Nothing
tests/testthat/test_significance_cell_chisq.R
In expss: Tables, Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics
if(isTRUE(getOption("covr"))) {
context("significance_cell_chisq")
test_table = text_to_columns("
row_labels Total Segment|PRO Segment|AMT Segment|DES
#Total 384 128 180 76
ADIDAS 112 92 16 4
NIKE 102 18 76 8
ASICS 67 3 56 8
MIZUNO 47 7 24 16
NEWBALANCE 56 8 8 40
", comment.char = "", check.names = FALSE)
test_table[,-1] = lapply(test_table[,-1], function(x) c(x[1], x[-1]/x[1]*100))
test_table = as.etable(test_table)
expss_digits(2)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table), res)
expect_identical(significance_cell_chisq(test_table, row_margin = "auto"), res)
expect_identical(significance_cell_chisq(test_table, row_margin = "sum_row"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 +", "14.06 -",
" 2.34 -", " 5.47 -", " 6.25 -"), `Segment|AMT` = c("180 ",
" 8.89 -", "42.22 +", "31.11 +", "13.33 ", " 4.44 -"), `Segment|DES` = c("76 ",
" 5.26 -", "10.53 -", "10.53 ", "21.05 +", "52.63 +")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, sig_labels_chisq = c("-", "+")), res)
expect_identical(significance_cell_chisq(test_table, sig_labels_chisq = c("-", "+"), subtable_marks = "both"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 ",
" 2.34 ", " 5.47 ", " 6.25 "), `Segment|AMT` = c("180 ",
" 8.89 ", "42.22 >", "31.11 >", "13.33 ", " 4.44 "), `Segment|DES` = c("76 ",
" 5.26 ", "10.53 ", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, subtable_marks = "greater"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 ", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 ", "31.11 ", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 ", "52.63 ")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, subtable_marks = "less"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76",
" 5.26", "10.53", "10.53", "21.05", "52.63")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, min_base = 100), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128", "71.88", "14.06",
" 2.34", " 5.47", " 6.25"), `Segment|AMT` = c("180 ", " 8.89 <",
"42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76",
" 5.26", "10.53", "10.53", "21.05", "52.63")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, min_base = 150), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128", "71.88", "14.06",
" 2.34", " 5.47", " 6.25"), `Segment|AMT` = c("180", " 8.89",
"42.22", "31.11", "13.33", " 4.44"), `Segment|DES` = c("76",
" 5.26", "10.53", "10.53", "21.05", "52.63")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, min_base = 400), res)
test_table = text_to_columns("
row_labels Total PRO AMT DES
#Total 384 128 180 76
ADIDAS 112 92 16 4
NIKE 102 18 76 8
ASICS 67 3 56 8
MIZUNO 47 7 24 16
NEWBALANCE 56 8 8 40
", comment.char = "", check.names = FALSE) %>% as.etable()
test_table[,-1] = lapply(test_table[,-1], function(x) c(x[1], x[-1]/x[1]*100))
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
colnames(res) = gsub(".+\\|", "", colnames(res), perl = TRUE)
expect_identical(significance_cell_chisq(test_table, row_margin = "first_column"), res)
expect_identical(significance_cell_chisq(test_table, total_column_marker = "Total"), res)
colnames(res)[2] = "#Total"
colnames(test_table)[2] = "#Total"
expect_identical(significance_cell_chisq(test_table, row_margin = "auto"), res)
res = structure(list(row_labels = c("ADIDAS", "NIKE", "ASICS", "MIZUNO",
"NEWBALANCE"), `#Total` = c("", "", "", "", ""), PRO = c(">",
"<", "<", "<", "<"), AMT = c("<", ">", ">", "", "<"), DES = c("<",
"<", "", ">", ">")), row.names = 2:6, class = c("etable", "data.frame"
))
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "none"), res)
res = structure(list(row_labels = c("ADIDAS", "NIKE", "ASICS", "MIZUNO",
"NEWBALANCE"), `#Total` = c("29.17", "26.56", "17.45", "12.24",
"14.58"), PRO = c("71.88 >", "14.06 <", " 2.34 <", " 5.47 <",
" 6.25 <"), AMT = c(" 8.89 <", "42.22 >", "31.11 >", "13.33 ",
" 4.44 <"), DES = c(" 5.26 <", "10.53 <", "10.53 ", "21.05 >",
"52.63 >")), row.names = 2:6, class = c("etable", "data.frame"
))
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "percent"), res)
expss_digits()
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "percent", digits = 2), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), `#Total` = c("384", "", "", "", "",
""), PRO = c("128", ">", "<", "<", "<", "<"), AMT = c("180",
"<", ">", ">", "", "<"), DES = c("76", "<", "<", "", ">", ">"
)), row.names = c(NA, -6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "bases"), res)
expect_identical(significance_cell_chisq(test_table[,1]), test_table[,1])
context("cell_chisq correct")
test_table = text_to_columns("
row_labels Total Segment|PRO Segment|AMT Segment|DES
#Total 384 128 180 76
ADIDAS 112 92 16 4
NIKE 102 18 76 8
ASICS 67 3 56 8
MIZUNO 47 7 24 16
NEWBALANCE 56 8 8 40
", comment.char = "", check.names = FALSE)
test_table[,-1] = lapply(test_table[,-1], function(x) c(x[1], x[-1]/x[1]*100))
test_table = as.etable(test_table)
expss_digits(2)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 ", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(
significance_cell_chisq(test_table, sig_level = 0.01, correct = TRUE),
res
)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(
significance_cell_chisq(test_table, sig_level = 0.01, correct = FALSE),
res
)
data(mtcars)
mtcars = apply_labels(mtcars,
mpg = "Miles/(US) gallon",
cyl = "Number of cylinders",
disp = "Displacement (cu.in.)",
hp = "Gross horsepower",
drat = "Rear axle ratio",
wt = "Weight (lb/1000)",
qsec = "1/4 mile time",
vs = "Engine",
vs = c("V-engine" = 0,
"Straight engine" = 1),
am = "Transmission",
am = c("Automatic" = 0,
"Manual"=1),
gear = "Number of forward gears",
carb = "Number of carburetors"
)
mtcars2 = add_rows(mtcars, mtcars, mtcars)
# table with multiple variables
tbl = cross_cpct(mtcars2, list(gear, cyl), list(total(), am, vs))
res = structure(list(row_labels = c("Number of forward gears|3", "Number of forward gears|4",
"Number of forward gears|5", "Number of forward gears|#Total cases",
"Number of cylinders|4", "Number of cylinders|6", "Number of cylinders|8",
"Number of cylinders|#Total cases"), `#Total` = c("46.88", "37.50",
"15.62", "96", "34.38", "21.88", "43.75", "96"), `Transmission|Automatic` = c("78.95 >",
"21.05 ", "<", "57 ", "15.79 <", "21.05 ", "63.16 >", "57 "
), `Transmission|Manual` = c("<", "61.54 ", "38.46 >", "39 ",
"61.54 >", "23.08 ", "15.38 <", "39 "), `Engine|V-engine` = c("66.67 >",
"11.11 <", "22.22 ", "54 ", " 5.56 <", "16.67 ", "77.78 >",
"54 "), `Engine|Straight engine` = c("21.43 <", "71.43 >", " 7.14 ",
"42 ", "71.43 >", "28.57 ", "<", "42 ")), row.names = c(NA,
-8L), class = c("etable", "data.frame"))
expect_equal(significance_cell_chisq(tbl, sig_level = .0001) , res)
expect_equal(mtcars2 %>%
tab_cells(gear, cyl) %>%
tab_cols(total(), am, vs) %>%
tab_stat_cpct() %>%
tab_last_sig_cell_chisq(sig_level = .0001) %>%
tab_pivot()
, res)
expect_equal(mtcars2 %>%
tab_significance_options(sig_level = .0001, subtable_marks = "greater", sig_labels_chisq = c("-", "+")) %>%
tab_cells(gear, cyl) %>%
tab_cols(total(), am, vs) %>%
tab_stat_cpct() %>%
tab_last_sig_cell_chisq() %>%
tab_pivot()
, significance_cell_chisq(tbl, sig_level = .0001, subtable_marks = "greater", sig_labels_chisq = c("-", "+")))
expect_equal(mtcars2 %>%
tab_significance_options(sig_level = .0001,
subtable_marks = "greater",
sig_labels_chisq = c("-", "+"),
row_margin = "sum_row"
) %>%
tab_cells(gear, cyl) %>%
tab_cols(total(), am, vs) %>%
tab_stat_cpct() %>%
tab_last_sig_cell_chisq() %>%
tab_pivot()
, significance_cell_chisq(tbl, sig_level = .0001,
subtable_marks = "greater",
sig_labels_chisq = c("-", "+"),
row_margin = "first_column"
))
expss_digits()
}
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if(isTRUE(getOption("covr"))) {
context("significance_cell_chisq")
test_table = text_to_columns("
row_labels Total Segment|PRO Segment|AMT Segment|DES
#Total 384 128 180 76
ADIDAS 112 92 16 4
NIKE 102 18 76 8
ASICS 67 3 56 8
MIZUNO 47 7 24 16
NEWBALANCE 56 8 8 40
", comment.char = "", check.names = FALSE)
test_table[,-1] = lapply(test_table[,-1], function(x) c(x[1], x[-1]/x[1]*100))
test_table = as.etable(test_table)
expss_digits(2)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table), res)
expect_identical(significance_cell_chisq(test_table, row_margin = "auto"), res)
expect_identical(significance_cell_chisq(test_table, row_margin = "sum_row"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 +", "14.06 -",
" 2.34 -", " 5.47 -", " 6.25 -"), `Segment|AMT` = c("180 ",
" 8.89 -", "42.22 +", "31.11 +", "13.33 ", " 4.44 -"), `Segment|DES` = c("76 ",
" 5.26 -", "10.53 -", "10.53 ", "21.05 +", "52.63 +")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, sig_labels_chisq = c("-", "+")), res)
expect_identical(significance_cell_chisq(test_table, sig_labels_chisq = c("-", "+"), subtable_marks = "both"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 ",
" 2.34 ", " 5.47 ", " 6.25 "), `Segment|AMT` = c("180 ",
" 8.89 ", "42.22 >", "31.11 >", "13.33 ", " 4.44 "), `Segment|DES` = c("76 ",
" 5.26 ", "10.53 ", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, subtable_marks = "greater"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 ", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 ", "31.11 ", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 ", "52.63 ")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, subtable_marks = "less"), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76",
" 5.26", "10.53", "10.53", "21.05", "52.63")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, min_base = 100), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128", "71.88", "14.06",
" 2.34", " 5.47", " 6.25"), `Segment|AMT` = c("180 ", " 8.89 <",
"42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76",
" 5.26", "10.53", "10.53", "21.05", "52.63")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, min_base = 150), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128", "71.88", "14.06",
" 2.34", " 5.47", " 6.25"), `Segment|AMT` = c("180", " 8.89",
"42.22", "31.11", "13.33", " 4.44"), `Segment|DES` = c("76",
" 5.26", "10.53", "10.53", "21.05", "52.63")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, min_base = 400), res)
test_table = text_to_columns("
row_labels Total PRO AMT DES
#Total 384 128 180 76
ADIDAS 112 92 16 4
NIKE 102 18 76 8
ASICS 67 3 56 8
MIZUNO 47 7 24 16
NEWBALANCE 56 8 8 40
", comment.char = "", check.names = FALSE) %>% as.etable()
test_table[,-1] = lapply(test_table[,-1], function(x) c(x[1], x[-1]/x[1]*100))
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
colnames(res) = gsub(".+\\|", "", colnames(res), perl = TRUE)
expect_identical(significance_cell_chisq(test_table, row_margin = "first_column"), res)
expect_identical(significance_cell_chisq(test_table, total_column_marker = "Total"), res)
colnames(res)[2] = "#Total"
colnames(test_table)[2] = "#Total"
expect_identical(significance_cell_chisq(test_table, row_margin = "auto"), res)
res = structure(list(row_labels = c("ADIDAS", "NIKE", "ASICS", "MIZUNO",
"NEWBALANCE"), `#Total` = c("", "", "", "", ""), PRO = c(">",
"<", "<", "<", "<"), AMT = c("<", ">", ">", "", "<"), DES = c("<",
"<", "", ">", ">")), row.names = 2:6, class = c("etable", "data.frame"
))
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "none"), res)
res = structure(list(row_labels = c("ADIDAS", "NIKE", "ASICS", "MIZUNO",
"NEWBALANCE"), `#Total` = c("29.17", "26.56", "17.45", "12.24",
"14.58"), PRO = c("71.88 >", "14.06 <", " 2.34 <", " 5.47 <",
" 6.25 <"), AMT = c(" 8.89 <", "42.22 >", "31.11 >", "13.33 ",
" 4.44 <"), DES = c(" 5.26 <", "10.53 <", "10.53 ", "21.05 >",
"52.63 >")), row.names = 2:6, class = c("etable", "data.frame"
))
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "percent"), res)
expss_digits()
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "percent", digits = 2), res)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), `#Total` = c("384", "", "", "", "",
""), PRO = c("128", ">", "<", "<", "<", "<"), AMT = c("180",
"<", ">", ">", "", "<"), DES = c("76", "<", "<", "", ">", ">"
)), row.names = c(NA, -6L), class = c("etable", "data.frame"))
expect_identical(significance_cell_chisq(test_table, row_margin = "auto", keep = "bases"), res)
expect_identical(significance_cell_chisq(test_table[,1]), test_table[,1])
context("cell_chisq correct")
test_table = text_to_columns("
row_labels Total Segment|PRO Segment|AMT Segment|DES
#Total 384 128 180 76
ADIDAS 112 92 16 4
NIKE 102 18 76 8
ASICS 67 3 56 8
MIZUNO 47 7 24 16
NEWBALANCE 56 8 8 40
", comment.char = "", check.names = FALSE)
test_table[,-1] = lapply(test_table[,-1], function(x) c(x[1], x[-1]/x[1]*100))
test_table = as.etable(test_table)
expss_digits(2)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 ", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(
significance_cell_chisq(test_table, sig_level = 0.01, correct = TRUE),
res
)
res = structure(list(row_labels = c("#Total", "ADIDAS", "NIKE", "ASICS",
"MIZUNO", "NEWBALANCE"), Total = c("384", "29.17", "26.56", "17.45",
"12.24", "14.58"), `Segment|PRO` = c("128 ", "71.88 >", "14.06 <",
" 2.34 <", " 5.47 <", " 6.25 <"), `Segment|AMT` = c("180 ",
" 8.89 <", "42.22 >", "31.11 >", "13.33 ", " 4.44 <"), `Segment|DES` = c("76 ",
" 5.26 <", "10.53 <", "10.53 ", "21.05 >", "52.63 >")), row.names = c(NA,
-6L), class = c("etable", "data.frame"))
expect_identical(
significance_cell_chisq(test_table, sig_level = 0.01, correct = FALSE),
res
)
data(mtcars)
mtcars = apply_labels(mtcars,
mpg = "Miles/(US) gallon",
cyl = "Number of cylinders",
disp = "Displacement (cu.in.)",
hp = "Gross horsepower",
drat = "Rear axle ratio",
wt = "Weight (lb/1000)",
qsec = "1/4 mile time",
vs = "Engine",
vs = c("V-engine" = 0,
"Straight engine" = 1),
am = "Transmission",
am = c("Automatic" = 0,
"Manual"=1),
gear = "Number of forward gears",
carb = "Number of carburetors"
)
mtcars2 = add_rows(mtcars, mtcars, mtcars)
# table with multiple variables
tbl = cross_cpct(mtcars2, list(gear, cyl), list(total(), am, vs))
res = structure(list(row_labels = c("Number of forward gears|3", "Number of forward gears|4",
"Number of forward gears|5", "Number of forward gears|#Total cases",
"Number of cylinders|4", "Number of cylinders|6", "Number of cylinders|8",
"Number of cylinders|#Total cases"), `#Total` = c("46.88", "37.50",
"15.62", "96", "34.38", "21.88", "43.75", "96"), `Transmission|Automatic` = c("78.95 >",
"21.05 ", "<", "57 ", "15.79 <", "21.05 ", "63.16 >", "57 "
), `Transmission|Manual` = c("<", "61.54 ", "38.46 >", "39 ",
"61.54 >", "23.08 ", "15.38 <", "39 "), `Engine|V-engine` = c("66.67 >",
"11.11 <", "22.22 ", "54 ", " 5.56 <", "16.67 ", "77.78 >",
"54 "), `Engine|Straight engine` = c("21.43 <", "71.43 >", " 7.14 ",
"42 ", "71.43 >", "28.57 ", "<", "42 ")), row.names = c(NA,
-8L), class = c("etable", "data.frame"))
expect_equal(significance_cell_chisq(tbl, sig_level = .0001) , res)
expect_equal(mtcars2 %>%
tab_cells(gear, cyl) %>%
tab_cols(total(), am, vs) %>%
tab_stat_cpct() %>%
tab_last_sig_cell_chisq(sig_level = .0001) %>%
tab_pivot()
, res)
expect_equal(mtcars2 %>%
tab_significance_options(sig_level = .0001, subtable_marks = "greater", sig_labels_chisq = c("-", "+")) %>%
tab_cells(gear, cyl) %>%
tab_cols(total(), am, vs) %>%
tab_stat_cpct() %>%
tab_last_sig_cell_chisq() %>%
tab_pivot()
, significance_cell_chisq(tbl, sig_level = .0001, subtable_marks = "greater", sig_labels_chisq = c("-", "+")))
expect_equal(mtcars2 %>%
tab_significance_options(sig_level = .0001,
subtable_marks = "greater",
sig_labels_chisq = c("-", "+"),
row_margin = "sum_row"
) %>%
tab_cells(gear, cyl) %>%
tab_cols(total(), am, vs) %>%
tab_stat_cpct() %>%
tab_last_sig_cell_chisq() %>%
tab_pivot()
, significance_cell_chisq(tbl, sig_level = .0001,
subtable_marks = "greater",
sig_labels_chisq = c("-", "+"),
row_margin = "first_column"
))
expss_digits()
}
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