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Cochran-Mantel-Haenszel Testi

Fields → Ziraat, Orman ve Su Ürünleri → Cochran-Mantel-Haenszel Testi

🌾 Ziraat, Orman ve Su Ürünleri · Cochran-Mantel-Haenszel Testi

Cochran-Mantel-Haenszel Testi

Kategorik · Stratifiye

Cochran-Mantel-Haenszel Test is one of the statistical analyses automatically performed in MerQur. This page illustratively demonstrates how the analysis is applied to a sample dataset from the field of Agriculture, Forestry & Fisheries, how the MerQur output appears, and how it is reported in APA 7 format.

🎯 What is it for?

Cochran-Mantel-Haenszel Test automatically applies all the necessary assumption checks (normality, homogeneity of variance, etc.) for the relevant data type in the background and presents the results with a clear table + chart. Automatic interpretation in the APA 7 standard, effect sizes such as Cohen’s d/η²/R², and 95% confidence intervals are reported.

📌 When is it used?

  • In the statistical analysis of measurements belonging to the Agriculture, Forestry and Aquaculture field
  • To produce APA 7 compliant result tables for academic publication
  • In hypothesis testing and decision-making processes
  • After selecting an appropriate method in undergraduate / master’s / doctoral theses

📐 Assumptions

  • Appropriate scale — Variables must be at the scale level required by the analysis (nominal/ordinal/interval/ratio)
  • Independent observations — Observations must come from mutually independent individuals
  • Adequate sample — The minimum n requirement for the analysis must be met
  • Outlier check — Outliers must be detected and evaluated

If the assumptions are violated, MerQur automatically steers you toward a non-parametric or robust alternative.

🛠 How to do it in MerQur

1

Load the data. Select the sample file from the File → Open menu. MerQur automatically detects the column types.

2

Select the analysis. Select Cochran-Mantel-Haenszel Test from the left sidebar.

3

Panel assignments (form fields in the program):

  • error: cats() got an unexpected keyword argument 'max_unique'
4

Optional settings. Effect size ✓ · 95% confidence interval ✓ · Assumption checks (automatic).

5

Press the ▶ Run button. The results are automatically generated as a table + chart.

6

📄 Export to Word. A report in APA 7 format with italicized statistical symbols.

📊 Sample Dataset — Ziraat, Orman ve Su Ürünleri

ℹ Note: The MerQur output and interpretation tables on this page are illustrative and intended to help understand the analysis. The numerical results for your own data may differ; this page does not have to match the YouTube video walkthrough exactly.

🎬 Example File Used in the Video

The YouTube video walkthrough of this page was recorded using the following sample file for the Agriculture, Forestry and Aquaculture field:

MerQur_Hoca_Tanitim/Ziraat_Orman_Su/26_cmh_koruma_hastalik_bolge.xlsx

Topic: Application of the Cochran-Mantel-Haenszel Test analysis on a real sample data set from the Agriculture, Forestry and Aquaculture field.

Data Preview (First 5 Rows)

parsel_idbolgeyontemyuksek_verim
1KaradenizGelenekselHayır
2KaradenizGelenekselEvet
3KaradenizGelenekselEvet
4KaradenizGelenekselEvet
5KaradenizGelenekselHayır

n = 360 · Sütunlar: parsel_id, bolge, yontem, yuksek_verim

MerQur Output (Illustrative)

CROSS TABLE (bolge × yontem) ───────────────────────────────────────────── Category A Category B Total Level 1 42 (%65) 23 (%35) 65 Level 2 18 (%32) 37 (%68) 55 Total 60 60 120 Chi-Square Test: χ²(1) = 14.71, p < .001 Cramer’s V = 0.350 (moderate-to-strong association)

MerQur Interpretation (Plain Language)

A significant association was found between bolge and yontem (χ² = 14.71, p < .001). The Cramer’s V = .35 value indicates a moderate-to-strong association.

APA 7 Interpretation (Academic Format · Illustrative)

The Chi-Square test of independence showed that there is a statistically significant association between the bolge and yontem variables, χ²(1, N = 120) = 14.71, p < .001, Cramer’s V = .35. This result supports that the two variables are not independent of each other and are associated at a moderate-to-strong level.

⚠ Common Mistakes

  • Specifying the data type incorrectly (e.g., loading a categorical variable as numeric)
  • Skipping the assumption checks and looking directly at the p-value
  • Not reporting the effect size — APA 7 requires both p and the effect size
  • Not applying a Type I error correction (Bonferroni/Tukey) in multiple comparisons
  • Not switching to a non-parametric alternative when n is insufficient

📹 Video Walkthrough

You can watch the video below for an end-to-end application of this analysis using the Agriculture, Forestry and Aquaculture file.

▶

The video will soon be uploaded to the MerQur YouTube channel

📺 MerQur YouTube Channel

🔀 The same analysis in other Core Fields:
🎓 Educational Sciences · 🧪 Natural Sciences and Mathematics · 🏛 Architecture, Planning and Design · ⚙ Engineering · 🏥 Health Sciences · 📊 Social, Humanities and Administrative Sciences · 🏃 Sports Sciences

📚 If You Used This Analysis, Cite MerQur

If you performed this analysis in a scientific study using MerQur, please use the following citation (APA 7) in accordance with the academic citation requirement:

Örücü, Ö. K. (2026). MerQur: An Integrated Academic Data Analysis and Reporting Platform [Computer Software] (Version 1.0.0). https://doi.org/10.53463/merqur.2026001

For BibTeX, RIS, EndNote and the English equivalent: all citation formats →

References:
  1. American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.).
  2. Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th ed.). Sage.
  3. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.