Multiple-Response Frequency Analysis

🏛 Architecture, Planning & Design · 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 Architecture, Planning & Design 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 required 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?

  • Statistical analysis of measurements in the Architecture, Planning & Design 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: aktiviteler
  • 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 — Architecture, Planning & Design

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 Architecture, Planning & Design:

Peyzaj_Mimarligi/29_mr_frequency_activities.xlsx

🎬 Scenario

We summarise as frequencies the activities users do in the park (a multiple-choice question where several options can be ticked).

⚙️ Variable Selection

  • Multiple-response column: activities

Data Preview (First 5 Rows)

participant_idageactivities
121walking, running, picnic
239walking, running, picnic
338picnic, child game, dog walking
451walking, photography
542walking, running, dog walking

n = 250 · Columns: participant_id, age, activities

📈 MerQur Output

MULTIPLE-RESPONSE FREQUENCY ANALYSIS RESULT ───────────────────────────────────────────── Total cases n = 250 Respondents = 250 (100%) Park activities (walking, picnic, sport, children’s play, dog walking…) selected as multi-choice

💬 Interpretation

Park users were asked which activities they do in the park — a “multiple response” question where several options can be ticked. All 250 users selected at least one activity, so the response rate is 100%. Multiple-response frequency analysis shows how many times and by what percentage of users each activity was chosen; the totals exceed 100% because everyone can tick several boxes. Profiling users’ activity use is very useful in landscape planning to determine which activities need dedicated equipment/spaces.

⚠ 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 Architecture, Planning & Design file.

▶ Multiple-Response Frequency Analysis — video walkthrough

This section is part of the Çok Seçimli Yanıtlar video (4 analyses in one video). The link below jumps straight to 0:00, where this analysis begins. Narration is in Turkish.

▶ Watch this analysis (0:00) 📺 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.