Test Dataset for Chi-Square Post-Hoc Analysis
chisqposttest_test_data.RdA comprehensive test dataset specifically designed for testing the chisqposttest function. Contains multiple categorical variables with known associations of different strengths, edge cases, and missing data patterns.
Usage
data("chisqposttest_test_data")Format
A data frame with 300 observations and 14 variables:
- PatientID
Patient identifier (1-300)
- Treatment
Treatment group: "Standard", "Experimental"
- Response
Treatment response: "No Response", "Response" (strongly associated with Treatment)
- Sex
Patient sex: "Male", "Female" (balanced)
- TumorGrade
Tumor grade: "Grade 1", "Grade 2", "Grade 3"
- TumorStage
Tumor stage: "Stage I", "Stage II", "Stage III" (moderately associated with TumorGrade)
- Institution
Hospital: "Hospital A", "Hospital B", "Hospital C", "Hospital D"
- QualityScore
Quality rating: "High", "Low" (weakly associated with Institution)
- RandomVar1
Random variable: "Group A", "Group B", "Group C" (no associations)
- RandomVar2
Random variable: "Type X", "Type Y" (no associations)
- RareCategory
Frequency category: "Common", "Uncommon", "Rare" (unbalanced)
- BinaryOutcome
Binary outcome: "Negative", "Positive" (associated with RareCategory)
- AgeGroup
Age category: "Young", "Middle", "Elderly"
- BiomarkerStatus
Biomarker status: "Negative", "Positive" (moderately associated with AgeGroup)
Details
This dataset contains several types of associations designed to test different aspects of chi-square post-hoc analysis:
Strong Associations:
Treatment -> Response: Clear treatment effect with odds ratio ~5
Moderate Associations:
TumorGrade -> TumorStage: Higher grades associated with advanced stages
AgeGroup -> BiomarkerStatus: Age-related biomarker expression pattern
Weak Associations:
Institution -> QualityScore: Institutional quality differences
RareCategory -> BinaryOutcome: Effect in rare category with small cell counts
No Associations:
RandomVar1 ⊥ RandomVar2: Independent random variables for null hypothesis testing
The dataset includes approximately 5% missing data in Treatment, Sex, and TumorGrade variables to test missing data handling options.
Source
Simulated data created for testing purposes. Associations are based on realistic clinical scenarios but data is artificially generated.
See also
chisqposttest, histopathology
Examples
# Load the dataset
data(chisqposttest_test_data)
# Examine structure
str(chisqposttest_test_data)
#> 'data.frame': 300 obs. of 14 variables:
#> $ PatientID : int 1 2 3 4 5 6 7 8 9 10 ...
#> $ Treatment : Factor w/ 2 levels "Standard","Experimental": 1 1 2 1 1 2 1 2 1 1 ...
#> $ Response : Factor w/ 2 levels "No Response",..: 1 1 1 1 1 2 1 2 1 1 ...
#> $ Sex : Factor w/ 2 levels "Male","Female": 2 2 2 2 1 1 2 2 2 2 ...
#> $ TumorGrade : Factor w/ 3 levels "Grade 1","Grade 2",..: 3 2 1 2 3 3 1 2 NA 3 ...
#> $ TumorStage : Factor w/ 3 levels "Stage I","Stage II",..: 3 3 1 2 2 3 2 2 3 3 ...
#> $ Institution : Factor w/ 4 levels "Hospital A","Hospital B",..: 1 1 3 1 3 4 1 1 3 1 ...
#> $ QualityScore : Factor w/ 2 levels "High","Low": 1 2 2 1 1 1 1 1 2 1 ...
#> $ RandomVar1 : Factor w/ 3 levels "Group A","Group B",..: 2 2 2 2 1 2 1 1 1 2 ...
#> $ RandomVar2 : Factor w/ 2 levels "Type X","Type Y": 1 2 2 1 2 2 1 2 1 1 ...
#> $ RareCategory : Factor w/ 3 levels "Common","Uncommon",..: 2 2 1 1 1 1 2 1 1 1 ...
#> $ BinaryOutcome : Factor w/ 2 levels "Negative","Positive": 1 2 1 1 2 1 2 1 1 1 ...
#> $ AgeGroup : Factor w/ 3 levels "Young","Middle",..: 3 2 1 1 3 2 2 2 1 2 ...
#> $ BiomarkerStatus: Factor w/ 2 levels "Negative","Positive": 2 1 2 1 2 2 2 1 1 1 ...
#> - attr(*, "description")= chr "Test dataset for chisqposttest function with known associations"
#> - attr(*, "associations")=List of 4
#> ..$ strong : chr "Treatment -> Response"
#> ..$ moderate: chr [1:2] "TumorGrade -> TumorStage" "AgeGroup -> BiomarkerStatus"
#> ..$ weak : chr [1:2] "Institution -> QualityScore" "RareCategory -> BinaryOutcome"
#> ..$ none : chr "RandomVar1 ⊥ RandomVar2"
#> - attr(*, "created")= Date[1:1], format: "2025-07-02"
#> - attr(*, "sample_size")= num 300
# Example 1: Strong association (should be highly significant)
chisqposttest(
data = chisqposttest_test_data,
rows = "Treatment",
cols = "Response",
posthoc = "bonferroni"
)
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#>
#> CHI-SQUARE POST-HOC TESTS
#>
#> <div style='padding: 15px; background-color: #fff3cd; border: 1px
#> solid #ffc107; color: #856404;'>Warning:33% of cells have expected
#> counts < 5. Chi-square test assumptions violated. Use Fisher's exact
#> test for more reliable results.
#>
#> Chi-Square Test Results
#> ──────────────────────────────────────────────
#> Statistic Value df p-value
#> ──────────────────────────────────────────────
#> Chi-Square 66.63312 2 < .0000001
#> ──────────────────────────────────────────────
#>
#>
#> <table style="border-collapse: collapse; width: 100%; margin: 15px 0;
#> font-family: 'Segoe UI', system-ui, sans-serif; font-size:
#> 13px; background-color: white; box-shadow: 0 1px 3px
#> rgba(0,0,0,0.1);">
#>
#> <tr style="background-color: #e3f2fd;">
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #f8f9fa;">
#> <div style="font-weight: bold; color: #495057;">
#> Response →
#> <br/>
#> Treatment ↓
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">Response
#> <div style="font-size: 13px; color: #212529;">No Response
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">Response
#> <div style="font-size: 13px; color: #212529;">Response
#>
#>
#>
#>
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">Treatment
#> <div style="font-size: 13px; color: #212529;">Standard
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">88
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">28
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">Treatment
#> <div style="font-size: 13px; color: #212529;">Experimental
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">49
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">130
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">Treatment
#> <div style="font-size: 13px; color: #212529;">NA
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">2
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">3
#>
#>
#>
#> <div style="padding: 10px; background-color: #e3f2fd; border-left: 4px
#> solid #1976d2; margin: 8px 0;">
#> Method notice:
#> Pairwise comparisons with expected cell counts < 5 are automatically
#> analysed with Fisher's exact test; the reported p-values use that
#> exact method.
#>
#> Pairwise Comparison Results
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Comparison Test Method Chi-Square p-value Adj. p-value Effect Size (Phi) 95% CI (Phi) Significant
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Standard vs Experimental Chi-square 66.5303419 < .0000001 < .0000001 0.47500000 Yes
#> Standard vs NA Fisher's exact 3.2350414 0.1056590 0.4226362 0.16400000 No
#> Experimental vs NA Fisher's exact 0.3870168 0.6181533 1.0000000 0.04600000 No
#> No Response vs Response Fisher's exact 66.6331188 < .0000001 < .0000001 0.47100000 Yes
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>
# Example 2: Moderate association (should be significant with post-hoc differences)
chisqposttest(
data = chisqposttest_test_data,
rows = "TumorGrade",
cols = "TumorStage",
posthoc = "fdr"
)
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#> Warning: Chi-squared approximation may be incorrect
#>
#> CHI-SQUARE POST-HOC TESTS
#>
#> <div style='padding: 15px; background-color: #fff3cd; border: 1px
#> solid #ffc107; color: #856404;'>Warning:25% of cells have expected
#> counts < 5. Chi-square test assumptions violated. Use Fisher's exact
#> test for more reliable results.
#>
#> Chi-Square Test Results
#> ──────────────────────────────────────────────
#> Statistic Value df p-value
#> ──────────────────────────────────────────────
#> Chi-Square 109.4691 6 < .0000001
#> ──────────────────────────────────────────────
#>
#>
#> <table style="border-collapse: collapse; width: 100%; margin: 15px 0;
#> font-family: 'Segoe UI', system-ui, sans-serif; font-size:
#> 13px; background-color: white; box-shadow: 0 1px 3px
#> rgba(0,0,0,0.1);">
#>
#> <tr style="background-color: #e3f2fd;">
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #f8f9fa;">
#> <div style="font-weight: bold; color: #495057;">
#> TumorStage →
#> <br/>
#> TumorGrade ↓
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">TumorStage
#> <div style="font-size: 13px; color: #212529;">Stage I
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">TumorStage
#> <div style="font-size: 13px; color: #212529;">Stage II
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">TumorStage
#> <div style="font-size: 13px; color: #212529;">Stage III
#>
#>
#>
#>
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">TumorGrade
#> <div style="font-size: 13px; color: #212529;">Grade 1
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">56
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">24
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">7
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">TumorGrade
#> <div style="font-size: 13px; color: #212529;">Grade 2
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">28
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">71
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">22
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">TumorGrade
#> <div style="font-size: 13px; color: #212529;">Grade 3
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">6
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">32
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">49
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">TumorGrade
#> <div style="font-size: 13px; color: #212529;">NA
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">0
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">3
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">2
#>
#>
#>
#> <div style="padding: 10px; background-color: #e3f2fd; border-left: 4px
#> solid #1976d2; margin: 8px 0;">
#> Method notice:
#> Pairwise comparisons with expected cell counts < 5 are automatically
#> analysed with Fisher's exact test; the reported p-values use that
#> exact method.
#>
#> Pairwise Comparison Results
#> ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Comparison Test Method Chi-Square p-value Adj. p-value Effect Size (Phi) 95% CI (Phi) Significant
#> ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Grade 1 vs Grade 2 Chi-square 35.741905 < .0000001 < .0000001 0.4150000 Yes
#> Grade 1 vs Grade 3 Chi-square 72.965438 < .0000001 < .0000001 0.6480000 Yes
#> Grade 1 vs NA Fisher's exact 9.846232 0.0045976 0.0059112 0.3270000 Yes
#> Grade 2 vs Grade 3 Chi-square 34.637706 < .0000001 < .0000001 0.4080000 Yes
#> Grade 2 vs NA Fisher's exact 2.358454 0.2905058 0.3268190 0.1370000 No
#> Grade 3 vs NA Fisher's exact 1.242070 0.5701787 0.5701787 0.1160000 No
#> Stage I vs Stage II Fisher's exact 46.531754 < .0000001 < .0000001 0.4600000 Yes
#> Stage I vs Stage III Fisher's exact 74.117520 < .0000001 < .0000001 0.6600000 Yes
#> Stage II vs Stage III Fisher's exact 28.625696 0.0000014 0.0000021 0.3690000 Yes
#> ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>
# Example 3: No association (should be non-significant)
chisqposttest(
data = chisqposttest_test_data,
rows = "RandomVar1",
cols = "RandomVar2",
posthoc = "bonferroni"
)
#>
#> CHI-SQUARE POST-HOC TESTS
#>
#> character(0)
#>
#> Chi-Square Test Results
#> ─────────────────────────────────────────────
#> Statistic Value df p-value
#> ─────────────────────────────────────────────
#> Chi-Square 6.359561 2 0.0415948
#> ─────────────────────────────────────────────
#>
#>
#> <table style="border-collapse: collapse; width: 100%; margin: 15px 0;
#> font-family: 'Segoe UI', system-ui, sans-serif; font-size:
#> 13px; background-color: white; box-shadow: 0 1px 3px
#> rgba(0,0,0,0.1);">
#>
#> <tr style="background-color: #e3f2fd;">
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #f8f9fa;">
#> <div style="font-weight: bold; color: #495057;">
#> RandomVar2 →
#> <br/>
#> RandomVar1 ↓
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RandomVar2
#> <div style="font-size: 13px; color: #212529;">Type X
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RandomVar2
#> <div style="font-size: 13px; color: #212529;">Type Y
#>
#>
#>
#>
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RandomVar1
#> <div style="font-size: 13px; color: #212529;">Group A
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">47
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">49
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RandomVar1
#> <div style="font-size: 13px; color: #212529;">Group B
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">51
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">57
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RandomVar1
#> <div style="font-size: 13px; color: #212529;">Group C
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">61
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">35
#>
#>
#>
#> character(0)
#>
#> Pairwise Comparison Results
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Comparison Test Method Chi-Square p-value Adj. p-value Effect Size (Phi) 95% CI (Phi) Significant
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Group A vs Group B Chi-square 0.06136889 0.8043453 1.0000000 0.01700000 No
#> Group A vs Group C Chi-square 4.14814815 0.0416801 0.1667203 0.14700000 No
#> Group B vs Group C Chi-square 5.46676048 0.0193815 0.0775261 0.16400000 No
#> Type X vs Type Y Chi-square 6.35956109 0.0415948 0.1663791 0.14600000 No
#> ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>
# Example 4: Edge case with rare categories
chisqposttest(
data = chisqposttest_test_data,
rows = "RareCategory",
cols = "BinaryOutcome",
posthoc = "fdr"
)
#>
#> CHI-SQUARE POST-HOC TESTS
#>
#> character(0)
#>
#> Chi-Square Test Results
#> ─────────────────────────────────────────────
#> Statistic Value df p-value
#> ─────────────────────────────────────────────
#> Chi-Square 24.74713 2 0.0000042
#> ─────────────────────────────────────────────
#>
#>
#> <table style="border-collapse: collapse; width: 100%; margin: 15px 0;
#> font-family: 'Segoe UI', system-ui, sans-serif; font-size:
#> 13px; background-color: white; box-shadow: 0 1px 3px
#> rgba(0,0,0,0.1);">
#>
#> <tr style="background-color: #e3f2fd;">
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #f8f9fa;">
#> <div style="font-weight: bold; color: #495057;">
#> BinaryOutcome →
#> <br/>
#> RareCategory ↓
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">BinaryOutcome
#> <div style="font-size: 13px; color: #212529;">Negative
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">BinaryOutcome
#> <div style="font-size: 13px; color: #212529;">Positive
#>
#>
#>
#>
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RareCategory
#> <div style="font-size: 13px; color: #212529;">Common
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">144
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">56
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RareCategory
#> <div style="font-size: 13px; color: #212529;">Uncommon
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">53
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">28
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">RareCategory
#> <div style="font-size: 13px; color: #212529;">Rare
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">3
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">16
#>
#>
#>
#> character(0)
#>
#> Pairwise Comparison Results
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Comparison Test Method Chi-Square p-value Adj. p-value Effect Size (Phi) 95% CI (Phi) Significant
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#> Common vs Uncommon Chi-square 1.186668 0.2760028 0.2760028 0.06500000 No
#> Common vs Rare Chi-square 24.843523 0.0000006 0.0000025 0.33700000 Yes
#> Uncommon vs Rare Chi-square 15.392437 0.0000873 0.0001164 0.39200000 Yes
#> Negative vs Positive Chi-square 24.747135 0.0000042 0.0000085 0.28700000 Yes
#> ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
#>
# Example 5: Missing data handling
chisqposttest(
data = chisqposttest_test_data,
rows = "Treatment",
cols = "Sex",
excl = TRUE # Exclude missing values
)
#>
#> CHI-SQUARE POST-HOC TESTS
#>
#> character(0)
#>
#> Chi-Square Test Results
#> ───────────────────────────────────────────────
#> Statistic Value df p-value
#> ───────────────────────────────────────────────
#> Chi-Square 0.02066086 1 0.8857067
#> ───────────────────────────────────────────────
#>
#>
#> <table style="border-collapse: collapse; width: 100%; margin: 15px 0;
#> font-family: 'Segoe UI', system-ui, sans-serif; font-size:
#> 13px; background-color: white; box-shadow: 0 1px 3px
#> rgba(0,0,0,0.1);">
#>
#> <tr style="background-color: #e3f2fd;">
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #f8f9fa;">
#> <div style="font-weight: bold; color: #495057;">
#> Sex →
#> <br/>
#> Treatment ↓
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom: 2px;">Sex
#> <div style="font-size: 13px; color: #212529;">Male
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center; background-color: #e3f2fd;">
#> <div style="font-weight: bold;">
#> <div style="font-size: 11px; color: #6c757d; margin-bottom: 2px;">Sex
#> <div style="font-size: 13px; color: #212529;">Female
#>
#>
#>
#>
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">Treatment
#> <div style="font-size: 13px; color: #212529;">Standard
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">50
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">62
#>
#>
#> <th style="border: 1px solid #e1e5e9; padding: 8px; background-color:
#> #e3f2fd; font-weight: bold;">
#>
#> <div style="font-size: 11px; color: #6c757d; margin-bottom:
#> 2px;">Treatment
#> <div style="font-size: 13px; color: #212529;">Experimental
#>
#>
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">81
#> <td style="border: 1px solid #e1e5e9; padding: 8px; text-align:
#> center;">97
#>
#>
#>
#> <div style='padding: 15px; background-color: #fff3cd; border: 1px
#> solid #ffc107;'>Post-hoc Testing Not Performed: Overall chi-square
#> test is not significant (p = 0.886 ≥ 0.05). Post-hoc pairwise
#> comparisons are only valid when the overall test is significant.
#> Running pairwise tests after a non-significant omnibus test increases
#> Type I error (false positives) and constitutes data dredging.