAPKS < 0.05))) / x$K,
"%",
"of items has non-lognormally distributed residuals",
"\t\n"
)
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
} else {
cat("\t", "No Extreme Residuals", "\t\n")
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat("\t", round(100 * length(which(x$EAPKS < 0.05))) / x$K, "%", "\t\n")
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
}
cat("\n\n\n\t", "*** \t\t\t\t\t\t ***", "\n")
cat("\t",
"*** Person Fit Analysis (IRT Model For Ability) ***",
"\n")
cat("\t", "*** \t\t\t\t\t\t ***", "\n")
# Percentage Aberrant lZP (chi-square statstic) Percentage Aberrant l0 (log-likelihood statstic)
cat("\n\t", "Percentage Outliers Persons (5% level)", "\n")
cat("\n\t", "Log-likelihood Statistic", "\n")
# cat('\t',round(100*length(which(out$lZPA < .05))/x$N,2),'%','\t\n')
cat("\t", round(100 * length(which(x$PFlp < 0.05)) / x$N, 2), "%", "\t\n")
cat("\t 95% Posterior Probability: ",
round(100 * sum(x$EAPCP2 > 0.95) / x$N, 2),
"%",
"\t\n")
cat(
"\t 95% Posterior Probability (Ability and Speed): ",
round(100 * sum(x$EAPCP3 > 0.95) / x$N, 2),
"%",
"\t\n"
)
cat("\n\n\t", "*** Item Fit Analysis ***", "\n")
cat("\n\t", "Misfitting Items (5% level)", "\n")
# set <- which(out$lZIA < .05)
set <- which(x$IFlp < 0.05)
if (length(set >= 1)) {
cat("\n\t", "lI", "\n")
cat("\t", set, "\t\n")
} else {
cat("\t", "No Misfitting Items", "\t\n")
}
cat("\n\t", "*** Residual Analysis ***", "\n")
set <- which(x$EAPresidA > 0.95)
if (length(set >= 1)) {
cat("\n\t",
"Percentage Extreme Residuals (.95 Posterior Probability)",
"\n")
cat(
"\t",
round(100 * length(set) / (x$N * x$K), 4),
"% (general average across persons and items)",
"\t\n"
)
## Identify Extremes
set <- which(x$EAPresidA > 0.95)
set <-
cbind((set %% x$N), (floor(set / x$N) + 1), x$Y[set], x$Mtheta[(set %% x$N)])
dd <- order(set[, 1])
colnames(set) <- c("Person", "Item", " Y ", " EAP theta")
rownames(set) <- rep(c(""), nrow(set))
cat("\n\t", "Extreme Residuals", "\n")
cat("\t", "Person", " Item", "\t", " Response ", " EAP Theta", "\n")
for (jj in dd) {
cat("\t")
printF(set[jj, 1], w = 6, d = 0)
cat("\t")
printF(set[jj, 2], w = 6, d = 0)
cat("\t")
printF(set[jj, 3], w = 6, d = 0)
cat("\t")
printF(set[jj, 4], w = 8, d = 4)
cat("\n")
}
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat(
"\t",
round(100 * length(which(
x$EAPKSA < 0.05
))) / x$K,
"%",
"of items has non-normally distributed latent residuals",
"\t\n"
)
set <- which(x$EAPKSA < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKSA[set[jj]], w = 6, d = 3)
cat("\n")
}
}
} else {
cat("\t", "No Extreme Residuals", "\t\n")
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat("\t", round(100 * length(which(
x$EAPKSA < 0.05
))) / x$K, "%", "\t\n")
set <- which(x$EAPKSA < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKSA[set[jj]], w = 6, d = 3)
cat("\n")
}
}
}
} ## close personfit report
cat("\n\n")
}
#' @method print summary.LNRT
#' @export
print.summary.LNRT <- function(x, ...)
{
## Person Fit outcomes
if (x$gammamodel) {
cat("\n", "Gamma RT Modeling, 2013, J.P. Fox")
} else {
cat("\n", "Log-Normal RT Modeling, 2013, J.P. Fox")
}
cat("\n\n", rep('-', 38))
cat("\n", "MCMC iterations:\t", x$XG)
cat("\n", "Burn-in period:\t", paste(x$burnin, "%", sep = ""))
if (x$ident == 2) {
cat("\n", "Identification:\t", "mu_zeta = 0")
if (!x$WL && x$td)
cat("\n", "\t\t\t prod(phi) = 1")
}
cat("\n", rep('-', 38))
cat("\n\n", "Summary of results")
if (x$gammamodel) {
if (x$simv) {
if (ncol(x$Mnug) == 1) {
cat("\n\n\t", "Time Intensity parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ncol(x$Mnug) > 1) {
cat("\n\n\t",
"Time Intensity parameter",
"\t",
"Shape Parameter Gamma",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
} else {
if (ncol(x$Mnug) == 1) {
cat("\n\n\t", "Time Intensity parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\n")
}
if (ncol(x$Mnug) > 1) {
cat("\n\n\t",
"Time Intensity parameter",
"\t",
"Shape Parameter Gamma",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
}
} else {
if (x$simv) {
if (x$WL) {
cat(
"\n\n\t",
"Time Discrimination (Measurement Error)",
" ",
"Time Intensity",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t\t",
"Time Intensity",
"\t\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
}
} else {
if (x$WL) {
cat(
"\n\n\t",
"Time Discrimination (Measurement Error)",
"\t",
"Time Intensity",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t",
"Time Intensity",
"\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
}
}
if (x$gammamodel) {
for (ii in 1:x$K) {
cat("\n\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # estimated bsp
cat("\t")
printF(x$setintens[ii], w = 6, d = 3)
if (x$simv) {
cat("\t")
printF(x$data$bsp[ii], w = 6, d = 3) # bsp true value
# cat('\n\t', ii,'\t')
if (ncol(x$Mnug) > 1) {
cat("\t")
cat("\t", ii, "\t")
printF(x$estnug[ii], w = 6, d = 3) # Shape Parameter Gamma EAP
cat("\t")
printF(x$seestnug[ii], w = 6, d = 3)
}
} else {
if (ncol(x$Mnug) == 1) {
cat("\t")
}
if (ncol(x$Mnug) > 1) {
cat("\t\t", ii, "\t")
printF(x$estnug[ii], w = 6, d = 3)
cat("\t")
printF(x$seestnug[ii], w = 6, d = 3)
}
}
}
} else {
for (ii in 1:x$K) {
cat("\t")
if (x$simv) {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(1 / sqrt(x$data$sigma2[ii]), w = 6, d = 3) #SIM
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 3], w = 6, d = 3) #SIM
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 4], w = 6, d = 3) # SIM
cat("\t")
if (x$WL) {
cat(" ")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$sigma2[ii], w = 6, d = 3) #SIM
}
} else {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t\t")
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
if (x$WL) {
cat("")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) #SD
}
}
}
}
cat("\n\n\t", "Mean and Covariance matrix Items (phi,lambda)", "\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t", "mu_phi", " ", "SD", "\t", "mu_lam", " ", "SD", "\n\t")
for (jj in c(1, 2)) {
printF(x$pdiscr[jj], w = 6, d = 3)
cat("\t ")
printF(x$sepdiscr[jj], w = 6, d = 3)
cat("\t")
}
cat("\n\n\t", "--- Covariance matrix Items ---", "\n")
cat("\t",
"phi",
"\t",
"SD",
"\t",
"Cov",
"\t",
"SD",
"\t",
"lambda",
" ",
"SD",
"\n\t")
for (jj in c(1, 2, 4)) {
printF(x$pSdiscr[jj], w = 6, d = 3)
cat("\t")
printF(x$sepSdiscr[jj], w = 6, d = 3)
cat("\t")
}
if (x$predictorit) {
if (x$simv) {
cat("\n\n\t", "Time Intensity Predictor Effects", "\n")
for (ii in 2:(x$kit + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr[ii], w = 6, d = 3)
cat("\t")
if (ii > 2) {
printF(x$data$Bit[ii - 2], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
else {
cat("\n\n\t", "Time Intensity Predictor Effects", "\n")
for (ii in 2:(x$kit + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
cat("\n\n\t", "Mean and Covariance matrix Persons", "\n")
cat("\n\t", "--- Population Mean Person ---", "\n")
cat("\t", "mu_P", "\t ", "SD", "\n\t")
for (jj in c(1)) {
printF(x$ppers[jj], w = 6, d = 2)
cat("\t")
printF(x$seppers[jj], w = 6, d = 2)
cat("\t")
}
if (x$predictort) {
if (x$simv) {
cat("\n\n\t", "Speed Predictor Effects", "\n")
for (ii in 1:x$kt) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers[ii], w = 6, d = 3)
cat("\t")
printF(x$sepper[ii], w = 6, d = 3)
cat("\t")
if (!is.null(x$data$Bt[ii])) {
printF(x$data$Bt[ii], w = 6, d = 3)
cat("\t\n")
}
else {
cat("\n")
}
}
}
else {
cat("\n\n\t", "Speed Predictor Effects", "\n")
for (ii in 1:x$kt) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
cat("\n\n\t", "--- Covariance matrix Person ---", "\n")
cat("\t", "Sigma_P", "SD", "\n\t")
for (jj in c(1)) {
printF(x$pSpers[jj], w = 6, d = 3)
cat("\t")
printF(x$sepSpers[jj], w = 6, d = 3)
cat("\t")
}
if ((x$gammamodel) && (ncol(x$Mnug) == 1)) {
cat("\n\n\t", "--- Shape Parameter Gamma ---", "\n")
cat("\t", "EAP", "\t", "SD", "\n\t")
printF(x$estnug, w = 6, d = 3)
cat("\t")
printF(x$seestnug[jj], w = 6, d = 3)
cat("\t")
}
if ("lZP" %in% names(x)) {
cat("\n\n\n\t", "*** Person Fit Analysis ***", "\n")
# Percentage Aberrant lZP3
cat("\n\t", "Percentage Outliers Persons (5% level)", "\n")
cat("\n\t", "lZ", "\n")
cat("\t", round(100 * sum(x$lZP < 0.05) / x$N, 2), "%", "\t\n")
cat("\t 95% Posterior Probability: ",
round(100 * sum(x$EAPCP > 0.95) / x$N, 2),
"%",
"\t\n")
# Percentage Persons (Estimation Group, Aberrant Group)
# cat('\n\t', 'Percentage Persons (Estimation Group, Aberrant Group) (5% level)','\n') cat('\n\t', 'Estimation Group', '\t',
# 'Aberrant','\n') cat('\t',100*round(apply(x$Mingroup,2,mean)[1],3),'\t\t\t',100*round(apply(x$Mingroup,2,mean)[2],3),'\t\n')
cat("\n\n\t", "*** Item Fit Analysis ***", "\n")
cat("\n\t", "Misfitting Items (5% level)", "\n")
set <- which(x$lZI < 0.05)
if (length(set >= 1)) {
cat("\n\t", "lI", "\n")
cat("\t", set, "\t\n")
} else {
cat("\t", "No Misfitting Items", "\t\n")
}
cat("\n\t", "*** Residual Analysis ***", "\n")
set <- which(x$EAPresid > 0.95)
if (length(set >= 1)) {
cat("\n\t",
"Percentage Extreme Residuals (.95 Posterior Probability)",
"\n")
cat(
"\t",
round(100 * length(set) / (x$N * x$K), 4),
"% (general average across persons and items)",
"\t\n"
)
## Identify Extremes
set <- which(x$EAPresid > 0.95)
set <- cbind((set %% x$N), (floor(set / x$N) + 1), exp(x$RT[set]))
dd <- order(set[, 1])
colnames(set) <- c("Person", "Item", " RT ")
rownames(set) <- rep(c(""), nrow(set))
cat("\n\t", "Extreme Residuals", "\n")
cat("\t", "Person", " Item", "\t", " RT ", "\n")
for (jj in dd) {
cat("\t")
printF(set[jj, 1], w = 6, d = 0)
cat("\t")
printF(set[jj, 2], w = 6, d = 0)
cat("\t")
printF(set[jj, 3], w = 8, d = 4)
cat("\n")
}
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat(
"\t",
round(100 * length(which(x$EAPKS < 0.05))) / x$K,
"%",
"of items has non-lognormally distributed residuals",
"\t\n"
)
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
} else {
cat("\t", "No Extreme Residuals", "\t\n")
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat("\t", round(100 * length(which(x$EAPKS < 0.05))) / x$K, "%", "\t\n")
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
}
}
cat("\n\n")
}
#' @method print summary.LNIRTQ
#' @export
print.summary.LNIRTQ <- function(x, ...)
{
if (!is.null(x$object$data)) {
# sim data
summaryIRTQ(out = x$object, data = x$object$data)
}
else {
summaryIRTQ(out = x$object)
}
}
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LNIRT documentation built on Jan. 20, 2021, 1:05 a.m.
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Defines functions print.summary.LNIRTQ print.summary.LNRT print.summary.LNIRT
#' @method print summary.LNIRT
#' @export
print.summary.LNIRT <- function(x, ...)
{
if (x$gammamodel) {
cat("\n", "Gamma RT-IRT Modeling, 2013, J.P. Fox")
} else {
cat("\n", "Log-Normal RT-IRT Modeling, 2013, J.-P. Fox")
}
cat("\n\n", rep('-', 38))
cat("\n", "MCMC iterations:\t", x$XG)
cat("\n", "Burn-in period:\t", paste(x$burnin, "%", sep = ""))
if (x$ident == 1) {
cat("\n", "Identification:\t", "mu_beta = mu_lambda = 0")
if (!x$WL && x$td)
cat("\n", "\t\t\t prod(alpha) = prod(phi) = 1")
else
cat("\n", "\t\t\t prod(alpha) = 1")
}
else if (x$ident == 2) {
cat("\n", "Identification:\t", "mu_theta = mu_zeta = 0")
if (!x$WL && x$td)
cat("\n", "\t\t\t prod(alpha) = prod(phi) = 1")
else
cat("\n", "\t\t\t prod(alpha) = 1")
}
cat("\n", rep('-', 38))
cat("\n\n", "Summary of results")
if (x$simv) {
cat("\n\n\t",
"Item Discrimination parameter",
"\t",
"Item Difficulty parameter",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
} else {
cat("\n\n\t",
"Item Discrimination parameter",
"\t",
"Item Difficulty parameter",
"\n")
cat("\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\n")
}
for (ii in 1:x$K) {
cat("\t")
if (x$simv) {
cat("\n\t", ii, "\t")
printF(x$idiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seidiscr[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 1], w = 6, d = 3) # SIM
cat("\t", ii, "\t")
printF(x$idiff[ii], w = 6, d = 3)
cat("\t")
printF(x$seidiff[ii], w = 6, d = 3)
cat("\t")
printF(x$data$ab[ii, 2], w = 6, d = 3)
} else {
cat("\n\t", ii, "\t")
printF(x$idiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seidiscr[ii], w = 6, d = 3) # SD
cat("\t\t", ii, "\t")
printF(x$idiff[ii], w = 6, d = 3)
cat("\t")
printF(x$seidiff[ii], w = 6, d = 3)
}
}
if (x$simv) {
if (x$WL) {
cat("\n\n\t",
"Time Discrimination (Measurement Error)",
" ",
"Time Intensity",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t\t",
"Time Intensity",
"\t\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
}
} else {
if (x$WL) {
cat(
"\n\n\t",
"Time Discrimination (Measurement Error)",
"\t",
"Time Intensity",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t",
"Time Intensity",
"\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
}
for (ii in 1:x$K) {
cat("\t")
if (x$simv) {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(1 / sqrt(x$data$sigma2[ii]), w = 6, d = 3) #SIM
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 3], w = 6, d = 3) #SIM
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 4], w = 6, d = 3) # SIM
cat("\t")
if (x$WL) {
cat(" ")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$sigma2[ii], w = 6, d = 3) #SIM
}
} else {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t\t")
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
if (x$WL) {
cat("")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) #SD
}
}
}
if (x$guess) {
if (x$simv) {
cat("\n\n\t", "Guessing Parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
for (ii in 1:x$K) {
cat("\n\t", ii, "\t")
# Guessing Parameter
printF(x$iguess[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seiguess[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$quess[ii], w = 6, d = 3) # true value
}
} else {
cat("\n\n\t", "Guessing Parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\n")
for (ii in 1:x$K) {
cat("\n\t", ii, "\t")
# Guessing Parameter
printF(x$iguess[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seiguess[ii], w = 6, d = 3) # SD
}
}
}
if (x$nopredictori) {
if (round(x$pdiscr2[2], 3) == 0 &&
round(x$pdiscr2[4], 3) == 0 && (!x$WL)) {
cat("\n\n\t",
"Mean and Covariance matrix Items (mu_a,mu_phi)",
"\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t", "mu_a", "\t", "SD", "\t", "mu_phi", " ", "SD", "\n")
for (jj in c(1, 3)) {
cat("\t")
printF(x$pdiscr2[jj], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[jj], w = 6, d = 3)
}
} else{
cat("\n\n\t",
"Mean and Covariance matrix Items (mu_a,mu_b,mu_phi,mu_lambda)",
"\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat(
"\t",
"mu_a",
"\t",
"SD",
"\t",
"mu_b",
"\t",
"SD",
"\t",
"mu_phi",
"",
"SD",
"\t",
"mu_lam",
"",
"SD",
"\n\t"
)
for (jj in c(1, 2, 3, 4)) {
printF(x$pdiscr2[jj], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[jj], w = 6, d = 3)
cat("\t")
}
}
if (x$WL) {
cat("\n\n\t",
"--- Covariance matrix Items (a,b,error variance,lambda)---",
"\n")
cat("\t\t",
"SigmaI",
"\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
} else{
cat("\n\n\t",
"--- Covariance matrix Items (a,b,phi,lambda)---",
"\n")
cat("\t\t",
"SigmaI",
"\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
}
for (ii in 1:4) {
cat("\t")
printF(x$pSdiscr2[ii, ], w = 6, d = 3)
cat("\t")
if (max(x$sepSdiscr2) < 1e02) {
printF(x$sepSdiscr2[ii, ], w = 6, d = 3)
} else{
printF(x$sepSdiscr2[ii, ], w = 8, d = 3)
}
cat("\t")
printF(x$SigmaIcor[ii, ], w = 6, d = 3)
cat("\t\n")
}
} else{
if (round(x$pdiscr2[2], 3) == 0 &&
round(x$pdiscr2[x$kia + 3], 3) == 0 && (!x$WL)) {
cat("\n\n\t", "Item Effects and Covariance matrix Items ", "\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t\t\t", "EAP", "\t", "SD", "\n")
cat("\t mu_a", "\t\t")
printF(x$pdiscr2[1], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[1], w = 6, d = 3)
cat("\n\t", "mu_phi", "\t")
printF(x$pdiscr2[x$kia + 2], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[x$kia + 2], w = 6, d = 3)
if (x$simv) {
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > 2) {
printF(x$data$Bia[ii - 2], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
if (x$predictorit) {
cat("\t\t", "Time Intensity Predictor Effects", "\n")
sst <- 0
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > (x$kia + 3)) {
printF(x$data$Bit[sst - 1], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
} else{
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
if (x$predictorit) {
cat("\t\t", "Time Intensity Predictor Effects", "\n")
sst <- 0
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
} else{
cat("\n\n\t", "Item Effects and Covariance matrix Items ", "\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t\t\t", "EAP", "\t", "SD", "\n")
cat("\t mu_a", "\t\t")
printF(x$pdiscr2[1], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[1], w = 6, d = 3)
cat("\n\t", "mu_phi", "\t")
printF(x$pdiscr2[x$kia + 2], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[x$kia + 2], w = 6, d = 3)
if (x$simv) {
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > 2) {
printF(x$data$Bia[ii - 2], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
if (x$predictorit) {
sst <- 0
cat("\t\t", "Time Intensity Predictor Effects", "\n")
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t")
if (ii > (x$kia + 3)) {
printF(x$data$Bit[sst - 1], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
} else{
if (x$predictoria) {
cat("\n\t\t", "Item Difficulty Predictor Effects", "\n")
for (ii in 2:(x$kia + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
if (x$predictorit) {
sst <- 0
cat("\t\t", "Time Intensity Predictor Effects", "\n")
for (ii in (x$kia + 3):(2 + x$kit + x$kia)) {
sst <- sst + 1
if (ii == (x$kia + 3)) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == (x$kia + 3)) {
cat("\t Intercept", "\t")
} else{
cat("\t X", (x$kia - 2) + sst, "\t\t")
}
printF(x$pdiscr2[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr2[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
}
if (x$WL) {
cat("\n\n\t",
"--- Covariance matrix Items (a,b,error variance,lambda)---",
"\n")
cat("\t",
"SigmaI",
"\t\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
} else{
cat("\n\n\t",
"--- Covariance matrix Items (a,b,phi,lambda)---",
"\n")
cat("\t",
"SigmaI",
"\t\t\t",
"SD SigmaI",
"\t\t\t",
"SigmaI (Correlation)",
"\n")
}
for (ii in 1:4) {
cat("\t")
printF(x$pSdiscr2[ii, ], w = 6, d = 3)
cat("\t")
if (max(x$sepSdiscr2) < 1e02) {
printF(x$sepSdiscr2[ii, ], w = 6, d = 3)
} else{
printF(x$sepSdiscr2[ii, ], w = 8, d = 3)
}
cat("\t")
printF(x$SigmaIcor[ii, ], w = 6, d = 3)
cat("\t\n")
}
}
if (x$nopredictorp) {
cat("\n\n\t",
"Mean and Covariance matrix Persons (ability,speed)",
"\n")
cat("\n\t",
"--- Population Mean Person (Ability - Speed)---",
"\n")
cat("\t\t\t", "muP", "\t", "SD", "\n")
for (ii in 1:2) {
if (ii == 1) {
cat("\t Ability \t")
} else{
cat("\t Speed \t\t")
}
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t\n")
}
} else {
if (x$simv) {
cat("\n\n\t",
"Person Effects and Covariance matrix Persons (ability,speed)",
"\n")
cat("\n\t", "--- Person Effects (Ability - Speed)---", "\n")
if (x$predictora) {
cat("\t\t", "Ability Predictor Effects", "\n")
for (ii in 1:x$ka) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t")
if (!is.null(x$data$Ba[ii])) {
printF(x$data$Ba[ii], w = 6, d = 3)
cat("\t\n")
}
else {
cat("\n")
}
}
}
if (x$predictort) {
cat("\t\t", "Speed Predictor Effects", "\n")
for (ii in (x$ka + 1):(x$kt + x$ka)) {
if (ii == (x$ka + 1)) {
cat("\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
cat("\t X", ii, "\t")
#cat("\t X",ii,"\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t")
if (!is.null(x$data$Bt[ii - x$ka])) {
printF(x$data$Bt[ii - x$ka], w = 6, d = 3)
cat("\t\n")
}
else {
cat("\n")
}
}
}
} else {
cat("\n\n\t",
"Person Effects and Covariance matrix Persons (ability,speed)",
"\n")
cat("\n\t", "--- Person Effects (Ability - Speed)---", "\n")
if (x$predictora) {
cat("\t\t", "Ability Predictor Effects", "\n")
for (ii in 1:x$ka) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t\n")
}
}
if (x$predictort) {
cat("\t\t", "Speed Predictor Effects", "\n")
for (ii in (x$ka + 1):(x$kt + x$ka)) {
if (ii == (x$ka + 1)) {
cat("\t\t", "EAP", "\t", "SD", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers2[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers2[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
}
cat("\n\t",
"SigmaP",
"\t",
"SD SigmaP",
"\t",
"SigmaP (Correlation)",
"\n")
for (ii in 1:2) {
cat("\t")
printF(x$pSpers2[ii,], w = 6, d = 3)
cat("\t")
printF(x$sepSpers2[ii,], w = 6, d = 3)
cat("\t")
printF(x$SigmaPcor[ii,], w = 6, d = 3)
cat("\t\n")
}
if (x$gammamodel) {
cat("\n\n\t", "--- Shape Parameter Gamma ---", "\n")
cat("\t", "EAP", "\t", "SD", "\n\t")
printF(x$estnug, w = 6, d = 3)
cat("\t")
printF(x$seestnug[jj], w = 6, d = 3)
cat("\t")
}
if ("lZP" %in% names(x)) {
cat("\n\n\n\t", "*** \t\t\t\t\t\t ***", "\n")
cat("\t", "*** Person Fit Analysis (Log-Normal Speed) ***", "\n")
cat("\t", "*** \t\t\t\t\t\t ***", "\n")
# Percentage Aberrant lZP (chi-square statstic)
cat("\n\t", "Percentage Outliers Persons (5% level)", "\n")
cat("\n\t", "lZ", "\n")
cat("\t", round(100 * length(which(x$lZP < 0.05)) / x$N, 2), "%", "\t\n")
cat("\t 95% Posterior Probability: ",
round(100 * sum(x$EAPCP1 > 0.95) / x$N, 2),
"%",
"\t\n")
# Percentage Persons (Estimation Group, Aberrant Group)
# cat('\n\t', 'Percentage Persons (Estimation Group, Aberrant Group) (5% level)','\n') cat('\n\t', 'Estimation Group', '\t',
# 'Aberrant','\n') cat('\t',100*round(apply(out$Mingroup,2,mean)[1],3),'\t\t\t',100*round(apply(out$Mingroup,2,mean)[2],3),'\t\n')
cat("\n\n\t", "*** Item Fit Analysis ***", "\n")
cat("\n\t", "Misfitting Items (5% level)", "\n")
set <- which(x$lZI < 0.05)
if (length(set >= 1)) {
cat("\n\t", "lI", "\n")
cat("\t", set, "\t\n")
} else {
cat("\t", "No Misfitting Items", "\t\n")
}
cat("\n\t", "*** Residual Analysis ***", "\n")
set <- which(x$EAPresid > 0.95)
if (length(set >= 1)) {
cat("\n\t",
"Percentage Extreme Residuals (.95 Posterior Probability)",
"\n")
cat(
"\t",
round(100 * length(set) / (x$N * x$K), 4),
"% (general average across persons and items)",
"\t\n"
)
## Identify Extremes
set <- which(x$EAPresid > 0.95)
set <- cbind((set %% x$N), (floor(set / x$N) + 1), exp(x$RT[set]))
dd <- order(set[, 1])
colnames(set) <- c("Person", "Item", " RT ")
rownames(set) <- rep(c(""), nrow(set))
cat("\n\t", "Extreme Residuals", "\n")
cat("\t", "Person", " Item", "\t", " RT ", "\n")
for (jj in dd) {
cat("\t")
printF(set[jj, 1], w = 6, d = 0)
cat("\t")
printF(set[jj, 2], w = 6, d = 0)
cat("\t")
printF(set[jj, 3], w = 8, d = 4)
cat("\n")
}
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat(
"\t",
round(100 * length(which(x$EAPKS < 0.05))) / x$K,
"%",
"of items has non-lognormally distributed residuals",
"\t\n"
)
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
} else {
cat("\t", "No Extreme Residuals", "\t\n")
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat("\t", round(100 * length(which(x$EAPKS < 0.05))) / x$K, "%", "\t\n")
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
}
cat("\n\n\n\t", "*** \t\t\t\t\t\t ***", "\n")
cat("\t",
"*** Person Fit Analysis (IRT Model For Ability) ***",
"\n")
cat("\t", "*** \t\t\t\t\t\t ***", "\n")
# Percentage Aberrant lZP (chi-square statstic) Percentage Aberrant l0 (log-likelihood statstic)
cat("\n\t", "Percentage Outliers Persons (5% level)", "\n")
cat("\n\t", "Log-likelihood Statistic", "\n")
# cat('\t',round(100*length(which(out$lZPA < .05))/x$N,2),'%','\t\n')
cat("\t", round(100 * length(which(x$PFlp < 0.05)) / x$N, 2), "%", "\t\n")
cat("\t 95% Posterior Probability: ",
round(100 * sum(x$EAPCP2 > 0.95) / x$N, 2),
"%",
"\t\n")
cat(
"\t 95% Posterior Probability (Ability and Speed): ",
round(100 * sum(x$EAPCP3 > 0.95) / x$N, 2),
"%",
"\t\n"
)
cat("\n\n\t", "*** Item Fit Analysis ***", "\n")
cat("\n\t", "Misfitting Items (5% level)", "\n")
# set <- which(out$lZIA < .05)
set <- which(x$IFlp < 0.05)
if (length(set >= 1)) {
cat("\n\t", "lI", "\n")
cat("\t", set, "\t\n")
} else {
cat("\t", "No Misfitting Items", "\t\n")
}
cat("\n\t", "*** Residual Analysis ***", "\n")
set <- which(x$EAPresidA > 0.95)
if (length(set >= 1)) {
cat("\n\t",
"Percentage Extreme Residuals (.95 Posterior Probability)",
"\n")
cat(
"\t",
round(100 * length(set) / (x$N * x$K), 4),
"% (general average across persons and items)",
"\t\n"
)
## Identify Extremes
set <- which(x$EAPresidA > 0.95)
set <-
cbind((set %% x$N), (floor(set / x$N) + 1), x$Y[set], x$Mtheta[(set %% x$N)])
dd <- order(set[, 1])
colnames(set) <- c("Person", "Item", " Y ", " EAP theta")
rownames(set) <- rep(c(""), nrow(set))
cat("\n\t", "Extreme Residuals", "\n")
cat("\t", "Person", " Item", "\t", " Response ", " EAP Theta", "\n")
for (jj in dd) {
cat("\t")
printF(set[jj, 1], w = 6, d = 0)
cat("\t")
printF(set[jj, 2], w = 6, d = 0)
cat("\t")
printF(set[jj, 3], w = 6, d = 0)
cat("\t")
printF(set[jj, 4], w = 8, d = 4)
cat("\n")
}
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat(
"\t",
round(100 * length(which(
x$EAPKSA < 0.05
))) / x$K,
"%",
"of items has non-normally distributed latent residuals",
"\t\n"
)
set <- which(x$EAPKSA < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKSA[set[jj]], w = 6, d = 3)
cat("\n")
}
}
} else {
cat("\t", "No Extreme Residuals", "\t\n")
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat("\t", round(100 * length(which(
x$EAPKSA < 0.05
))) / x$K, "%", "\t\n")
set <- which(x$EAPKSA < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKSA[set[jj]], w = 6, d = 3)
cat("\n")
}
}
}
} ## close personfit report
cat("\n\n")
}
#' @method print summary.LNRT
#' @export
print.summary.LNRT <- function(x, ...)
{
## Person Fit outcomes
if (x$gammamodel) {
cat("\n", "Gamma RT Modeling, 2013, J.P. Fox")
} else {
cat("\n", "Log-Normal RT Modeling, 2013, J.P. Fox")
}
cat("\n\n", rep('-', 38))
cat("\n", "MCMC iterations:\t", x$XG)
cat("\n", "Burn-in period:\t", paste(x$burnin, "%", sep = ""))
if (x$ident == 2) {
cat("\n", "Identification:\t", "mu_zeta = 0")
if (!x$WL && x$td)
cat("\n", "\t\t\t prod(phi) = 1")
}
cat("\n", rep('-', 38))
cat("\n\n", "Summary of results")
if (x$gammamodel) {
if (x$simv) {
if (ncol(x$Mnug) == 1) {
cat("\n\n\t", "Time Intensity parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ncol(x$Mnug) > 1) {
cat("\n\n\t",
"Time Intensity parameter",
"\t",
"Shape Parameter Gamma",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
} else {
if (ncol(x$Mnug) == 1) {
cat("\n\n\t", "Time Intensity parameter", "\n")
cat("\t", "item", "\t", "EAP", "\t", "SD", "\n")
}
if (ncol(x$Mnug) > 1) {
cat("\n\n\t",
"Time Intensity parameter",
"\t",
"Shape Parameter Gamma",
"\n")
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
}
} else {
if (x$simv) {
if (x$WL) {
cat(
"\n\n\t",
"Time Discrimination (Measurement Error)",
" ",
"Time Intensity",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t\t",
"Time Intensity",
"\t\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\t",
"EAP",
"\t",
"SD",
"\t",
"Sim",
"\n"
)
}
} else {
if (x$WL) {
cat(
"\n\n\t",
"Time Discrimination (Measurement Error)",
"\t",
"Time Intensity",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t\t\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"\n"
)
} else {
cat(
"\n\n\t",
"Time Discrimination",
"\t",
"Time Intensity",
"\t",
"Measurement Error Variance",
"\n"
)
cat(
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"item",
"\t",
"EAP",
"\t",
"SD",
"\t",
"EAP",
"\t",
"SD",
"\n"
)
}
}
}
if (x$gammamodel) {
for (ii in 1:x$K) {
cat("\n\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # estimated bsp
cat("\t")
printF(x$setintens[ii], w = 6, d = 3)
if (x$simv) {
cat("\t")
printF(x$data$bsp[ii], w = 6, d = 3) # bsp true value
# cat('\n\t', ii,'\t')
if (ncol(x$Mnug) > 1) {
cat("\t")
cat("\t", ii, "\t")
printF(x$estnug[ii], w = 6, d = 3) # Shape Parameter Gamma EAP
cat("\t")
printF(x$seestnug[ii], w = 6, d = 3)
}
} else {
if (ncol(x$Mnug) == 1) {
cat("\t")
}
if (ncol(x$Mnug) > 1) {
cat("\t\t", ii, "\t")
printF(x$estnug[ii], w = 6, d = 3)
cat("\t")
printF(x$seestnug[ii], w = 6, d = 3)
}
}
}
} else {
for (ii in 1:x$K) {
cat("\t")
if (x$simv) {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(1 / sqrt(x$data$sigma2[ii]), w = 6, d = 3) #SIM
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 3], w = 6, d = 3) #SIM
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$ab[ii, 4], w = 6, d = 3) # SIM
cat("\t")
if (x$WL) {
cat(" ")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t")
printF(x$data$sigma2[ii], w = 6, d = 3) #SIM
}
} else {
cat("\n\t", ii, "\t")
if (x$WL) {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) # SD
cat("\t\t")
} else {
printF(x$tdiscr[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setdiscr[ii], w = 6, d = 3) # SD
}
cat("\t", ii, "\t")
printF(x$tintens[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$setintens[ii], w = 6, d = 3) # SD
cat("\t")
if (x$WL) {
cat("")
} else {
printF(x$estsigma2[ii], w = 6, d = 3) # EAP
cat("\t")
printF(x$seestsigma2[ii], w = 6, d = 3) #SD
}
}
}
}
cat("\n\n\t", "Mean and Covariance matrix Items (phi,lambda)", "\n")
cat("\n\t", "--- Population Mean Item ---", "\n")
cat("\t", "mu_phi", " ", "SD", "\t", "mu_lam", " ", "SD", "\n\t")
for (jj in c(1, 2)) {
printF(x$pdiscr[jj], w = 6, d = 3)
cat("\t ")
printF(x$sepdiscr[jj], w = 6, d = 3)
cat("\t")
}
cat("\n\n\t", "--- Covariance matrix Items ---", "\n")
cat("\t",
"phi",
"\t",
"SD",
"\t",
"Cov",
"\t",
"SD",
"\t",
"lambda",
" ",
"SD",
"\n\t")
for (jj in c(1, 2, 4)) {
printF(x$pSdiscr[jj], w = 6, d = 3)
cat("\t")
printF(x$sepSdiscr[jj], w = 6, d = 3)
cat("\t")
}
if (x$predictorit) {
if (x$simv) {
cat("\n\n\t", "Time Intensity Predictor Effects", "\n")
for (ii in 2:(x$kit + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr[ii], w = 6, d = 3)
cat("\t")
if (ii > 2) {
printF(x$data$Bit[ii - 2], w = 6, d = 3)
cat("\t\n")
} else{
cat("\n")
}
}
}
else {
cat("\n\n\t", "Time Intensity Predictor Effects", "\n")
for (ii in 2:(x$kit + 1)) {
if (ii == 2) {
cat("\t\t\t", "EAP", "\t", "SD", "\n")
}
if (ii == 2) {
cat("\t Intercept", "\t")
} else{
cat("\t X", ii - 2, "\t\t")
}
printF(x$pdiscr[ii], w = 6, d = 3)
cat("\t")
printF(x$sepdiscr[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
cat("\n\n\t", "Mean and Covariance matrix Persons", "\n")
cat("\n\t", "--- Population Mean Person ---", "\n")
cat("\t", "mu_P", "\t ", "SD", "\n\t")
for (jj in c(1)) {
printF(x$ppers[jj], w = 6, d = 2)
cat("\t")
printF(x$seppers[jj], w = 6, d = 2)
cat("\t")
}
if (x$predictort) {
if (x$simv) {
cat("\n\n\t", "Speed Predictor Effects", "\n")
for (ii in 1:x$kt) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\t", "Sim", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers[ii], w = 6, d = 3)
cat("\t")
printF(x$sepper[ii], w = 6, d = 3)
cat("\t")
if (!is.null(x$data$Bt[ii])) {
printF(x$data$Bt[ii], w = 6, d = 3)
cat("\t\n")
}
else {
cat("\n")
}
}
}
else {
cat("\n\n\t", "Speed Predictor Effects", "\n")
for (ii in 1:x$kt) {
if (ii == 1) {
cat("\t\t", "EAP", "\t", "SD", "\n")
}
cat("\t X", ii, "\t")
printF(x$ppers[ii], w = 6, d = 3)
cat("\t")
printF(x$seppers[ii], w = 6, d = 3)
cat("\t\n")
}
}
}
cat("\n\n\t", "--- Covariance matrix Person ---", "\n")
cat("\t", "Sigma_P", "SD", "\n\t")
for (jj in c(1)) {
printF(x$pSpers[jj], w = 6, d = 3)
cat("\t")
printF(x$sepSpers[jj], w = 6, d = 3)
cat("\t")
}
if ((x$gammamodel) && (ncol(x$Mnug) == 1)) {
cat("\n\n\t", "--- Shape Parameter Gamma ---", "\n")
cat("\t", "EAP", "\t", "SD", "\n\t")
printF(x$estnug, w = 6, d = 3)
cat("\t")
printF(x$seestnug[jj], w = 6, d = 3)
cat("\t")
}
if ("lZP" %in% names(x)) {
cat("\n\n\n\t", "*** Person Fit Analysis ***", "\n")
# Percentage Aberrant lZP3
cat("\n\t", "Percentage Outliers Persons (5% level)", "\n")
cat("\n\t", "lZ", "\n")
cat("\t", round(100 * sum(x$lZP < 0.05) / x$N, 2), "%", "\t\n")
cat("\t 95% Posterior Probability: ",
round(100 * sum(x$EAPCP > 0.95) / x$N, 2),
"%",
"\t\n")
# Percentage Persons (Estimation Group, Aberrant Group)
# cat('\n\t', 'Percentage Persons (Estimation Group, Aberrant Group) (5% level)','\n') cat('\n\t', 'Estimation Group', '\t',
# 'Aberrant','\n') cat('\t',100*round(apply(x$Mingroup,2,mean)[1],3),'\t\t\t',100*round(apply(x$Mingroup,2,mean)[2],3),'\t\n')
cat("\n\n\t", "*** Item Fit Analysis ***", "\n")
cat("\n\t", "Misfitting Items (5% level)", "\n")
set <- which(x$lZI < 0.05)
if (length(set >= 1)) {
cat("\n\t", "lI", "\n")
cat("\t", set, "\t\n")
} else {
cat("\t", "No Misfitting Items", "\t\n")
}
cat("\n\t", "*** Residual Analysis ***", "\n")
set <- which(x$EAPresid > 0.95)
if (length(set >= 1)) {
cat("\n\t",
"Percentage Extreme Residuals (.95 Posterior Probability)",
"\n")
cat(
"\t",
round(100 * length(set) / (x$N * x$K), 4),
"% (general average across persons and items)",
"\t\n"
)
## Identify Extremes
set <- which(x$EAPresid > 0.95)
set <- cbind((set %% x$N), (floor(set / x$N) + 1), exp(x$RT[set]))
dd <- order(set[, 1])
colnames(set) <- c("Person", "Item", " RT ")
rownames(set) <- rep(c(""), nrow(set))
cat("\n\t", "Extreme Residuals", "\n")
cat("\t", "Person", " Item", "\t", " RT ", "\n")
for (jj in dd) {
cat("\t")
printF(set[jj, 1], w = 6, d = 0)
cat("\t")
printF(set[jj, 2], w = 6, d = 0)
cat("\t")
printF(set[jj, 3], w = 8, d = 4)
cat("\n")
}
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat(
"\t",
round(100 * length(which(x$EAPKS < 0.05))) / x$K,
"%",
"of items has non-lognormally distributed residuals",
"\t\n"
)
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
} else {
cat("\t", "No Extreme Residuals", "\t\n")
cat("\n\t", "Kolmogorov Smirnov Test (5% level)", "\n")
cat("\t", round(100 * length(which(x$EAPKS < 0.05))) / x$K, "%", "\t\n")
set <- which(x$EAPKS < 0.05)
if (length(set) > 0) {
cat("\t", "Item", "\t P-value ", "\n")
for (jj in 1:length(set)) {
cat("\t")
printF(set[jj], w = 6, d = 0)
cat("\t")
printF(x$EAPKS[set[jj]], w = 6, d = 3)
cat("\n")
}
}
}
}
cat("\n\n")
}
#' @method print summary.LNIRTQ
#' @export
print.summary.LNIRTQ <- function(x, ...)
{
if (!is.null(x$object$data)) {
# sim data
summaryIRTQ(out = x$object, data = x$object$data)
}
else {
summaryIRTQ(out = x$object)
}
}
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