Multiple-Response Frequency Analysis

🏥 Health Sciences · Multiple-Response Frequency Analysis

Multiple-Response Frequency Analysis

Kategorik · MR

Multiple-Response Frequency Analysis is one of the statistical analyses applied automatically in MerQur. This page illustrates — on a Health Sciences sample dataset — how the analysis is run, what the MerQur output looks like, and how the result is reported in APA 7 format.

🎯 What is it for?

Multiple-Response Frequency Analysis automatically performs all assumption checks required for the data type (normality, homogeneity of variance, etc.) in the background and presents the results in a clear table + chart. Automatic APA 7-formatted interpretation, effect sizes (Cohen’s d, η², R²) and 95% confidence intervals are reported.

📌 When is it used?

  • Statistical analysis of measurements in the Health Sciences domain
  • To produce APA 7-compatible result tables for academic publications
  • Hypothesis testing and decision-making processes
  • Undergraduate / master’s / PhD theses after the appropriate method has been selected

📐 Assumptions

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

If assumptions are violated, MerQur automatically suggests a non-parametric or robust alternative.

🛠 How to do it in MerQur

1

Load the data. Select the sample file from File → Open. MerQur auto-detects column types.

2

Select the analysis. From the left side select Multiple-Response Frequency Analysis.

3

Panel assignments (form fields in the program):

  • MR Set kaynak: komorbidite
  • MR metadata: None
4

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

5

▶ Run — click the button. Results are produced automatically as a table + chart.

6

📄 Export to Word. APA 7-formatted report with italic statistical symbols.

📊 Sample Dataset — Health Sciences

ℹ Note: The scenario, MerQur output and interpretation below were produced by actually running the real example dataset in MerQur. Numeric results on your own data will differ; the goal is to show how the analysis is set up and interpreted end-to-end.

🎬 Example File

This analysis is demonstrated on the following example dataset for Health Sciences:

Tip/29_mr_frequency_comorbidity.xlsx

🎬 Scenario

We analyze a multi-select comorbidity question. For a multi-select question, multiple-response frequency is appropriate.

⚙️ Variable Selection

  • Variables: comorbidity (coklu yanit / multi-response)

Data Preview (First 5 Rows)

patient_idagecomorbidity
182copd, asthma
254copd
349hypertension
465hypertension, diabetes
560hypertension, diabetes, cardiovascular, rheumatic

n = 250 · Columns: patient_id, age, comorbidity

📈 MerQur Output

MULTIPLE-RESPONSE FREQUENCY ANALYSIS RESULT ───────────────────────────────────────────── Total cases n = 250 Respondents = 250 (100%) multi-select “comorbidity” question

💬 Interpretation

We analyzed a question where several options could be checked (“which comorbidities are present?”): each of 250 patients listed one or more comorbidities. Multiple-response frequency analysis gives the count of checks per option and both the response and case percentages separately (percentages sum to over 100, because a patient can have several comorbidities). In medicine it is the standard method for correctly summarizing the comorbidity profiles of multi-morbid patients (co-existing diseases).

⚠ Common Mistakes

  • Misidentifying the data type (e.g., loading a categorical variable as numeric)
  • Skipping assumption checks and going straight to the p-value
  • Failing to report effect size — APA 7 requires both p and effect size
  • Failing to apply a Type I error correction (Bonferroni/Tukey) in multiple comparisons
  • Not switching to a non-parametric alternative when n is insufficient

📹 Video Walkthrough

Watch the video below for an end-to-end walkthrough of this analysis on a Health Sciences file.

▶ Multiple-Response Frequency Analysis — video walkthrough

A complete end-to-end walkthrough of this analysis in MerQur, narrated on screen. Narration is in Turkish.

▶ Watch the video 📺 All videos

📚 If You Used This Analysis, Cite MerQur

If you performed this analysis using MerQur in a scientific study, please use the citation below as part of your academic citation obligations (APA 7):

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

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

Sources:
  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.