In this document, we compare various DescrTab2 tests and descriptive statistics with their SAS equivalents.
These comparisons are not automated. The user may check if the results presented within this document are according to the users preferences.
The datasets used in these comparisons are taken mostly from the
?help pages of the underlying test functions used within
DescrTab2. For the SAS comparisons, these datasets are then
written to .csv format and read into SAS with help of the
?foreign package.
The origin of these datasets is described in the respective sections.
This document is created by including in the .html SAS output. Unfortunately, this has ugly side effects for the formatting of this document, but everything should still be readable.
Dataset origin: ?wilcox.test (accessed on R-version
4.0.3).
x <- c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 3.06, 1.30)
y <- c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)
dat_wilcox.test_1_sample <- tibble::tibble(diff = x-y)
descr(dat_wilcox.test_1_sample, test_options = c(nonparametric=TRUE))| (N=9) | ||
|---|---|---|
| diff | ||
| N | 9 | 0.039Wil1 |
| mean | 0.432 | |
| sd | 0.427 | |
| median | 0.49 | |
| Q1 - Q3 | 0.01 – 0.62 | |
| min - max | -0.147 – 1.02 | |
| Wil1 Wilcoxon’s one-sample signed-rank test | ||
Dataset origin: ?wilcox.test (accessed on R-version
4.0.3).
x <- c(0.80, 0.83, 1.89, 1.04, 1.45, 1.38, 1.91, 1.64, 0.73, 1.46)
y <- c(1.15, 0.88, 0.90, 0.74, 1.21)
group <- c(rep("Trt", length(x)), rep("Ctrl", length(y)))
dat_wilcox.test_2_sample <- tibble::tibble(var=c(x,y), group=group)
descr(dat_wilcox.test_2_sample, "group", test_options = c(nonparametric=TRUE))| (N=10) | (N=5) | (N=15) | ||
|---|---|---|---|---|
| var | ||||
| N | 10 | 5 | 15 | 0.254MWU |
| mean | 1.31 | 0.976 | 1.2 | |
| sd | 0.441 | 0.197 | 0.404 | |
| median | 1.42 | 0.9 | 1.15 | |
| Q1 - Q3 | 0.83 – 1.64 | 0.88 – 1.15 | 0.83 – 1.46 | |
| min - max | 0.73 – 1.91 | 0.74 – 1.21 | 0.73 – 1.91 | |
| MWU Mann-Whitney’s U test | ||||
Dataset origin: ?kruskal.test (accessed on R-version
4.0.3).
x <- c(2.9, 3.0, 2.5, 2.6, 3.2) # normal subjects
y <- c(3.8, 2.7, 4.0, 2.4) # with obstructive airway disease
z <- c(2.8, 3.4, 3.7, 2.2, 2.0) # with asbestosis
group <- c(rep("Trt", length(x)), rep("Ctrl", length(y)), rep("Placebo", length(z)))
dat_kruskal.test <- tibble::tibble(var=c(x,y,z), group=group)
descr(dat_kruskal.test, "group", test_options = c(nonparametric=TRUE)) | (N=5) | (N=4) | (N=5) | (N=14) | ||
|---|---|---|---|---|---|
| var | |||||
| N | 5 | 4 | 5 | 14 | 0.680KW |
| mean | 2.84 | 3.23 | 2.82 | 2.94 | |
| sd | 0.288 | 0.793 | 0.736 | 0.61 | |
| median | 2.9 | 3.25 | 2.8 | 2.85 | |
| Q1 - Q3 | 2.6 – 3 | 2.55 – 3.9 | 2.2 – 3.4 | 2.5 – 3.4 | |
| min - max | 2.5 – 3.2 | 2.4 – 4 | 2 – 3.7 | 2 – 4 | |
| KW Kruskal-Wallis’s one-way ANOVA | |||||
#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/kruskal.test/kruskal.test_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.Dataset origin: ?friedman.test (accessed on R-version
4.0.3).
RoundingTimes <-
matrix(c(5.40, 5.50, 5.55,
5.85, 5.70, 5.75,
5.20, 5.60, 5.50,
5.55, 5.50, 5.40,
5.90, 5.85, 5.70,
5.45, 5.55, 5.60,
5.40, 5.40, 5.35,
5.45, 5.50, 5.35,
5.25, 5.15, 5.00,
5.85, 5.80, 5.70,
5.25, 5.20, 5.10,
5.65, 5.55, 5.45,
5.60, 5.35, 5.45,
5.05, 5.00, 4.95,
5.50, 5.50, 5.40,
5.45, 5.55, 5.50,
5.55, 5.55, 5.35,
5.45, 5.50, 5.55,
5.50, 5.45, 5.25,
5.65, 5.60, 5.40,
5.70, 5.65, 5.55,
6.30, 6.30, 6.25),
nrow = 22,
byrow = TRUE,
dimnames = list(1 : 22,
c("Round Out", "Narrow Angle", "Wide Angle")))
idx <- rep(1:22, 3)
dat <- tibble::tibble(var = c(RoundingTimes[,1], RoundingTimes[,2], RoundingTimes[,3]),
group = c(rep("Round Out", 22), rep("Narrow Angle", 22), rep("Wide Angle", 22)))
descr(dat, "group", test_options = list(nonparametric=TRUE, indices=idx, paired=TRUE))
#> You specified paired tests and did not explicitly
#> specify format_options$print_Total. print_Total is set to FALSE.| (N=22) | (N=22) | (N=22) | ||
|---|---|---|---|---|
| var | ||||
| N | 22 | 22 | 22 | 0.004Frie |
| mean | 5.54 | 5.53 | 5.46 | |
| sd | 0.272 | 0.26 | 0.273 | |
| median | 5.5 | 5.53 | 5.45 | |
| Q1 - Q3 | 5.4 – 5.65 | 5.45 – 5.6 | 5.35 – 5.55 | |
| min - max | 5.05 – 6.3 | 5 – 6.3 | 4.95 – 6.25 | |
| Frie Friedman test | ||||
#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/friedman.test/friedman.test_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.| The SAS System |
| Summary Statistics for group by var Controlling for indices |
| Cochran-Mantel-Haenszel Statistics (Based on Rank Scores) | ||||
|---|---|---|---|---|
| Statistic | Alternative Hypothesis | DF | Value | Prob |
| 1 | Nonzero Correlation | 1 | 5.3571 | 0.0206 |
| 2 | Row Mean Scores Differ | 2 | 11.1429 | 0.0038 |
| Total Sample Size = 66 |
Dataset origin: This is a replicate of the dataset from the SAS documentation of the Cochrane Q test from proc freq.
d.frm <- DescTools::Untable(xtabs(c(6,2,2,6,16,4,4,6) ~ .,
expand.grid(rep(list(c("F","U")), times=3))),
colnames = LETTERS[1:3])
# rearrange to long shape
d.long <- reshape(d.frm, varying=1:3, times=names(d.frm)[c(1:3)],
v.names="resp", direction="long")
idx <- d.long$id
dat <- d.long[, 1:2] |> dplyr::mutate(time=as.character(time), resp=as.character(resp))
descr(dat, "time", test_options = list(indices=idx, paired=TRUE))
#> You specified paired tests and did not explicitly
#> specify format_options$print_Total. print_Total is set to FALSE.| (N=46) | (N=46) | (N=46) | ||
|---|---|---|---|---|
| resp | ||||
| F | 28 (60.9%) | 28 (60.9%) | 16 (34.8%) | 0.014CocQ |
| U | 18 (39.1%) | 18 (39.1%) | 30 (65.2%) | |
| CocQ Cochran’s Q test | ||||
#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/CochraneQTest/CochraneQTest_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.Dataset origin: ?mcnemar.test (accessed on R-version
4.0.3). Note that this dataset is not explicitly defined in
?mcnemar.test. It is constructed to reflect the cross table
defined there.
dat <- tibble::tibble(var = c(rep("Approve", 794), rep("Approve", 150), rep("Disapprove", 86), rep("Disapprove", 570),
rep("Approve", 794), rep("Disapprove", 150), rep("Approve", 86), rep("Disapprove", 570)),
group= c(rep("first", 1600), rep("second",1600)))
descr(dat, "group", test_options = list(paired=TRUE, indices=c(1:1600, 1:1600)))
#> You specified paired tests and did not explicitly
#> specify format_options$print_Total. print_Total is set to FALSE.
#> Warning in sig_test(var, group, test_options, test_override, var_name): Confidence intervals for differences in proportions ignore the paired structure of the data.
#> Use Exact McNemar's test if you want confidence intervals which use the test statistic of the
#> exact McNemar's test.| (N=1600) | (N=1600) | ||
|---|---|---|---|
| var | |||
| Approve | 944 (59.0%) | 880 (55.0%) | <0.001McN |
| Disapprove | 656 (41.0%) | 720 (45.0%) | |
| McN McNemar’s test | |||
descr(dat, "group", test_options = list(paired=TRUE, exact=TRUE, indices=c(1:1600, 1:1600)))
#> You specified paired tests and did not explicitly
#> specify format_options$print_Total. print_Total is set to FALSE.| (N=1600) | (N=1600) | ||
|---|---|---|---|
| var | |||
| Approve | 944 (59.0%) | 880 (55.0%) | <0.001eMcN |
| Disapprove | 656 (41.0%) | 720 (45.0%) | |
| eMcN Exact McNemar’s test | |||
dat <-
tibble::tibble(x = c(
rep("Approve", 794),
rep("Approve", 150),
rep("Disapprove", 86),
rep("Disapprove", 570)
),
y = c(
rep("Approve", 794),
rep("Disapprove", 150),
rep("Approve", 86),
rep("Disapprove", 570)
))mcnemar.test(dat$x, dat$y, correct = FALSE)
#>
#> McNemar's Chi-squared test
#>
#> data: dat$x and dat$y
#> McNemar's chi-squared = 17.356, df = 1, p-value = 3.099e-05#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/mcnemar.test/mcnemar.test_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.| The SAS System |
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Statistics for Table of x by y |
| McNemar's Test | |||
|---|---|---|---|
| Chi-Square | DF | Pr > ChiSq | Exact Pr >= ChiSq |
| 17.3559 | 1 | <.0001 | .000037159 |
| Simple Kappa Coefficient | |||
|---|---|---|---|
| Estimate | Standard Error |
95% Confidence Limits | |
| 0.6996 | 0.0180 | 0.6644 | 0.7348 |
| Sample Size = 1600 |
Dataset origin: “Gender-Party dataset”:?chisq.test
(accessed on R-version 4.0.3). “a-b dataset”: selfmade.
dat <- tibble::tibble(gender=c(rep("F",sum(c(762, 327, 468)) ), rep("M", sum( c(484, 239, 477)))),
party=c(rep("Democrat", 762), rep("Independent", 327), rep("Republican", 468),
rep("Democrat", 484), rep("Independent", 239), rep("Republican", 477)))
descr(dat, "gender")| (N=1557) | (N=1200) | (N=2757) | ||
|---|---|---|---|---|
| party | ||||
| Democrat | 762 (48.9%) | 484 (40.3%) | 1246 (45.2%) | <0.001chi2 |
| Independent | 327 (21.0%) | 239 (19.9%) | 566 (20.5%) | |
| Republican | 468 (30.1%) | 477 (39.8%) | 945 (34.3%) | |
| chi2 Pearson’s chi-squared test | ||||
| (N=2757) | ||
|---|---|---|
| gender | ||
| F | 1557 (56.5%) | <0.001chi1 |
| M | 1200 (43.5%) | |
| party | ||
| Democrat | 1246 (45.2%) | <0.001chi1 |
| Independent | 566 (20.5%) | |
| Republican | 945 (34.3%) | |
| chi1 Chi-squared goodness-of-fit test | ||
chisq.test(dat$gender, dat$party)
#>
#> Pearson's Chi-squared test
#>
#> data: dat$gender and dat$party
#> X-squared = 30.07, df = 2, p-value = 2.954e-07
chisq.test(table(dat$gender))
#>
#> Chi-squared test for given probabilities
#>
#> data: table(dat$gender)
#> X-squared = 46.227, df = 1, p-value = 1.053e-11
chisq.test(table(dat$party))
#>
#> Chi-squared test for given probabilities
#>
#> data: table(dat$party)
#> X-squared = 252.68, df = 2, p-value < 2.2e-16dat <- tibble::tibble(
a = factor(c(0,
0,
1,
1,
0,
0,
0,
0,
0,
0,
1)),
b = factor(c(1,
1,
1,
1,
1,
1,
1,
0,
0,
1,
0))
)
descr(dat, "b")
#> Warning in (function (x, y = NULL, correct = TRUE, p = rep(1/length(x), :
#> Chi-squared approximation may be incorrect
#> Warning in stats::prop.test(table(group, var), correct = FALSE): Chi-squared
#> approximation may be incorrect| (N=3) | (N=8) | (N=11) | ||
|---|---|---|---|---|
| a | ||||
| 0 | 2 (66.7%) | 6 (75.0%) | 8 (72.7%) | 0.782chi2 |
| 1 | 1 (33.3%) | 2 (25.0%) | 3 (27.3%) | |
| chi2 Pearson’s chi-squared test | ||||
#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/chisq.test/chisq.test_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.| The SAS System |
| gender | Frequency | Percent | Cumulative Frequency |
Cumulative Percent |
|---|---|---|---|---|
| F | 1557 | 56.47 | 1557 | 56.47 |
| M | 1200 | 43.53 | 2757 | 100.00 |
| Chi-Square Test for Equal Proportions |
|
|---|---|
| Chi-Square | 46.2274 |
| DF | 1 |
| Pr > ChiSq | <.0001 |
| Sample Size = 2757 |
| party | Frequency | Percent | Cumulative Frequency |
Cumulative Percent |
|---|---|---|---|---|
| Democrat | 1246 | 45.19 | 1246 | 45.19 |
| Independent | 566 | 20.53 | 1812 | 65.72 |
| Republican | 945 | 34.28 | 2757 | 100.00 |
| Chi-Square Test for Equal Proportions |
|
|---|---|
| Chi-Square | 252.6812 |
| DF | 2 |
| Pr > ChiSq | <.0001 |
| Sample Size = 2757 |
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Statistics for Table of gender by party |
| Statistic | DF | Value | Prob |
|---|---|---|---|
| Chi-Square | 2 | 30.0701 | <.0001 |
| Likelihood Ratio Chi-Square | 2 | 30.0167 | <.0001 |
| Mantel-Haenszel Chi-Square | 1 | 28.9797 | <.0001 |
| Phi Coefficient | 0.1044 | ||
| Contingency Coefficient | 0.1039 | ||
| Cramer's V | 0.1044 |
| Sample Size = 2757 |
| The SAS System |
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Statistics for Table of a by b |
| Statistic | DF | Value | Prob |
|---|---|---|---|
| Chi-Square | 1 | 0.0764 | 0.7823 |
| Likelihood Ratio Chi-Square | 1 | 0.0745 | 0.7849 |
| Continuity Adj. Chi-Square | 1 | 0.0000 | 1.0000 |
| Mantel-Haenszel Chi-Square | 1 | 0.0694 | 0.7921 |
| Phi Coefficient | -0.0833 | ||
| Contingency Coefficient | 0.0830 | ||
| Cramer's V | -0.0833 | ||
| WARNING: 75% of the cells have expected counts less than 5. Chi-Square may not be a valid test. |
|||
| Fisher's Exact Test | |
|---|---|
| Cell (1,1) Frequency (F) | 2 |
| Left-sided Pr <= F | 0.6606 |
| Right-sided Pr >= F | 0.8485 |
| Table Probability (P) | 0.5091 |
| Two-sided Pr <= P | 1.0000 |
| Sample Size = 11 |
Dataset origin: ?t.test, which references
?sleep (accessed on R-version 4.0.3).
| (N=20) | ||
|---|---|---|
| value | ||
| N | 20 | 0.003tt1 |
| mean | 1.54 | |
| sd | 2.02 | |
| median | 0.95 | |
| Q1 - Q3 | -0.05 – 3.4 | |
| min - max | -1.6 – 5.5 | |
| tt1 Student’s one-sample t-test | ||
| (N=10) | (N=10) | (N=20) | ||
|---|---|---|---|---|
| extra | ||||
| N | 10 | 10 | 20 | 0.079tt2 |
| mean | 0.75 | 2.33 | 1.54 | |
| sd | 1.79 | 2 | 2.02 | |
| median | 0.35 | 1.75 | 0.95 | |
| Q1 - Q3 | -0.2 – 2 | 0.8 – 4.4 | -0.05 – 3.4 | |
| min - max | -1.6 – 3.7 | -0.1 – 5.5 | -1.6 – 5.5 | |
| tt2 Welch’s two-sample t-test | ||||
descr(dat, "group", test_options = list(paired=TRUE, indices=rep(1:10, 2)))
#> You specified paired tests and did not explicitly
#> specify format_options$print_Total. print_Total is set to FALSE.| (N=10) | (N=10) | ||
|---|---|---|---|
| extra | |||
| N | 10 | 10 | 0.003tpar |
| mean | 0.75 | 2.33 | |
| sd | 1.79 | 2 | |
| median | 0.35 | 1.75 | |
| Q1 - Q3 | -0.2 – 2 | 0.8 – 4.4 | |
| min - max | -1.6 – 3.7 | -0.1 – 5.5 | |
| tpar Student’s paired t-test | |||
#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/t.test/t.test_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.| The SAS System |
| Moments | |||
|---|---|---|---|
| N | 20 | Sum Weights | 20 |
| Mean | 1.54 | Sum Observations | 30.8 |
| Std Deviation | 2.01791972 | Variance | 4.072 |
| Skewness | 0.45185739 | Kurtosis | -0.7747436 |
| Uncorrected SS | 124.8 | Corrected SS | 77.368 |
| Coeff Variation | 131.033748 | Std Error Mean | 0.45122057 |
| Basic Statistical Measures | |||
|---|---|---|---|
| Location | Variability | ||
| Mean | 1.54000 | Std Deviation | 2.01792 |
| Median | 0.95000 | Variance | 4.07200 |
| Mode | -0.10000 | Range | 7.10000 |
| Interquartile Range | 3.45000 | ||
| Note: The mode displayed is the smallest of 3 modes with a count of 2. |
| Tests for Location: Mu0=0 | ||||
|---|---|---|---|---|
| Test | Statistic | p Value | ||
| Student's t | t | 3.412965 | Pr > |t| | 0.0029 |
| Sign | M | 4.5 | Pr >= |M| | 0.0636 |
| Signed Rank | S | 67.5 | Pr >= |S| | 0.0048 |
| Quantiles (Definition 5) | |
|---|---|
| Level | Quantile |
| 100% Max | 5.50 |
| 99% | 5.50 |
| 95% | 5.05 |
| 90% | 4.50 |
| 75% Q3 | 3.40 |
| 50% Median | 0.95 |
| 25% Q1 | -0.05 |
| 10% | -0.70 |
| 5% | -1.40 |
| 1% | -1.60 |
| 0% Min | -1.60 |
| Extreme Observations | |||
|---|---|---|---|
| Lowest | Highest | ||
| Value | Obs | Value | Obs |
| -1.6 | 2 | 3.4 | 20 |
| -1.2 | 4 | 3.7 | 7 |
| -0.2 | 3 | 4.4 | 16 |
| -0.1 | 15 | 4.6 | 19 |
| -0.1 | 5 | 5.5 | 17 |
| The SAS System |
| group | Method | N | Mean | Std Dev | Std Err | Minimum | Maximum |
|---|---|---|---|---|---|---|---|
| 1 | 10 | 0.7500 | 1.7890 | 0.5657 | -1.6000 | 3.7000 | |
| 2 | 10 | 2.3300 | 2.0022 | 0.6332 | -0.1000 | 5.5000 | |
| Diff (1-2) | Pooled | -1.5800 | 1.8986 | 0.8491 | |||
| Diff (1-2) | Satterthwaite | -1.5800 | 0.8491 |
| group | Method | Mean | 95% CL Mean | Std Dev | 95% CL Std Dev | ||
|---|---|---|---|---|---|---|---|
| 1 | 0.7500 | -0.5298 | 2.0298 | 1.7890 | 1.2305 | 3.2660 | |
| 2 | 2.3300 | 0.8977 | 3.7623 | 2.0022 | 1.3772 | 3.6553 | |
| Diff (1-2) | Pooled | -1.5800 | -3.3639 | 0.2039 | 1.8986 | 1.4346 | 2.8077 |
| Diff (1-2) | Satterthwaite | -1.5800 | -3.3655 | 0.2055 | |||
| Method | Variances | DF | t Value | Pr > |t| |
|---|---|---|---|---|
| Pooled | Equal | 18 | -1.86 | 0.0792 |
| Satterthwaite | Unequal | 17.776 | -1.86 | 0.0794 |
| Equality of Variances | ||||
|---|---|---|---|---|
| Method | Num DF | Den DF | F Value | Pr > F |
| Folded F | 9 | 9 | 1.25 | 0.7427 |
Dataset origin: Modified version of ?datasets::npk.
npk is used in ?aov (accessed on R-version
4.0.3).
dat <- data.frame(
y = npk$yield,
P = ordered(gl(3, 24)),
N = ordered(gl(3, 1, 24))
)
descr(dat[, c("y", "P")], "P") | (N=24) | (N=24) | (N=24) | (N=72) | ||
|---|---|---|---|---|---|
| y | |||||
| N | 24 | 24 | 24 | 72 | >0.999F |
| mean | 54.9 | 54.9 | 54.9 | 54.9 | |
| sd | 6.17 | 6.17 | 6.17 | 6.09 | |
| median | 55.6 | 55.6 | 55.6 | 55.6 | |
| Q1 - Q3 | 49.6 – 58.8 | 49.6 – 58.8 | 49.6 – 58.8 | 49.6 – 58.8 | |
| min - max | 44.2 – 69.5 | 44.2 – 69.5 | 44.2 – 69.5 | 44.2 – 69.5 | |
| F F-test (ANOVA) | |||||
| (N=24) | (N=24) | (N=24) | (N=72) | ||
|---|---|---|---|---|---|
| y | |||||
| N | 24 | 24 | 24 | 72 | 0.346F |
| mean | 54.1 | 56.4 | 54.2 | 54.9 | |
| sd | 5.56 | 6.94 | 5.63 | 6.09 | |
| median | 55.6 | 54.6 | 55.5 | 55.6 | |
| Q1 - Q3 | 49.6 – 58 | 50.4 – 61.3 | 49.1 – 57.9 | 49.6 – 58.8 | |
| min - max | 44.2 – 62 | 48.8 – 69.5 | 45.5 – 62.8 | 44.2 – 69.5 | |
| F F-test (ANOVA) | |||||
#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/aov/aov_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.| The SAS System |
| Class Level Information | ||
|---|---|---|
| Class | Levels | Values |
| P | 3 | 1 2 3 |
| Number of Observations Read | 72 |
|---|---|
| Number of Observations Used | 72 |
| The SAS System |
| Source | DF | Sum of Squares | Mean Square | F Value | Pr > F |
|---|---|---|---|---|---|
| Model | 2 | 0.000000 | 0.000000 | 0.00 | 1.0000 |
| Error | 69 | 2629.095000 | 38.102826 | ||
| Corrected Total | 71 | 2629.095000 |
| R-Square | Coeff Var | Root MSE | y Mean |
|---|---|---|---|
| 0.000000 | 11.24874 | 6.172749 | 54.87500 |
| Source | DF | Anova SS | Mean Square | F Value | Pr > F |
|---|---|---|---|---|---|
| P | 2 | 0 | 0 | 0.00 | 1.0000 |
| The SAS System |
| Class Level Information | ||
|---|---|---|
| Class | Levels | Values |
| N | 3 | 1 2 3 |
| Number of Observations Read | 72 |
|---|---|
| Number of Observations Used | 72 |
| The SAS System |
| Source | DF | Sum of Squares | Mean Square | F Value | Pr > F |
|---|---|---|---|---|---|
| Model | 2 | 79.702500 | 39.851250 | 1.08 | 0.3457 |
| Error | 69 | 2549.392500 | 36.947717 | ||
| Corrected Total | 71 | 2629.095000 |
| R-Square | Coeff Var | Root MSE | y Mean |
|---|---|---|---|
| 0.030316 | 11.07693 | 6.078463 | 54.87500 |
| Source | DF | Anova SS | Mean Square | F Value | Pr > F |
|---|---|---|---|---|---|
| N | 2 | 79.70250000 | 39.85125000 | 1.08 | 0.3457 |
Dataset origin: Modified version of ?nlme::Orthodont.
Orthodont is used in ?lme (accessed on
R-version 4.0.3).
dat <- nlme::Orthodont
dat2 <- nlme::Orthodont[1:64,]
dat2$Sex <- "Divers"
dat2$distance <- dat2$distance + c(rep(0.1*c(1,4,3,2), 10), 0.1*rep(c(0.4,2,1.5, 2.3), 6) )
dat2$Subject <- stringr::str_replace_all(dat2$Subject, "M", "D")
dat <- dplyr::bind_rows(dat, dat2)
dat <- tibble::as_tibble(dat)
descr(dat[, c("Sex", "distance")], "Sex", test_options = list(paired=TRUE, indices=dat$Subject))
#> You specified paired tests and did not explicitly
#> specify format_options$print_Total. print_Total is set to FALSE.| (N=64) | (N=44) | (N=64) | ||
|---|---|---|---|---|
| distance | ||||
| N | 64 | 44 | 64 | 0.003MiAn |
| mean | 25 | 22.6 | 25.2 | |
| sd | 2.9 | 2.4 | 2.93 | |
| median | 24.8 | 22.8 | 25 | |
| Q1 - Q3 | 23 – 26.5 | 21 – 24.2 | 23.1 – 26.8 | |
| min - max | 17 – 31.5 | 16.5 – 28 | 17 – 31.7 | |
| MiAn Mixed model ANOVA | ||||
#> Warning: `includeHTML()` was provided a `path` that appears to be a complete HTML document.
#> ✖ Path: /tmp/Rtmp1CcSPj/Rbuild179c7a099f1a/DescrTab2/vignettes/validation_report/mixed/mixed_example_1.html
#> ℹ Use `tags$iframe()` to include an HTML document. You can either ensure `path` is accessible in your app or document (see e.g. `shiny::addResourcePath()`) and pass the relative path to the `src` argument. Or you can read the contents of `path` and pass the contents to `srcdoc`.| The SAS System |
| Model Information | |
|---|---|
| Data Set | WORK.RDATA |
| Dependent Variable | distance |
| Covariance Structure | Variance Components |
| Subject Effect | Subject |
| Estimation Method | REML |
| Residual Variance Method | Profile |
| Fixed Effects SE Method | Model-Based |
| Degrees of Freedom Method | Satterthwaite |
| Class Level Information | ||
|---|---|---|
| Class | Levels | Values |
| Sex | 3 | Divers Female Male |
| Subject | 43 | D01 D02 D03 D04 D05 D06 D07 D08 D09 D10 D11 D12 D13 D14 D15 D16 F01 F02 F03 F04 F05 F06 F07 F08 F09 F10 F11 M01 M02 M03 M04 M05 M06 M07 M08 M09 M10 M11 M12 M13 M14 M15 M16 |
| Dimensions | |
|---|---|
| Covariance Parameters | 2 |
| Columns in X | 4 |
| Columns in Z per Subject | 1 |
| Subjects | 43 |
| Max Obs per Subject | 4 |
| Number of Observations | |
|---|---|
| Number of Observations Read | 172 |
| Number of Observations Used | 172 |
| Number of Observations Not Used | 0 |
| Iteration History | |||
|---|---|---|---|
| Iteration | Evaluations | -2 Res Log Like | Criterion |
| 0 | 1 | 838.60158118 | |
| 1 | 1 | 823.17375628 | 0.00000000 |
| Convergence criteria met. |
| Covariance Parameter Estimates | ||
|---|---|---|
| Cov Parm | Subject | Estimate |
| Intercept | Subject | 2.2123 |
| Residual | 5.6941 | |
| Fit Statistics | |
|---|---|
| -2 Res Log Likelihood | 823.2 |
| AIC (Smaller is Better) | 827.2 |
| AICC (Smaller is Better) | 827.2 |
| BIC (Smaller is Better) | 830.7 |
| Type 3 Tests of Fixed Effects | ||||
|---|---|---|---|---|
| Effect | Num DF | Den DF | F Value | Pr > F |
| Sex | 2 | 40 | 6.69 | 0.0031 |
Dataset origin: selfmade.
DescrTab2 uses the exact2x2::boschloo with option
tsmethod=central to calculate p-values. There is no
comparison for this option readily available.
dat <- tibble::tibble(gender=factor(c("M", "M", "M", "M", "M", "M", "F", "F", "F", "F", "F")),
party=factor(c("A", "A", "B", "B", "B", "B", "A", "A", "A", "B", "B")))
descr(dat, "gender", test_options = c(exact=TRUE))| (N=5) | (N=6) | (N=11) | ||
|---|---|---|---|---|
| party | ||||
| A | 3 (60.0%) | 2 (33.3%) | 5 (45.5%) | 0.491Bolo |
| B | 2 (40.0%) | 4 (66.7%) | 6 (54.5%) | |
| Bolo Boschloo’s test | ||||
exact2x2::boschloo(3, 5, 2, 6, tsmethod="central")
#>
#> Boschloo's test
#>
#> data: x1/n1=(3/5) and x2/n2= (2/6)
#> proportion 1 = 0.6, proportion 2 = 0.33333, p-value = 0.4909
#> alternative hypothesis: true p2(1-p1)/[p1(1-p2)] is less than 1
#> percent confidence interval:
#> NA NA
#> sample estimates:
#> p2(1-p1)/[p1(1-p2)]
#> 0.3333333However, we can compare the exact2x2::boschloo with
tsmethod=minlike to Exact::exact.test:
exact2x2::boschloo(3, 5, 2, 6, tsmethod="minlike")
#>
#> Boschloo's test
#>
#> data: x1/n1=(3/5) and x2/n2= (2/6)
#> proportion 1 = 0.6, proportion 2 = 0.33333, p-value = 0.5488
#> alternative hypothesis: true p2(1-p1)/[p1(1-p2)] is not equal to 1
#> 95 percent confidence interval:
#> NA NA
#> sample estimates:
#> p2(1-p1)/[p1(1-p2)]
#> 0.3333333
Exact::exact.test(table(dat), method="boschloo", to.plot = FALSE)
#>
#> Boschloo's Exact Test
#>
#> data: 3 out of 5 vs. 2 out of 6
#> test statistic = 0.5671, first sample size = 5, second sample size = 6,
#> p-value = 0.5488
#> alternative hypothesis: true difference in proportion is not equal to 0
#> sample estimates:
#> difference in proportion
#> 0.2666667