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R/summaryf_MRMC.R
In MRMCbinary: Multi-Reader Multi-Case Analysis of Binary Diagnostic Tests
Defines functions
sens_spec_MRMCbinary_ss
all_MRMCbinary_ss
####
all_MRMCbinary_ss <- function(object, digits) {
x <- object
## Data Structure
cat("\n")
cat("###### 1. Data Structure \n")
cat(paste0("The total number of modalities : ", x$n.modality, "\n"))
cat(paste0("The total number of readers : ", x$n.reader, "\n"))
cat(paste0("The total number of cases : ", x$n.case, "\n"))
cat(paste0("The number of diseased cases : ", x$n.diseased, "\n"))
cat(paste0("The number of non-diseased cases : ", x$n.nondiseased, "\n"))
cat("\n")
## Variable List
cat("###### 2. Variable List \n")
if (x$effect == "Both") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
cat(paste0("Referecen for Reader variable : ", x$reference.Reader, "\n"))
} else if (x$effect == "Modality") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
} else if (x$effect == "Reader") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Reader variable : ", x$reference.Reader, "\n"))
}
cat("\n")
## Analysis Description
cat("###### 3. Analysis Description \n")
if (x$effect == "Both") {
cat(paste0("Effect to compare : Both (Modality effect and Reader effect) \n"))
cat(paste0("Use of interaction term : ", x$interaction, "\n"))
} else {
cat(paste0("Effect to compare: ", x$effect, " effect \n"))
}
cat("\n")
## Summary results
cat("###### 4. Analysis Result \n")
if (x$effect == "Both") {
##########################################################################
## Sensitivity with interaction term between modality and reader
cat("#### 4.1. Sensitivity \n")
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_sen <- round(x$CLR_sen, digits = digits)
temp_CLR_sen_p <- format_p(xx = x$CLR_sen$P.value, digits = digits)
mat_CLR_sen <- data.frame(format_f(xx = temp_CLR_sen$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_sen$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_sen$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_sen$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_sen_p)
colnames(mat_CLR_sen) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_sen) <- rownames(temp_CLR_sen)
base::print(mat_CLR_sen)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test_sen <- rbind(x$CLR_LRT_sen, x$CLR_Score_sen, x$CLR_Wald_sen)
temp_test_sen_p <- format_p(xx = temp_test_sen$P.value, digits = digits)
temp_test_sen <- round(temp_test_sen, digits = digits)
mat_test_sen <- data.frame(format_f(xx = temp_test_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_sen$DF,
temp_test_sen_p)
colnames(mat_test_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_sen) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_sen)
cat("\n")
if (x$interaction == TRUE) {
cat("## 4.1.3. Cochran's Q Test \n")
temp_Q_MN_sen <- round(x$Q_MN_sen, digits = digits)
temp_Q_MN_sen_p <- format_p(xx = x$Q_MN_sen$P.value, digits = digits)
mat_Q_MN_sen <- data.frame(format_f(xx = temp_Q_MN_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_sen$DF,
temp_Q_MN_sen_p)
colnames(mat_Q_MN_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_sen) <- c("")
base::print(mat_Q_MN_sen)
cat("\n")
}
##########################################################################
## Specificity with interaction term between modality and reader
cat("#### 4.2. Specificity \n")
cat("## 4.2.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 0, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_spe <- round(x$CLR_spe, digits = digits)
temp_CLR_spe_p <- format_p(xx = x$CLR_spe$P.value, digits = digits)
mat_CLR_spe <- data.frame(format_f(xx = temp_CLR_spe$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_spe$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_spe$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_spe$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_spe_p)
colnames(mat_CLR_spe) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_spe) <- rownames(temp_CLR_spe)
base::print(mat_CLR_spe)
cat("\n")
cat("## 4.2.2. Test from Conditional Logistic Regression \n")
temp_test_spe <- rbind(x$CLR_LRT_spe, x$CLR_Score_spe, x$CLR_Wald_spe)
temp_test_spe_p <- format_p(xx = temp_test_spe$P.value, digits = digits)
temp_test_spe <- round(temp_test_spe, digits = digits)
mat_test_spe <- data.frame(format_f(xx = temp_test_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_spe$DF,
temp_test_spe_p)
colnames(mat_test_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_spe) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_spe)
cat("\n")
if (x$interaction == TRUE) {
cat("## 4.2.3. Cochran's Q Test \n")
temp_Q_MN_spe <- round(x$Q_MN_spe, digits = digits)
temp_Q_MN_spe_p <- format_p(xx = x$Q_MN_spe$P.value, digits = digits)
mat_Q_MN_spe <- data.frame(format_f(xx = temp_Q_MN_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_spe$DF,
temp_Q_MN_spe_p)
colnames(mat_Q_MN_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_spe) <- c("")
base::print(mat_Q_MN_spe)
cat("\n")
}
} else {
##########################################################################
## Sensitivity
cat("#### 4.1. Sensitivity \n")
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_sen <- round(x$CLR_sen, digits = digits)
temp_CLR_sen_p <- format_p(xx = x$CLR_sen$P.value, digits = digits)
mat_CLR_sen <- data.frame(format_f(xx = temp_CLR_sen$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_sen$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_sen$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_sen$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_sen_p)
colnames(mat_CLR_sen) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_sen) <- rownames(temp_CLR_sen)
base::print(mat_CLR_sen)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test_sen <- rbind(x$CLR_LRT_sen, x$CLR_Score_sen, x$CLR_Wald_sen)
temp_test_sen_p <- format_p(xx = temp_test_sen$P.value, digits = digits)
temp_test_sen <- round(temp_test_sen, digits = digits)
mat_test_sen <- data.frame(format_f(xx = temp_test_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_sen$DF,
temp_test_sen_p)
colnames(mat_test_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_sen) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_sen)
cat("\n")
if (x$effect == "Modality") {
if (x$n.modality == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
} else if (x$effect == "Reader") {
if (x$n.reader == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
}
temp_Q_MN_sen <- round(x$Q_MN_sen, digits = digits)
temp_Q_MN_sen_p <- format_p(xx = x$Q_MN_sen$P.value, digits = digits)
mat_Q_MN_sen <- data.frame(format_f(xx = temp_Q_MN_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_sen$DF,
temp_Q_MN_sen_p)
colnames(mat_Q_MN_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_sen) <- c("")
base::print(mat_Q_MN_sen)
cat("\n")
##########################################################################
## Specificity
cat("#### 4.2. Specificity \n")
cat("## 4.2.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 0, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_spe <- round(x$CLR_spe, digits = digits)
temp_CLR_spe_p <- format_p(xx = x$CLR_spe$P.value, digits = digits)
mat_CLR_spe <- data.frame(format_f(xx = temp_CLR_spe$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_spe$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_spe$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_spe$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_spe_p)
colnames(mat_CLR_spe) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_spe) <- rownames(temp_CLR_spe)
base::print(mat_CLR_spe)
cat("\n")
cat("## 4.2.2. Test from Conditional Logistic Regression \n")
temp_test_spe <- rbind(x$CLR_LRT_spe, x$CLR_Score_spe, x$CLR_Wald_spe)
temp_test_spe_p <- format_p(xx = temp_test_spe$P.value, digits = digits)
temp_test_spe <- round(temp_test_spe, digits = digits)
mat_test_spe <- data.frame(format_f(xx = temp_test_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_spe$DF,
temp_test_spe_p)
colnames(mat_test_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_spe) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_spe)
cat("\n")
if (x$effect == "Modality") {
if (x$n.modality == 2) {
cat("## 4.2.3. McNemar's Test \n")
} else {
cat("## 4.2.3. Cochran's Q Test \n")
}
} else if (x$effect == "Reader") {
if (x$n.reader == 2) {
cat("## 4.2.3. McNemar's Test \n")
} else {
cat("## 4.2.3. Cochran's Q Test \n")
}
}
temp_Q_MN_spe <- round(x$Q_MN_spe, digits = digits)
temp_Q_MN_spe_p <- format_p(xx = x$Q_MN_spe$P.value, digits = digits)
mat_Q_MN_spe <- data.frame(format_f(xx = temp_Q_MN_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_spe$DF,
temp_Q_MN_spe_p)
colnames(mat_Q_MN_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_spe) <- c("")
base::print(mat_Q_MN_spe)
cat("\n")
}
# cat("\n")
invisible(x)
}
####
sens_spec_MRMCbinary_ss <- function(object, digits) {
x <- object
## Data Structure
cat("\n")
if (x$measure == "Sensitivity") {
cat("###### 1. Data Structure \n")
cat(paste0("The total number of modalities : ", x$n.modality, "\n"))
cat(paste0("The total number of readers : ", x$n.reader, "\n"))
cat(paste0("The total number of cases : ", x$n.case, "\n"))
cat(paste0("The number of diseased cases : ", x$n.diseased, "\n"))
} else {
cat("###### 1. Data Structure \n")
cat(paste0("The total number of modalities : ", x$n.modality, "\n"))
cat(paste0("The total number of readers : ", x$n.reader, "\n"))
cat(paste0("The total number of cases : ", x$n.case, "\n"))
cat(paste0("The number of non-diseased cases : ", x$n.nondiseased, "\n"))
}
cat("\n")
## Variable List
cat("###### 2. Variable List \n")
if (x$effect == "Both") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
if (!is.null(x$args$D)) {
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
}
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
cat(paste0("Referecen for Reader variable : ", x$reference.Reader, "\n"))
} else if (x$effect == "Modality") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
if (!is.null(x$args$D)) {
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
}
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
} else if (x$effect == "Reader") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
if (!is.null(x$args$D)) {
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
}
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Reader variable : ", x$reference.Reader, "\n"))
}
cat("\n")
## Analysis Description
cat("###### 3. Analysis Description \n")
if (x$effect == "Both") {
cat(paste0("Effect to compare : Both (Modality effect and Reader effect) \n"))
cat(paste0("Use of interaction term : ", x$interaction, "\n"))
} else {
cat(paste0("Effect to compare: ", x$effect, " effect \n"))
}
cat("\n")
## Summary results
cat("###### 4. Analysis Result \n")
if (x$effect == "Both") {
##########################################################################
## MRMC model with interaction term between modality and reader
cat(paste0("#### 4.1. ", x$measure, " \n"))
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
if (!is.null(x$args$D)) {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
} else {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data, method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
}
temp_CLR <- round(x$CLR, digits = digits)
temp_CLR_p <- format_p(xx = x$CLR$P.value, digits = digits)
mat_CLR <- data.frame(format_f(xx = temp_CLR$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_p)
colnames(mat_CLR) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR) <- rownames(temp_CLR)
base::print(mat_CLR)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test <- rbind(x$CLR_LRT, x$CLR_Score, x$CLR_Wald)
temp_test_p <- format_p(xx = temp_test$P.value, digits = digits)
temp_test <- round(temp_test, digits = digits)
mat_test <- data.frame(format_f(xx = temp_test$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test$DF,
temp_test_p)
colnames(mat_test) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test)
cat("\n")
if (x$interaction == TRUE) {
cat("## 4.1.3. Cochran's Q Test \n")
temp_Q_MN <- round(x$Q_MN, digits = digits)
temp_Q_MN_p <- format_p(xx = x$Q_MN$P.value, digits = digits)
mat_Q_MN <- data.frame(format_f(xx = temp_Q_MN$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN$DF,
temp_Q_MN_p)
colnames(mat_Q_MN) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN) <- c("")
base::print(mat_Q_MN)
cat("\n")
}
} else {
##########################################################################
cat(paste0("#### 4.1. ", x$measure, " \n"))
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
if (!is.null(x$args$D)) {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
} else {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data, method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
}
temp_CLR <- round(x$CLR, digits = digits)
temp_CLR_p <- format_p(xx = x$CLR$P.value, digits = digits)
mat_CLR <- data.frame(format_f(xx = temp_CLR$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_p)
colnames(mat_CLR) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR) <- rownames(temp_CLR)
base::print(mat_CLR)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test <- rbind(x$CLR_LRT, x$CLR_Score, x$CLR_Wald)
temp_test_p <- format_p(xx = temp_test$P.value, digits = digits)
temp_test <- round(temp_test, digits = digits)
mat_test <- data.frame(format_f(xx = temp_test$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test$DF,
temp_test_p)
colnames(mat_test) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test)
cat("\n")
if (x$effect == "Modality") {
if (x$n.modality == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
} else if (x$effect == "Reader") {
if (x$n.reader == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
}
temp_Q_MN <- round(x$Q_MN, digits = digits)
temp_Q_MN_p <- format_p(xx = x$Q_MN$P.value, digits = digits)
mat_Q_MN <- data.frame(format_f(xx = temp_Q_MN$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN$DF,
temp_Q_MN_p)
colnames(mat_Q_MN) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN) <- c("")
base::print(mat_Q_MN)
cat("\n")
}
}
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MRMCbinary documentation built on April 3, 2025, 9:17 p.m.
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Defines functions sens_spec_MRMCbinary_ss all_MRMCbinary_ss
####
all_MRMCbinary_ss <- function(object, digits) {
x <- object
## Data Structure
cat("\n")
cat("###### 1. Data Structure \n")
cat(paste0("The total number of modalities : ", x$n.modality, "\n"))
cat(paste0("The total number of readers : ", x$n.reader, "\n"))
cat(paste0("The total number of cases : ", x$n.case, "\n"))
cat(paste0("The number of diseased cases : ", x$n.diseased, "\n"))
cat(paste0("The number of non-diseased cases : ", x$n.nondiseased, "\n"))
cat("\n")
## Variable List
cat("###### 2. Variable List \n")
if (x$effect == "Both") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
cat(paste0("Referecen for Reader variable : ", x$reference.Reader, "\n"))
} else if (x$effect == "Modality") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
} else if (x$effect == "Reader") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Reader variable : ", x$reference.Reader, "\n"))
}
cat("\n")
## Analysis Description
cat("###### 3. Analysis Description \n")
if (x$effect == "Both") {
cat(paste0("Effect to compare : Both (Modality effect and Reader effect) \n"))
cat(paste0("Use of interaction term : ", x$interaction, "\n"))
} else {
cat(paste0("Effect to compare: ", x$effect, " effect \n"))
}
cat("\n")
## Summary results
cat("###### 4. Analysis Result \n")
if (x$effect == "Both") {
##########################################################################
## Sensitivity with interaction term between modality and reader
cat("#### 4.1. Sensitivity \n")
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_sen <- round(x$CLR_sen, digits = digits)
temp_CLR_sen_p <- format_p(xx = x$CLR_sen$P.value, digits = digits)
mat_CLR_sen <- data.frame(format_f(xx = temp_CLR_sen$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_sen$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_sen$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_sen$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_sen_p)
colnames(mat_CLR_sen) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_sen) <- rownames(temp_CLR_sen)
base::print(mat_CLR_sen)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test_sen <- rbind(x$CLR_LRT_sen, x$CLR_Score_sen, x$CLR_Wald_sen)
temp_test_sen_p <- format_p(xx = temp_test_sen$P.value, digits = digits)
temp_test_sen <- round(temp_test_sen, digits = digits)
mat_test_sen <- data.frame(format_f(xx = temp_test_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_sen$DF,
temp_test_sen_p)
colnames(mat_test_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_sen) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_sen)
cat("\n")
if (x$interaction == TRUE) {
cat("## 4.1.3. Cochran's Q Test \n")
temp_Q_MN_sen <- round(x$Q_MN_sen, digits = digits)
temp_Q_MN_sen_p <- format_p(xx = x$Q_MN_sen$P.value, digits = digits)
mat_Q_MN_sen <- data.frame(format_f(xx = temp_Q_MN_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_sen$DF,
temp_Q_MN_sen_p)
colnames(mat_Q_MN_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_sen) <- c("")
base::print(mat_Q_MN_sen)
cat("\n")
}
##########################################################################
## Specificity with interaction term between modality and reader
cat("#### 4.2. Specificity \n")
cat("## 4.2.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 0, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_spe <- round(x$CLR_spe, digits = digits)
temp_CLR_spe_p <- format_p(xx = x$CLR_spe$P.value, digits = digits)
mat_CLR_spe <- data.frame(format_f(xx = temp_CLR_spe$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_spe$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_spe$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_spe$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_spe_p)
colnames(mat_CLR_spe) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_spe) <- rownames(temp_CLR_spe)
base::print(mat_CLR_spe)
cat("\n")
cat("## 4.2.2. Test from Conditional Logistic Regression \n")
temp_test_spe <- rbind(x$CLR_LRT_spe, x$CLR_Score_spe, x$CLR_Wald_spe)
temp_test_spe_p <- format_p(xx = temp_test_spe$P.value, digits = digits)
temp_test_spe <- round(temp_test_spe, digits = digits)
mat_test_spe <- data.frame(format_f(xx = temp_test_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_spe$DF,
temp_test_spe_p)
colnames(mat_test_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_spe) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_spe)
cat("\n")
if (x$interaction == TRUE) {
cat("## 4.2.3. Cochran's Q Test \n")
temp_Q_MN_spe <- round(x$Q_MN_spe, digits = digits)
temp_Q_MN_spe_p <- format_p(xx = x$Q_MN_spe$P.value, digits = digits)
mat_Q_MN_spe <- data.frame(format_f(xx = temp_Q_MN_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_spe$DF,
temp_Q_MN_spe_p)
colnames(mat_Q_MN_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_spe) <- c("")
base::print(mat_Q_MN_spe)
cat("\n")
}
} else {
##########################################################################
## Sensitivity
cat("#### 4.1. Sensitivity \n")
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_sen <- round(x$CLR_sen, digits = digits)
temp_CLR_sen_p <- format_p(xx = x$CLR_sen$P.value, digits = digits)
mat_CLR_sen <- data.frame(format_f(xx = temp_CLR_sen$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_sen$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_sen$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_sen$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_sen_p)
colnames(mat_CLR_sen) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_sen) <- rownames(temp_CLR_sen)
base::print(mat_CLR_sen)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test_sen <- rbind(x$CLR_LRT_sen, x$CLR_Score_sen, x$CLR_Wald_sen)
temp_test_sen_p <- format_p(xx = temp_test_sen$P.value, digits = digits)
temp_test_sen <- round(temp_test_sen, digits = digits)
mat_test_sen <- data.frame(format_f(xx = temp_test_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_sen$DF,
temp_test_sen_p)
colnames(mat_test_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_sen) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_sen)
cat("\n")
if (x$effect == "Modality") {
if (x$n.modality == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
} else if (x$effect == "Reader") {
if (x$n.reader == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
}
temp_Q_MN_sen <- round(x$Q_MN_sen, digits = digits)
temp_Q_MN_sen_p <- format_p(xx = x$Q_MN_sen$P.value, digits = digits)
mat_Q_MN_sen <- data.frame(format_f(xx = temp_Q_MN_sen$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_sen$DF,
temp_Q_MN_sen_p)
colnames(mat_Q_MN_sen) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_sen) <- c("")
base::print(mat_Q_MN_sen)
cat("\n")
##########################################################################
## Specificity
cat("#### 4.2. Specificity \n")
cat("## 4.2.1. Conditional Logistic Regression Result \n")
## Report formula
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 0, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
temp_CLR_spe <- round(x$CLR_spe, digits = digits)
temp_CLR_spe_p <- format_p(xx = x$CLR_spe$P.value, digits = digits)
mat_CLR_spe <- data.frame(format_f(xx = temp_CLR_spe$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR_spe$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR_spe$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR_spe$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_spe_p)
colnames(mat_CLR_spe) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR_spe) <- rownames(temp_CLR_spe)
base::print(mat_CLR_spe)
cat("\n")
cat("## 4.2.2. Test from Conditional Logistic Regression \n")
temp_test_spe <- rbind(x$CLR_LRT_spe, x$CLR_Score_spe, x$CLR_Wald_spe)
temp_test_spe_p <- format_p(xx = temp_test_spe$P.value, digits = digits)
temp_test_spe <- round(temp_test_spe, digits = digits)
mat_test_spe <- data.frame(format_f(xx = temp_test_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test_spe$DF,
temp_test_spe_p)
colnames(mat_test_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test_spe) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test_spe)
cat("\n")
if (x$effect == "Modality") {
if (x$n.modality == 2) {
cat("## 4.2.3. McNemar's Test \n")
} else {
cat("## 4.2.3. Cochran's Q Test \n")
}
} else if (x$effect == "Reader") {
if (x$n.reader == 2) {
cat("## 4.2.3. McNemar's Test \n")
} else {
cat("## 4.2.3. Cochran's Q Test \n")
}
}
temp_Q_MN_spe <- round(x$Q_MN_spe, digits = digits)
temp_Q_MN_spe_p <- format_p(xx = x$Q_MN_spe$P.value, digits = digits)
mat_Q_MN_spe <- data.frame(format_f(xx = temp_Q_MN_spe$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN_spe$DF,
temp_Q_MN_spe_p)
colnames(mat_Q_MN_spe) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN_spe) <- c("")
base::print(mat_Q_MN_spe)
cat("\n")
}
# cat("\n")
invisible(x)
}
####
sens_spec_MRMCbinary_ss <- function(object, digits) {
x <- object
## Data Structure
cat("\n")
if (x$measure == "Sensitivity") {
cat("###### 1. Data Structure \n")
cat(paste0("The total number of modalities : ", x$n.modality, "\n"))
cat(paste0("The total number of readers : ", x$n.reader, "\n"))
cat(paste0("The total number of cases : ", x$n.case, "\n"))
cat(paste0("The number of diseased cases : ", x$n.diseased, "\n"))
} else {
cat("###### 1. Data Structure \n")
cat(paste0("The total number of modalities : ", x$n.modality, "\n"))
cat(paste0("The total number of readers : ", x$n.reader, "\n"))
cat(paste0("The total number of cases : ", x$n.case, "\n"))
cat(paste0("The number of non-diseased cases : ", x$n.nondiseased, "\n"))
}
cat("\n")
## Variable List
cat("###### 2. Variable List \n")
if (x$effect == "Both") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
if (!is.null(x$args$D)) {
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
}
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
cat(paste0("Referecen for Reader variable : ", x$reference.Reader, "\n"))
} else if (x$effect == "Modality") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
if (!is.null(x$args$D)) {
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
}
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Modality variable : ", x$reference.Modality, "\n"))
} else if (x$effect == "Reader") {
cat(paste0("Modality : ", as.character(x$args$Modality), "\n"))
cat(paste0("Reader : ", as.character(x$args$Reader), "\n"))
cat(paste0("Case : ", as.character(x$args$Case), "\n"))
if (!is.null(x$args$D)) {
cat(paste0("True disease status (D) : ", as.character(x$args$D), "\n"))
}
cat(paste0("Binary diagnostic test (Y) : ", as.character(x$args$Y), "\n"))
cat(paste0("Reference for Reader variable : ", x$reference.Reader, "\n"))
}
cat("\n")
## Analysis Description
cat("###### 3. Analysis Description \n")
if (x$effect == "Both") {
cat(paste0("Effect to compare : Both (Modality effect and Reader effect) \n"))
cat(paste0("Use of interaction term : ", x$interaction, "\n"))
} else {
cat(paste0("Effect to compare: ", x$effect, " effect \n"))
}
cat("\n")
## Summary results
cat("###### 4. Analysis Result \n")
if (x$effect == "Both") {
##########################################################################
## MRMC model with interaction term between modality and reader
cat(paste0("#### 4.1. ", x$measure, " \n"))
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
if (!is.null(x$args$D)) {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
} else {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data, method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
}
temp_CLR <- round(x$CLR, digits = digits)
temp_CLR_p <- format_p(xx = x$CLR$P.value, digits = digits)
mat_CLR <- data.frame(format_f(xx = temp_CLR$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_p)
colnames(mat_CLR) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR) <- rownames(temp_CLR)
base::print(mat_CLR)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test <- rbind(x$CLR_LRT, x$CLR_Score, x$CLR_Wald)
temp_test_p <- format_p(xx = temp_test$P.value, digits = digits)
temp_test <- round(temp_test, digits = digits)
mat_test <- data.frame(format_f(xx = temp_test$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test$DF,
temp_test_p)
colnames(mat_test) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test)
cat("\n")
if (x$interaction == TRUE) {
cat("## 4.1.3. Cochran's Q Test \n")
temp_Q_MN <- round(x$Q_MN, digits = digits)
temp_Q_MN_p <- format_p(xx = x$Q_MN$P.value, digits = digits)
mat_Q_MN <- data.frame(format_f(xx = temp_Q_MN$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN$DF,
temp_Q_MN_p)
colnames(mat_Q_MN) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN) <- c("")
base::print(mat_Q_MN)
cat("\n")
}
} else {
##########################################################################
cat(paste0("#### 4.1. ", x$measure, " \n"))
cat("## 4.1.1. Conditional Logistic Regression Result \n")
## Report formula
if (!is.null(x$args$D)) {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data[data$D == 1, ], method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
} else {
cat("\nclogit formula: ",
paste(paste0("survival::clogit(", x$formula, ", \n",
" data = data, method=\"exact\")"),
sep = "\n", collapse = "\n"), "\n\n", sep = "")
}
temp_CLR <- round(x$CLR, digits = digits)
temp_CLR_p <- format_p(xx = x$CLR$P.value, digits = digits)
mat_CLR <- data.frame(format_f(xx = temp_CLR$Estimate,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
# format_f(xx = temp_CLR$SE,
# numer = NULL, denom = NULL,
# percentage = FALSE, digits = digits),
paste0("[", format_f(xx = temp_CLR$Lower.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
", ", format_f(xx = temp_CLR$Upper.ci,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits), "]"),
temp_CLR_p)
colnames(mat_CLR) <- c("Odds ratio", "Confidence interval", "P value") # "Standard error"
rownames(mat_CLR) <- rownames(temp_CLR)
base::print(mat_CLR)
cat("\n")
cat("## 4.1.2. Test from Conditional Logistic Regression \n")
temp_test <- rbind(x$CLR_LRT, x$CLR_Score, x$CLR_Wald)
temp_test_p <- format_p(xx = temp_test$P.value, digits = digits)
temp_test <- round(temp_test, digits = digits)
mat_test <- data.frame(format_f(xx = temp_test$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_test$DF,
temp_test_p)
colnames(mat_test) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_test) <- c("Likelihood ratio test", "Score test", "Wald test")
base::print(mat_test)
cat("\n")
if (x$effect == "Modality") {
if (x$n.modality == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
} else if (x$effect == "Reader") {
if (x$n.reader == 2) {
cat("## 4.1.3. McNemar's Test \n")
} else {
cat("## 4.1.3. Cochran's Q Test \n")
}
}
temp_Q_MN <- round(x$Q_MN, digits = digits)
temp_Q_MN_p <- format_p(xx = x$Q_MN$P.value, digits = digits)
mat_Q_MN <- data.frame(format_f(xx = temp_Q_MN$Statistic,
numer = NULL, denom = NULL,
percentage = FALSE, digits = digits),
temp_Q_MN$DF,
temp_Q_MN_p)
colnames(mat_Q_MN) <- c("Statistic", "Degree of freedom", "P value")
rownames(mat_Q_MN) <- c("")
base::print(mat_Q_MN)
cat("\n")
}
}
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