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Frailty Cox

Research Disciplines → Sport Sciences → Frailty Cox

🏃 Sport Sciences · Frailty Cox

Frailty Cox

Sağkalım · Küme

Frailty Cox is one of the statistical analyses applied automatically in MerQur. This page illustrates — on a Sport 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?

Frailty Cox 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 to 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 Sport 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 Frailty Cox.

3

Panel assignments (form fields in the program):

  • duration_col: None
  • event_col: olay
  • feature_cols: ['kariyer_yil']
  • cluster_col: klinik_grup
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 — Sport 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 Sport Sciences:

Spor_Bilimleri/93_frailty_cox.xlsx

🎬 Scenario

We model the club-specific hidden risk as frailty in clustered survival data. For shared hidden risk, frailty Cox is appropriate.

⚙️ Variable Selection

  • Time: career_year
  • Event: event
  • Predictor(s): clinical_group (faktorize/factorized)
  • Cluster: club_id

Data Preview (First 5 Rows)

athlete_idclub_idcareer_yeareventclinical_group
116.211K1
211.810K4
314.581K3
411.230K2
515.620K2

n = 120 · Columns: athlete_id, club_id, career_year, event, clinical_group

📈 MerQur Output

FRAILTY COX RESULT ───────────────────────────────────────────── Concordance = 0.535 cg_n: p = 0.340 ns time: career_year, event: event cluster: club_id (frailty)

💬 Interpretation

In clustered survival data (athletes within the same club) we modeled the club-specific unobserved risk as “frailty” (a random effect); the clinical-group effect is non-significant (p = 0.34). Frailty Cox accounts for the hidden risk shared by units in the same cluster — solving the independence assumption that standard Cox violates. In sports science it is the right choice for event data clustered within a club/team (shared hidden risk).

⚠ 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 Sport Sciences file.

▶ Frailty Cox — video walkthrough

This section is part of the Sağkalım Analizi video (7 analyses in one video). The link below jumps straight to 9:53, where this analysis begins. Narration is in Turkish.

▶ Watch this analysis (9:53) 📺 All videos

🔀 The same analysis in other disciplines:
🎓 Education Sciences · 🧪 Natural Sciences & Mathematics · 🏛 Architecture, Planning & Design · ⚙ Engineering · 🏥 Health Sciences · 📊 Social, Humanities & Admin Sciences · 🌾 Agriculture, Forestry & Aquatic

📚 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.