R version 4.6.0 alpha (2026-03-28 r89737 ucrt) Copyright (C) 2026 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # This file is part of the standard setup for testthat. > # It is recommended that you do not modify it. > # > # Where should you do additional test configuration? > # Learn more about the roles of various files in: > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview > # * https://testthat.r-lib.org/articles/special-files.html > > library(testthat) > library(evanverse) > > test_check("evanverse") D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL\file47a47c9512be +-- a.R D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL\file47a47d8b700 ! P(1000, 999) exceeds double range and will return Inf. ! P(1000, 999) exceeds double range and will return Inf. i Downloading human gene annotation (Ensembl 110)... v Retrieved 5 annotated genes. v Saved to 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL\file47a440c2450b.rds' i Downloading human gene annotation (Ensembl 110)... v Retrieved 5 annotated genes. v Saved to 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL\file47a4165ae9.rds' i Downloading human gene annotation (Ensembl 110)... v Retrieved 5 annotated genes. Setting options('download.file.method.GEOquery'='auto') Setting options('GEOquery.inmemory.gpl'=FALSE) v Palette saved: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/cp_test_18340/sequential/my_blues.json' v Palette saved: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/cp_json_18340/qualitative/qual_trio.json' v Palette saved: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/cp_ow_18340/sequential/blues.json' v Palette saved: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/cp_owt_18340/sequential/blues.json' i Overwriting existing palette: "blues" v Palette saved: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/cp_owt_18340/sequential/blues.json' v Palette saved: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/rm_test_18340/sequential/to_remove.json' v Removed "to_remove" from sequential v Palette saved: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/rm_auto_18340/diverging/find_me.json' v Removed "find_me" from diverging v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 ! Failed to parse JSON: 'D:\temp\2026_03_29_17_50_16_6441\Rtmp25eyFL/pal_test_18340/sequential/broken.json' v Compiled 3 palettes: Sequential=1, Diverging=1, Qualitative=1 v CRAN mirror set to: v CRAN mirror set to: v CRAN mirror set to: v Bioconductor mirror set to: v Bioconductor mirror set to: v CRAN mirror set to: v Bioconductor mirror set to: v CRAN mirror set to: v Bioconductor mirror set to: v CRAN mirror set to: v Bioconductor mirror set to: v CRAN mirror set to: v Bioconductor mirror set to: v CRAN mirror set to: v Installed: stats v Installed: stats v Installed: stats v Installed: utils v Installed: cli x Power: 47.8% (very low) | Two-sample t-test n = 30 per group, effect size = 0.500, alpha = 0.050 With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. x Power: 47.8% (very low) | Two-sample t-test n = 30 per group, effect size = 0.500, alpha = 0.050 With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. -- Statistical Power Analysis -------------------------------------------------- -- Parameters -- Test: Two-sample t-test n: 30 per group Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- x Power (1−β): 47.79% (very low) -- Interpretation -- With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. -- Recommendation -- i To reach 80% power, increase n from 30 to 64 per group. -- Statistical Power Analysis -------------------------------------------------- -- Parameters -- Test: Two-sample t-test n: 30 per group Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- x Power (1−β): 47.79% (very low) -- Interpretation -- With only 47.8% power, the study is unlikely to detect a true effect of size 0.50. -- Recommendation -- i To reach 80% power, increase n from 30 to 64 per group. v n = 64 per group (128 total) | Two-sample t-test Target power = 80%, effect size = 0.500, alpha = 0.050 To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). v n = 64 per group (128 total) | Two-sample t-test Target power = 80%, effect size = 0.500, alpha = 0.050 To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). -- Sample Size Estimation ------------------------------------------------------ -- Parameters -- Test: Two-sample t-test Target power: 80% (0.8000) Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- v n per group: 64 v n total: 128 -- Interpretation -- To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). -- Recommendation -- i Recruit 10–20% extra to account for dropout, missing data, or protocol violations. -- Sample Size Estimation ------------------------------------------------------ -- Parameters -- Test: Two-sample t-test Target power: 80% (0.8000) Effect size: 0.5000 alpha: 0.0500 Alternative: two.sided -- Result -- v n per group: 64 v n total: 128 -- Interpretation -- To detect an effect of size 0.50 with 80% power, recruit 64 subjects per group (128 total). -- Recommendation -- i Recruit 10–20% extra to account for dropout, missing data, or protocol violations. t.test | p < 0.001* | A n=30, B n=30 t.test | p < 0.001* | A n=30, B n=30 -- Two-group Comparison -------------------------------------------------------- -- Parameters -- Test: Welch two-sample t-test Direction: A - B Alternative: two.sided alpha: 0.050 Paired: FALSE -- Result -- v p < 0.001 (significant at alpha = 0.05) Welch Two Sample t-test data: value by group t = -4.7184, df = 56.741, p-value = 1.594e-05 alternative hypothesis: true difference in means between group A and group B is not equal to 0 95 percent confidence interval: -1.4961113 -0.6045215 sample estimates: mean in group A mean in group B 0.08245817 1.13277458 -- Descriptive statistics -- # A tibble: 2 x 7 group n mean sd median min max 1 A 30 0.0825 0.924 0.257 -2.21 1.60 2 B 30 1.13 0.795 0.943 -0.377 2.98 -- Normality (Shapiro-Wilk) -- A: n = 30, p = 0.170 B: n = 30, p = 0.948 → Medium samples (min n = 30). Data reasonably normal (all Shapiro p ≥ 0.01). -- Two-group Comparison -------------------------------------------------------- -- Parameters -- Test: Welch two-sample t-test Direction: A - B Alternative: two.sided alpha: 0.050 Paired: FALSE -- Result -- v p < 0.001 (significant at alpha = 0.05) Welch Two Sample t-test data: value by group t = -4.7184, df = 56.741, p-value = 1.594e-05 alternative hypothesis: true difference in means between group A and group B is not equal to 0 95 percent confidence interval: -1.4961113 -0.6045215 sample estimates: mean in group A mean in group B 0.08245817 1.13277458 -- Descriptive statistics -- # A tibble: 2 x 7 group n mean sd median min max 1 A 30 0.0825 0.924 0.257 -2.21 1.60 2 B 30 1.13 0.795 0.943 -0.377 2.98 -- Normality (Shapiro-Wilk) -- A: n = 30, p = 0.170 B: n = 30, p = 0.948 → Medium samples (min n = 30). Data reasonably normal (all Shapiro p ≥ 0.01). One-way ANOVA | p < 0.001* | A n=25, B n=25, C n=25 One-way ANOVA | p < 0.001* | A n=25, B n=25, C n=25 -- One-way Comparison ---------------------------------------------------------- -- Parameters -- Test: One-way ANOVA alpha: 0.050 -- Omnibus Test -- v p < 0.001 (significant at alpha = 0.05) eta_squared = 0.357, omega_squared = 0.336 Df Sum Sq Mean Sq F value Pr(>F) group 2 30.11 15.054 19.99 1.24e-07 *** Residuals 72 54.21 0.753 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 -- Descriptive statistics -- # A tibble: 3 x 7 group n mean sd median min max 1 A 25 -0.289 0.774 -0.308 -1.67 1.27 2 B 25 0.661 0.955 0.848 -1.77 2.20 3 C 25 1.25 0.865 1.46 -0.537 2.56 -- Normality (Shapiro-Wilk) -- A: n = 25, p = 0.267 B: n = 25, p = 0.211 C: n = 25, p = 0.264 -> Small samples (min n = 25). Data appears normal (all Shapiro p ≥ 0.05). -- Variance (Levene's test) -- p = 0.467 | equal variances: TRUE -- Post-hoc (tukey) -- # A tibble: 3 x 6 group2 group1 diff lwr upr `p adj` 1 B A 0.950 0.362 1.54 0.000687 2 C A 1.54 0.951 2.13 0.0000000721 3 C B 0.588 0.000817 1.18 0.0496 -- One-way Comparison ---------------------------------------------------------- -- Parameters -- Test: One-way ANOVA alpha: 0.050 -- Omnibus Test -- v p < 0.001 (significant at alpha = 0.05) eta_squared = 0.357, omega_squared = 0.336 Df Sum Sq Mean Sq F value Pr(>F) group 2 30.11 15.054 19.99 1.24e-07 *** Residuals 72 54.21 0.753 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 -- Descriptive statistics -- # A tibble: 3 x 7 group n mean sd median min max 1 A 25 -0.289 0.774 -0.308 -1.67 1.27 2 B 25 0.661 0.955 0.848 -1.77 2.20 3 C 25 1.25 0.865 1.46 -0.537 2.56 -- Normality (Shapiro-Wilk) -- A: n = 25, p = 0.267 B: n = 25, p = 0.211 C: n = 25, p = 0.264 -> Small samples (min n = 25). Data appears normal (all Shapiro p ≥ 0.05). -- Variance (Levene's test) -- p = 0.467 | equal variances: TRUE -- Post-hoc (tukey) -- # A tibble: 3 x 6 group2 group1 diff lwr upr `p adj` 1 B A 0.950 0.362 1.54 0.000687 2 C A 1.54 0.951 2.13 0.0000000721 3 C B 0.588 0.000817 1.18 0.0496 Chi-square test | p = 0.3156 | 3x2 | V = 0.152 (small) Chi-square test | p = 0.3156 | 3x2 | V = 0.152 (small) -- Categorical Association Test ------------------------------------------------ -- Parameters -- Test: Chi-square test Variables: treatment × response Table size: 3x2 alpha: 0.050 -- Result -- i p = 0.3156 (not significant at alpha = 0.05) Pearson's Chi-squared test data: cont_table X-squared = 2.3064, df = 2, p-value = 0.3156 -- Effect Size (Cramer's V) -- V: 0.152 Interpretation: small -- Observed Frequencies -- No Yes A 12 24 B 16 17 C 10 21 -- Expected Frequencies -- No Yes A 13.68 22.32 B 12.54 20.46 C 11.78 19.22 -- Pearson Residuals -- No Yes A -0.45 0.36 B 0.98 -0.76 C -0.52 0.41 → |residual| > 2 indicates significant deviation from independence -- Method Selection -- Table size: 3x2 Total N: 100 Min expected freq: 11.78 Cells with freq < 5: 0 Decision: All expected frequencies adequate: using standard chi-square test -- Categorical Association Test ------------------------------------------------ -- Parameters -- Test: Chi-square test Variables: treatment × response Table size: 3x2 alpha: 0.050 -- Result -- i p = 0.3156 (not significant at alpha = 0.05) Pearson's Chi-squared test data: cont_table X-squared = 2.3064, df = 2, p-value = 0.3156 -- Effect Size (Cramer's V) -- V: 0.152 Interpretation: small -- Observed Frequencies -- No Yes A 12 24 B 16 17 C 10 21 -- Expected Frequencies -- No Yes A 13.68 22.32 B 12.54 20.46 C 11.78 19.22 -- Pearson Residuals -- No Yes A -0.45 0.36 B 0.98 -0.76 C -0.52 0.41 → |residual| > 2 indicates significant deviation from independence -- Method Selection -- Table size: 3x2 Total N: 100 Min expected freq: 11.78 Cells with freq < 5: 0 Decision: All expected frequencies adequate: using standard chi-square test i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 3 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 10 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. pearson | 4 vars | 0/6 significant pairs (alpha = 0.05) pearson | 4 vars | 0/6 significant pairs (alpha = 0.05) i Found 0 significant pairs out of 6 tests. -- Correlation Analysis -------------------------------------------------------- -- Parameters -- Method: pearson Missing obs: pairwise.complete.obs P-adjust: none Variables: 4 alpha: 0.050 -- Descriptive Statistics -- variable n mean sd median min max x1 50 0.064934373 1.0686820 -0.14079713 -2.183967 2.215461 x2 50 -0.001664339 0.8130295 -0.06993174 -2.102329 2.387233 x3 50 -0.033696299 1.1076103 0.01153808 -1.995387 2.600142 x4 50 0.066717211 0.9896570 -0.02757658 -2.621345 2.246255 -- Correlation Summary -- Min: -0.136 Max: 0.262 Mean |r|: 0.143 -- Significant Pairs -- i Based on unadjusted p-values. 0 out of 6 pairs significant at alpha = 0.05 -- Correlation Analysis -------------------------------------------------------- -- Parameters -- Method: pearson Missing obs: pairwise.complete.obs P-adjust: none Variables: 4 alpha: 0.050 -- Descriptive Statistics -- variable n mean sd median min max x1 50 0.064934373 1.0686820 -0.14079713 -2.183967 2.215461 x2 50 -0.001664339 0.8130295 -0.06993174 -2.102329 2.387233 x3 50 -0.033696299 1.1076103 0.01153808 -1.995387 2.600142 x4 50 0.066717211 0.9896570 -0.02757658 -2.621345 2.246255 -- Correlation Summary -- Min: -0.136 Max: 0.262 Mean |r|: 0.143 -- Significant Pairs -- i Based on unadjusted p-values. 0 out of 6 pairs significant at alpha = 0.05 i Found 0 significant pairs out of 6 tests. i Found 0 significant pairs out of 6 tests. i Created directory: 'D:/temp/2026_03_29_17_50_16_6441/Rtmp25eyFL/evanverse_dest_47a4271b6029/nested' [ FAIL 0 | WARN 0 | SKIP 8 | PASS 911 ] ══ Skipped tests (8) ═══════════════════════════════════════════════════════════ • On CRAN (8): 'test-download.R:94:3', 'test-download.R:190:3', 'test-download.R:200:3', 'test-download.R:341:3', 'test-download.R:425:3', 'test-pkg.R:362:3', 'test-pkg.R:373:3', 'test-pkg.R:385:3' [ FAIL 0 | WARN 0 | SKIP 8 | PASS 911 ] > > proc.time() user system elapsed 22.03 1.84 24.90