tests/testthat/test-flipformat.R
In NumbersInternational/flipRegression: Estimates standard regression models
context("flipFormat tests")
data(bank, package = "flipExampleData")
zformula <- formula("Overall ~ Fees + Interest + Phone + Branch + Online + ATM")
sb <- bank$ID > 100
attr(sb, "label") <- "ID greater than 100"
wgt <- bank$ID
attr(wgt, "label") <- "ID"
bank$dep <- (unclass(bank$Overall) - 1) / 6
attr(bank$dep, "label") <- "Overall satisfaction"
attr(bank$Fees, "label") <- "Fees paid"
attr(bank$Online, "label") <- "Online banking"
bank$fBranch <- factor(bank$Branch)
attr(bank$fBranch, "label") <- "Branch as a factor"
attr(bank$Overall, "label") <- "Overall satisfaction"
library(flipRegression)
# Below tests fail (optimization errors when run inside testthat run on the subset of 200 rows.
# Hence are run on the full data set. They do not fail when run outside testthat.
test_that("Regression: Variable names to labels",
{
# Variable labels
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Ordered Logit",
subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[1], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[4], "Branch as a factor: 2")
# Multiple imputation
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE, missing = "Multiple imputation"))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
})
#### REDUCE DATA SIZE FOR TESTS WITHOUT NUMERICAL EQUALITY ###
bank <- bank[sample(nrow(bank), 200), ] # random sample of 200 rows to improve perfomance
zformula <- formula("Overall ~ Fees + Interest + Phone + Branch + Online + ATM")
sb <- bank$ID > 100
attr(sb, "label") <- "ID greater than 100"
wgt <- bank$ID
attr(wgt, "label") <- "ID"
bank$dep <- (unclass(bank$Overall) - 1) / 6
attr(bank$dep, "label") <- "Overall satisfaction"
attr(bank$Fees, "label") <- "Fees paid"
attr(bank$Online, "label") <- "Online banking"
bank$fBranch <- factor(bank$Branch)
attr(bank$fBranch, "label") <- "Branch as a factor"
attr(bank$Overall, "label") <- "Overall satisfaction"
test_that("DS-1467 and 1468",
{
state = factor(rep(c("NSW","VC"), 2))
attr(state, "label") = "State"
attr(state, "question") = "State1"
expect_equal(Labels(state), "State1: State")
attr(state, "questiontype") = "PickAny"
expect_equal(Labels(state), "State1: State")
z = data.frame(state, state)
expect_equal(as.character(Labels(z)), rep("State1: State", 2))
attr(state, "questiontype") = "Date"
expect_equal(Labels(state), "State1")
attr(state, "questiontype") = "Number"
expect_equal(Labels(state), "State1")
attr(state, "questiontype") = "PickOne"
expect_equal(Labels(state), "State1")
attr(state, "questiontype") = "Text"
expect_equal(Labels(state), "State1")
z = data.frame(state, state)
expect_equal(as.character(Labels(z)), rep("State1", 2))
attr(state, "question") = ""
expect_equal(Labels(state), "State")
attr(state, "question") = NULL
expect_equal(Labels(state), "State")
bank$overall_dog = bank$Overall
bank$zx = bank$Fees
attr(bank$zx, "label") = "Label"
attr(bank$zx, "question") = "Question"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Question: Label")
attr(bank$zx, "questiontype") = "PickAny"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Question: Label")
attr(bank$zx, "questiontype") = "PickOne"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Question")
attr(bank$zx, "question") = "Label"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Label")
#DS-1468
Regression(overall_dog ~ Fees, data = bank, show.labels = TRUE)
})
test_that("Labels",
{
data("phone", package = "flipExampleData")
# A data frame with labels for everything
expect_equal(as.character(Labels(phone, names(phone))), as.character(unlist(sapply(phone, function(x) attr(x, "label")))))
# A few missing labels
phone <- phone[,1:6]
attr(phone[, 1], "label") <- NULL
attr(phone[, 3], "label") <- NULL
expect_equal(Labels(phone, names(phone)), c("id", "Does respondent have a mobile phone?", "q2", "Occupation", "Age", "Top of mind awareness"))
# Backticks put in manually.
names(phone) <- paste0("`", names(phone), "`")
expect_equal(Labels(phone, names(phone)), c("id", "Does respondent have a mobile phone?", "q2", "Occupation", "Age", "Top of mind awareness"))
#Factors in regression models
data("cola", package = "flipExampleData")
factor.coefficient.names <- suppressWarnings(names(coef(lm(Q2 ~ Q3, data = cola))))
expect_equal(Labels(cola, factor.coefficient.names), c("(Intercept)", "Q3. Age: 25 to 29", "Q3. Age: 30 to 34", "Q3. Age: 35 to 39", "Q3. Age: 40 to 44", "Q3. Age: 45 to 49", "Q3. Age: 50 to 54", "Q3. Age: 55 to 64", "Q3. Age: 65 or more"))
# Regression.
data("bank", package = "flipExampleData")
zbank <- bank[1:200,]
set.seed(23442)
zbank$rnd <- runif(nrow(zbank))
zbank$rnd1 <- runif(nrow(zbank))
zbank$rnd2 <- runif(nrow(zbank))
zbank$rnd3 <- runif(nrow(zbank))
zbank$rnd4 <- runif(nrow(zbank))
attr(bank$Overall, "label") <- "Overall satisfaction"
attr(bank$Fees, "label") <- "Fees paid"
attr(bank$Online, "label") <- "Online banking"
data("cola", package = "flipExampleData")
cola <- cola[1:150,]
cola$Q3[1:100] <- NA
cola$Q3 <- unclass(cola$Q3)
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
# DS-1467
attr(bank$Fees, "question") <- "Fees paid1"
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
attr(bank$Fees, "questiontype") <- "PickAny"
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
attr(bank$Fees, "questiontype") <- "PickOne"
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
# Some variables have labels and others do not.
z <- data.frame(a = 1:10, b = 1:10, c = 1:10)
flipFormat::Labels(z) <- c("A", "B")
expect_equal(as.character(flipFormat::Labels(z)), c("A", "B", "c"))
})
data(bank, package = "flipExampleData")
test_that("BaseDescription",
{
library(flipRegression)
# Unweighted, unfiltered
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank)),
NA)
#z$sample.description
# Weighted
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank, weights = ID)),
NA)
#z$sample.description
# Filtered
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank, subset = ID > 0.5)),
NA)
#z$sample.description
# Weighted, Filtered
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank, weights = ID)),
NA)
#z$sample.description
})
test_that("Numeric dependent ~ numeric, factor, numeric factor",
{
data(colas, package= "flipExampleData")
library(flipRegression)
colas$num <- colas$q1a
colas$q1b <- as.numeric(unclass(colas$q1a))
colas$q1c <- as.numeric(unclass(colas$q1c))
z <-suppressWarnings(Regression(num ~ q1b + q3 + q1c + d3, data = colas, detail = FALSE, show.labels = TRUE))
expect_equal( rownames(z$summary$coefficients)[11], "Gender: Female")
})
test_that("Regression: labels are extracted from variables containing $",
{
library(flipRegression)
attach(bank)
z = data.frame(q = Fees)
zz <- rownames(Regression(Overall ~ z$q + Phone, detail = FALSE, show.labels = TRUE)$summary$coef)[2]
expect_equal(zz, "Fees paid")
detach(bank)
})
test_that("Regression: Variable names to labels",
{
# Variable names
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = FALSE))
expect_equal(rownames(z$summary$coefficients)[5], "fBranch2")
expect_equal(rownames(z$summary$coefficients)[2], "Fees")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Binary Logit", subset = sb, weights = wgt, detail = FALSE, show.labels = FALSE))
expect_equal(rownames(z$summary$coefficients)[5], "fBranch2")
expect_equal(rownames(z$summary$coefficients)[2], "Fees")
# Variable labels
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Binary Logit", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Multinomial Logit", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(colnames(z$summary$coefficients)[2], "Fees paid")
expect_equal(colnames(z$summary$coefficients)[5], "Branch as a factor: 2")
# This test is run above on the full data set
#z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Ordered Logit",
# subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE)
#expect_equal(rownames(z$summary$coefficients)[1], "Fees paid")
#expect_equal(rownames(z$summary$coefficients)[4], "Branch as a factor: 2")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Poisson", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
# Small binary logit
data(cola, package = "flipExampleData")
attr(cola$Q2, "label") <- "Gender"
attr(cola$Q3, "label") <- "Age of person"
z <- suppressWarnings(Regression(Q3 ~ Q2, data = cola, type = "Binary Logit", detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Gender: Female")
# Multiple imputation
# This test is run above on the full data set
#z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE, missing = "Multiple imputation"))
#expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
#expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
})
test_that("RegressionTable",{
ft <- "Yo! This footer specifically designed
to communicate important information.
Since it is so important, it will of course
extend over many lines. In fact, on narrow tables,
it might take >3. On wide tables, it might only
require one. Feel free to adjust the width,
and the importance and significance does not
go away."
data(weight, package = "flipExampleData")
z = summary(lm(Weight ~ Height + Age, data = weight))$coef
RegressionTable(z, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog", p.cutoff = 0.05)
expect_error(RegressionTable(z, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog"), NA)
## Linear regression
suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online +ATM, data = bank, detail = FALSE))
# Linear regression with robust se
suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online +ATM, data = bank, robust.se = TRUE, detail = FALSE))
# Ordered logit (has a z statistic rather than a t)
suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online +ATM, data = bank, type = "Ordered Logit", detail = FALSE))
coef.matrix <- summary(lm(Sepal.Length ~ Species * Sepal.Width, iris))$coef
rownames(coef.matrix)[1] <- "Big dog"
RegressionTable(coef.matrix, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog")
expect_error(RegressionTable(coef.matrix, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog"), NA)
})
NumbersInternational/flipRegression documentation built on March 2, 2024, 10:42 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
context("flipFormat tests")
data(bank, package = "flipExampleData")
zformula <- formula("Overall ~ Fees + Interest + Phone + Branch + Online + ATM")
sb <- bank$ID > 100
attr(sb, "label") <- "ID greater than 100"
wgt <- bank$ID
attr(wgt, "label") <- "ID"
bank$dep <- (unclass(bank$Overall) - 1) / 6
attr(bank$dep, "label") <- "Overall satisfaction"
attr(bank$Fees, "label") <- "Fees paid"
attr(bank$Online, "label") <- "Online banking"
bank$fBranch <- factor(bank$Branch)
attr(bank$fBranch, "label") <- "Branch as a factor"
attr(bank$Overall, "label") <- "Overall satisfaction"
library(flipRegression)
# Below tests fail (optimization errors when run inside testthat run on the subset of 200 rows.
# Hence are run on the full data set. They do not fail when run outside testthat.
test_that("Regression: Variable names to labels",
{
# Variable labels
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Ordered Logit",
subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[1], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[4], "Branch as a factor: 2")
# Multiple imputation
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE, missing = "Multiple imputation"))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
})
#### REDUCE DATA SIZE FOR TESTS WITHOUT NUMERICAL EQUALITY ###
bank <- bank[sample(nrow(bank), 200), ] # random sample of 200 rows to improve perfomance
zformula <- formula("Overall ~ Fees + Interest + Phone + Branch + Online + ATM")
sb <- bank$ID > 100
attr(sb, "label") <- "ID greater than 100"
wgt <- bank$ID
attr(wgt, "label") <- "ID"
bank$dep <- (unclass(bank$Overall) - 1) / 6
attr(bank$dep, "label") <- "Overall satisfaction"
attr(bank$Fees, "label") <- "Fees paid"
attr(bank$Online, "label") <- "Online banking"
bank$fBranch <- factor(bank$Branch)
attr(bank$fBranch, "label") <- "Branch as a factor"
attr(bank$Overall, "label") <- "Overall satisfaction"
test_that("DS-1467 and 1468",
{
state = factor(rep(c("NSW","VC"), 2))
attr(state, "label") = "State"
attr(state, "question") = "State1"
expect_equal(Labels(state), "State1: State")
attr(state, "questiontype") = "PickAny"
expect_equal(Labels(state), "State1: State")
z = data.frame(state, state)
expect_equal(as.character(Labels(z)), rep("State1: State", 2))
attr(state, "questiontype") = "Date"
expect_equal(Labels(state), "State1")
attr(state, "questiontype") = "Number"
expect_equal(Labels(state), "State1")
attr(state, "questiontype") = "PickOne"
expect_equal(Labels(state), "State1")
attr(state, "questiontype") = "Text"
expect_equal(Labels(state), "State1")
z = data.frame(state, state)
expect_equal(as.character(Labels(z)), rep("State1", 2))
attr(state, "question") = ""
expect_equal(Labels(state), "State")
attr(state, "question") = NULL
expect_equal(Labels(state), "State")
bank$overall_dog = bank$Overall
bank$zx = bank$Fees
attr(bank$zx, "label") = "Label"
attr(bank$zx, "question") = "Question"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Question: Label")
attr(bank$zx, "questiontype") = "PickAny"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Question: Label")
attr(bank$zx, "questiontype") = "PickOne"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Question")
attr(bank$zx, "question") = "Label"
z = Regression(overall_dog ~ zx, data = bank, show.labels = TRUE)
expect_equal(rownames(z$summary$coefficients)[[2]], "Label")
#DS-1468
Regression(overall_dog ~ Fees, data = bank, show.labels = TRUE)
})
test_that("Labels",
{
data("phone", package = "flipExampleData")
# A data frame with labels for everything
expect_equal(as.character(Labels(phone, names(phone))), as.character(unlist(sapply(phone, function(x) attr(x, "label")))))
# A few missing labels
phone <- phone[,1:6]
attr(phone[, 1], "label") <- NULL
attr(phone[, 3], "label") <- NULL
expect_equal(Labels(phone, names(phone)), c("id", "Does respondent have a mobile phone?", "q2", "Occupation", "Age", "Top of mind awareness"))
# Backticks put in manually.
names(phone) <- paste0("`", names(phone), "`")
expect_equal(Labels(phone, names(phone)), c("id", "Does respondent have a mobile phone?", "q2", "Occupation", "Age", "Top of mind awareness"))
#Factors in regression models
data("cola", package = "flipExampleData")
factor.coefficient.names <- suppressWarnings(names(coef(lm(Q2 ~ Q3, data = cola))))
expect_equal(Labels(cola, factor.coefficient.names), c("(Intercept)", "Q3. Age: 25 to 29", "Q3. Age: 30 to 34", "Q3. Age: 35 to 39", "Q3. Age: 40 to 44", "Q3. Age: 45 to 49", "Q3. Age: 50 to 54", "Q3. Age: 55 to 64", "Q3. Age: 65 or more"))
# Regression.
data("bank", package = "flipExampleData")
zbank <- bank[1:200,]
set.seed(23442)
zbank$rnd <- runif(nrow(zbank))
zbank$rnd1 <- runif(nrow(zbank))
zbank$rnd2 <- runif(nrow(zbank))
zbank$rnd3 <- runif(nrow(zbank))
zbank$rnd4 <- runif(nrow(zbank))
attr(bank$Overall, "label") <- "Overall satisfaction"
attr(bank$Fees, "label") <- "Fees paid"
attr(bank$Online, "label") <- "Online banking"
data("cola", package = "flipExampleData")
cola <- cola[1:150,]
cola$Q3[1:100] <- NA
cola$Q3 <- unclass(cola$Q3)
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
# DS-1467
attr(bank$Fees, "question") <- "Fees paid1"
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
attr(bank$Fees, "questiontype") <- "PickAny"
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
attr(bank$Fees, "questiontype") <- "PickOne"
suppressWarnings(Regression(Overall ~ Fees, data = bank, type = "Ordered Logit", missing = "Multiple imputation", detail = FALSE, show.labels = TRUE))
# Some variables have labels and others do not.
z <- data.frame(a = 1:10, b = 1:10, c = 1:10)
flipFormat::Labels(z) <- c("A", "B")
expect_equal(as.character(flipFormat::Labels(z)), c("A", "B", "c"))
})
data(bank, package = "flipExampleData")
test_that("BaseDescription",
{
library(flipRegression)
# Unweighted, unfiltered
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank)),
NA)
#z$sample.description
# Weighted
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank, weights = ID)),
NA)
#z$sample.description
# Filtered
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank, subset = ID > 0.5)),
NA)
#z$sample.description
# Weighted, Filtered
expect_error(z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online + ATM, data = bank, weights = ID)),
NA)
#z$sample.description
})
test_that("Numeric dependent ~ numeric, factor, numeric factor",
{
data(colas, package= "flipExampleData")
library(flipRegression)
colas$num <- colas$q1a
colas$q1b <- as.numeric(unclass(colas$q1a))
colas$q1c <- as.numeric(unclass(colas$q1c))
z <-suppressWarnings(Regression(num ~ q1b + q3 + q1c + d3, data = colas, detail = FALSE, show.labels = TRUE))
expect_equal( rownames(z$summary$coefficients)[11], "Gender: Female")
})
test_that("Regression: labels are extracted from variables containing $",
{
library(flipRegression)
attach(bank)
z = data.frame(q = Fees)
zz <- rownames(Regression(Overall ~ z$q + Phone, detail = FALSE, show.labels = TRUE)$summary$coef)[2]
expect_equal(zz, "Fees paid")
detach(bank)
})
test_that("Regression: Variable names to labels",
{
# Variable names
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = FALSE))
expect_equal(rownames(z$summary$coefficients)[5], "fBranch2")
expect_equal(rownames(z$summary$coefficients)[2], "Fees")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Binary Logit", subset = sb, weights = wgt, detail = FALSE, show.labels = FALSE))
expect_equal(rownames(z$summary$coefficients)[5], "fBranch2")
expect_equal(rownames(z$summary$coefficients)[2], "Fees")
# Variable labels
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Binary Logit", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Multinomial Logit", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(colnames(z$summary$coefficients)[2], "Fees paid")
expect_equal(colnames(z$summary$coefficients)[5], "Branch as a factor: 2")
# This test is run above on the full data set
#z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Ordered Logit",
# subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE)
#expect_equal(rownames(z$summary$coefficients)[1], "Fees paid")
#expect_equal(rownames(z$summary$coefficients)[4], "Branch as a factor: 2")
z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Poisson", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
# Small binary logit
data(cola, package = "flipExampleData")
attr(cola$Q2, "label") <- "Gender"
attr(cola$Q3, "label") <- "Age of person"
z <- suppressWarnings(Regression(Q3 ~ Q2, data = cola, type = "Binary Logit", detail = FALSE, show.labels = TRUE))
expect_equal(rownames(z$summary$coefficients)[2], "Gender: Female")
# Multiple imputation
# This test is run above on the full data set
#z <- suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + fBranch + Online + ATM, data = bank, type = "Linear", subset = sb, weights = wgt, detail = FALSE, show.labels = TRUE, missing = "Multiple imputation"))
#expect_equal(rownames(z$summary$coefficients)[2], "Fees paid")
#expect_equal(rownames(z$summary$coefficients)[5], "Branch as a factor: 2")
})
test_that("RegressionTable",{
ft <- "Yo! This footer specifically designed
to communicate important information.
Since it is so important, it will of course
extend over many lines. In fact, on narrow tables,
it might take >3. On wide tables, it might only
require one. Feel free to adjust the width,
and the importance and significance does not
go away."
data(weight, package = "flipExampleData")
z = summary(lm(Weight ~ Height + Age, data = weight))$coef
RegressionTable(z, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog", p.cutoff = 0.05)
expect_error(RegressionTable(z, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog"), NA)
## Linear regression
suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online +ATM, data = bank, detail = FALSE))
# Linear regression with robust se
suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online +ATM, data = bank, robust.se = TRUE, detail = FALSE))
# Ordered logit (has a z statistic rather than a t)
suppressWarnings(Regression(Overall ~ Fees + Interest + Phone + Branch + Online +ATM, data = bank, type = "Ordered Logit", detail = FALSE))
coef.matrix <- summary(lm(Sepal.Length ~ Species * Sepal.Width, iris))$coef
rownames(coef.matrix)[1] <- "Big dog"
RegressionTable(coef.matrix, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog")
expect_error(RegressionTable(coef.matrix, TRUE, footer = ft, title = "My awesome regression", subtitle = "Big brown dog"), NA)
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.